National Institutes of Health Stroke Scale (NIHSS)

Purpose

The National Institutes of Health StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Scale (NIHSS) is a 15-item impairment scale, intended to evaluate neurologic outcome and degree of recovery for patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. The scale assesses level of consciousness, extraocular movements, visual fields, facial muscle function, extremity strength, sensory function, coordination (ataxia), language (aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada)), speech (dysarthria), and hemi-inattention (neglect) (Lyden, Lu, & Jackson, 1999; Lyden, Lu, & Levine, 2001). The NIHSS was designed to assess differences in interventions in clinical trials, although its use is increasing in patient care as an initial assessment tool and in planningPlanning ability involves anticipating future events, formulating a goal or endpoint, and devising a sequence of steps or actions that will achieve the goal or endpoint” (Anderson, 2008, p. 17)
postacute care disposition (Schlegel et al., 2003; Schlegel, Tanne, Demchuk, Levine, & Kasner, 2004).

In-Depth Review

Purpose of the measure

The NIHSS is a 15-item impairment scale, intended to evaluate neurologic outcome and degree of recovery for patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. More. The scale assesses level of consciousness, extraocular movements, visual fields, facial muscle function, extremity strength, sensory function, coordination (ataxia), language (aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person's ability to communicate. It is most often the result of stroke or head injury.
An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person's intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada)), speech (dysarthria), and hemi-inattention (neglect) (Lyden, Lu, & Jackson, 1999; Lyden, Lu, & Levine, 2001). The NIHSS was designed to assess differences in interventions in clinical trials, although its use is increasing in patient care as an initial assessment tool and in planningPlanning ability involves anticipating future events, formulating a goal or endpoint, and devising a sequence of steps or actions that will achieve the goal or endpoint" (Anderson, 2008, p. 17)
postacute care disposition (Schlegel et al., 2003; Schlegel, Tanne, Demchuk, Levine, & Kasner, 2004).

Available versions

Original version: Brott, Adams, Olinger, Marler, Barsan, Biller, Spilker, Holleran, Eberle, Hertzberg, Rorick, Moomaw, and Walker (1989).

Features of the measure

Items:
Items of the NIHSS are based on three previously used scales, the Toronto StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Scale, the Oxbury Initial Severity Scale and the Cincinnati StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Scale (Brott et al., 1989).

The scale has 15 items in total which assess the following:

1. Level of consciousness

• ResponsivenessThe ability of an instrument to detect clinically important change over time.
  of the patient (rated from 0 – 3).
• Questions: Patients are asked to state the month and their age (rated from 0 – 2).
• Commands: The patient is asked to open and close the eyes and then to grip and release the non-paretic hand (hand not affected by partial motor paralysis) (rated from 0 – 2).

2. Best gaze

• Horizontal eye movements of patient (rated from 0 – 2).

3. Visual

• To assess the presence of hemianopia (rated from 0 – 3).

4. Facial palsy

• Patients are asked to show their teeth or raise their eyebrows and close their eyes. Look for symmetry (rated from 0 – 3).

5. Motor arm

• Left arm: Arm is extended (palms down) 90 degrees (if sitting) or 45 degrees (if supine). Drift is scored if the arm falls before 10 seconds (rated from 0 – 4, or UN if amputation or joint fusion).
• Right arm: Same as in a.

6. Motor leg

• Left leg: Leg is raised at 30 degrees (supine). Drift is scored if the leg falls before 5 seconds (rated from 0 – 4, or UN if amputation or joint fusion).
• Right leg: Same as in a.

7. Limb ataxia

• Finger-to-nose and heel-to-shin test (rated from 0 – 2, or UN if amputation or joint fusion).

8. Sensory function

• If level of consciousness is impaired, score if a grimace or an asymmetric withdrawal is observed (rated from 0 – 2).

9. Best language (aphasiaAphasia is an acquired disorder caused by an injury to the brain and affects a person’s ability to communicate. It is most often the result of stroke or head injury.
   An individual with aphasia may experience difficulty expressing themselves when speaking, difficulty understanding the speech of others, and difficulty reading and writing. Sadly, aphasia can mask a person’s intelligence and ability to communicate feelings, thoughts and emotions. (The Aphasia Institute, Canada))

• Standard pictures are named (rated from 0 – 3).

10. Dysarthria

• Patient is asked to read or repeat words from a list (rated from 0 – 2, or UN if intubated or other physical barrier).

11. Extinction and inattention (formerly called neglect)

• Sufficient information to detect neglect may be obtained from prior testing (rated from 0 – 2).

An additional item that measures distal motor function has been used in a few drug trials, but is not widely used in ongoing research or in clinical practice.

Time:
The examination requires less than 10 minutes to complete.

Scoring:
Each item is scored from 0 – 2, 0 – 3, or 0 – 4, and untestable items are scored as “UN”. A score of 0 indicates normal performance. Total scores on the NIHSS range from 0 – 42, with higher values reflecting more severe cerebral infarcts. StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More severity is further stratified in the following way:

(Source: Brott et al., 1989)

≥ 25 – Very severe neurological impairment

5-14 – Mild to adequately severe neurological impairment

< 5 – Mild impairment

The predictive value of the scale can also aid in planningPlanning ability involves anticipating future events, formulating a goal or endpoint, and devising a sequence of steps or actions that will achieve the goal or endpoint” (Anderson, 2008, p. 17)
a patient’s rehabilitation or long-term care needs, even as early as the day of admission. NIHSS scores can be interpreted in the following way:

(Source: Schlegel et al., 2003; Rundek et al., 2000; Goldstein & Samsa, 1997; DeGraba, Hallenbeck, Pettigrew, Dutha, & Kelly, 1999)

≥ 14 – Severe: Long-term care in nursing facility required

6-13 – adequate: Acute inpatient rehabilitation required

≤ 5 – Mild: 80% with this score are discharged home

The NIHSS can be completed and scored automatically at the following link:
http://sitemaker.umich.edu/chant/yale_nihss_calculator

Equipment:
None typically reported.

Subscales:
The subscaleMany measurement instruments are multidimensional and are designed to measure more than one construct or more than one domain of a single construct. In such instances subscales can be constructed in which the various items from a scale are grouped into subscales. Although a subscale could consist of a single item, in most cases subscales consist of multiple individual items that have been combined into a composite score (National Multiple Sclerosis Society).
items encompass level of consciousness, vision, extraocular movements, facial palsy, limb strength, ataxia, sensation, and speech and language.

Training:
A trained observer rates the patent’s ability to answer questions and perform activitiesAs defined by the International Classification of Functioning, Disability and Health, activity is the performance of a task or action by an individual. Activity limitations are difficulties in performance of activities. These are also referred to as function.
. Training is minimal and is available through instructional videos: a 45-minute training program tape, and two certification tapes (Lyden et al., 1994), or alternatively one can be trained and certified online at the following website: http://www.nihstrokescale.org/. A new training DVD is now available and has established reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
(Lyden et al., 2005).

It is important to note that one must be both trained and certified in order to administer the NIHSS.

As the NIHSS was designed as an observational scale, measurement by self-report or by telephone is not possible. However, measurement by video telemedicine appears to be reliable and could offer a method for remote assessment (Meyer et al., 2005; Shafqat, Kvedar, Guanci, Chang, & Schwamm, 1999). This method of administration would require slightly more time to complete.

To see video clips of the NIHSS items being administered by telemedicine, visit the following link: https://telestroke.massgeneral.org/about.asp

Schmülling, Grond, Rudolf, and Kiencke (1998) examined whether the NIHSS could be reliably administered without any formal training program. The results of this study suggest that good inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the NIHSS depends on adequate training of the raters. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
among untrained raters was only poor (kappa = 0.33).

Alternative forms of NIHSS

• 11-item modified NIHSS (mNIHSS).
  Developed by deleting poorly reproducible or redundant items (level of consciousness, face weakness, ataxia, and dysarthria) and collapsing the sensory item from 3 into 2 responses (Lyden, Lu, Levine, Brott, & Broderick, 2001). The mNIHSS consists of ten items with excellent reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
  and one item with adequate reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
  (Meyer, Hemmen, Jackson, & Lyden, 2002). The total score for the mNIHSS is 31.
• 5-item NIHSS (sNIHSS-5) and 8-item NIHSS (sNIHSS-8).
  For pre-hospital assessment of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More severity, an 8-item and a 5-item NIHSS have undergone preliminary evaluation. The 8 items that were most predictive of “good outcome” three months after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More were: right leg, left leg, gaze, visual fields, language, level of consciousness, facial palsy, and dysarthria. The sNIHSS-8 comprises all 8 of these items and the sNIHSS-5 contains only the first 5. In the validation models, receiver operator characteristic’s (ROC) for the sNIHSS-8 and sNIHSS-5 were adequate (ROC = 0.77 and 0.76, respectively). Furthermore, no significant difference between the sNIHSS-8 and the sNIHSS-5 was observed. The sNIHSS-5 retained much of the predictive performance of the full NIHSS (Tirschwell et al., 2002).

Client suitability

Can be used with:

• Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More.

The NIHSS is designed so that virtually any strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More will register some abnormality on the scale.

Should not be used in:

• The NIHSS can be administered to virtually any patient with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, however, a potential flaw with the NIHSS is that there may be a ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More below the theoretical limit in patients with very severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More because many scale items cannot be tested in these patients (Muir, Weir, Murray, Povey, & Lees, 1996).
• Can be estimated retrospectively from the admission neurological examination (Bushnell, Johnston, & Goldstein, 2001; Kasner et al., 1999; Williams, Yilmaz, & Lopez-Yunez, 2000), although actual testing is preferable.

In what languages is the measure available?

The NIHSS has been translated into the following languages: (http://www.proqolid.org/)

• Cantonese for Hong-Kong
• Estonian
• Hindi
• Hungarian
• Italian
• Marathi
• Portuguese
• Telugu

The NIHSS has been translated and validated in the following languages:

• Chinese (Sun, Chiu, Yeh, & Chang, 2006)
• German (Berger et al., 1999)
• Spanish (Dominguez et al., 2006)

Summary

What does the tool measure?	Neurologic outcome and degree of recovery for patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More
What types of clients can the tool be used for?	Patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More.
Is this a screeningTesting for disease in people without symptoms. or assessment tool?	Assessment
Time to administer	It takes less that 10 minutes to complete the NIHSS.
Versions	11-item modified NIHSS (mNIHSS); 5-item NIHSS (sNIHSS-5); 8-item NIHSS (sNIHSS-8).
Other Languages	Translated in Cantonese for Hong-Kong; Estonian; Hindi; Hungarian; Italian; Marathi; Portuguese; Telugu. Translated and validated in Chinese; German; Spanish.
Measurement Properties
ReliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .	Internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. More: No studies have examined the internal consistencyA method of measuring reliability . Internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else. Internal consistency coefficients can take on values from 0 to 1. Higher values represent higher levels of internal consistency. More of the NIHSS. Test-retest: Only one study has examined the test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society). the original NIHSS and reported adequate to excellent test-retest. Intra-rater: Only one study has examined the intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings. of the original NIHSS and reported excellent intra-rater. Inter-rater: – Out of 11 studies examining the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the original NIHSS, six reported excellent inter-rater, one reported adequate inter-rater, three reported adequate to excellent inter-rater, and one reported poor to excellent inter-rater. – Out of three studies examining the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept. of the mNIHSS, two studies reported excellent inter-rater, and one study reported that inter-rater was improved with the mNIHSS in comparison to the original NIHSS.
ValidityThe degree to which an assessment measures what it is supposed to measure.	Construct: Modified NIHSS: The correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation. between the original NIHSS and mNIHSS was excellent. Criterion: Concurrent: Original NIHSS: Poor correlations between NIHSS and the Modified Rankin Scale and the Barthel Index; adequate to excellent correlations with infarct volumes using computed tomography and excellent correlations using MRI. Concurrent: Modified NIHSS: Excellent correlations between mNIHSS and the Modified Rankin Scale, the Barthel Index, and the Glasgow Outcome Scale were reported in a retrospective analysis, however, in a prospective analysis the mNIHSS had poor concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.” with the Barthel Index and the modified Rankin Scale. Adequate to excellent correlations have been reported with infarct volumes using computed tomography and excellent correlations using MRI. Predictive: The NIHSS was found to predict Barthel Index, Rankin Scale, and Glasgow Outcome Scale scores at 3-month outcome; administered in the first 24 hours after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More onset, the NIHSS can retrospectively predict the next level of care after acute hospitalization; NIHSS also predicted clinical outcome; recovery; the likelihood of a patient’s recovery after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More; discharge destination; 3-month mortality; presence and location of a vessel occlusion.
Floor/Ceiling Effects	A significant ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More has been detected with the NIHSS.
Does the tool detect change in patients?	One study assessed the responsivenessThe ability of an instrument to detect clinically important change over time. of the original NIHSS by comparing the scale scores on patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More to the patients’ infarction size as measured by computed tomography at 1 week. Although most patients improved clinically, 4/15 items changed only minimally.
Acceptability	The NIHSS can be administered to virtually any patient with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, however, a potential flaw with the NIHSS is that there may be a ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More below the theoretical limit in patients with very severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More because many scale items cannot be tested in these patients (Muir, Weir, Murray, Povey, & Lees, 1996). The scale cannot be completed by proxy or by self-report as it is an observational scale. However, measurement by video telemedicine appears to be reliable and could offer a method for remote assessment.
Feasibility	It is important to note that one must be both trained and certified in order to administer the NIHSS. Training and certification can be obtained online at the following website: http://www.nihstrokescale.org/ No specialized equipment is required and relatively little space is needed to administer the NIHSS.
How to obtain the tool?	This measurement tool is available in the following article: https://www.ahajournals.org/doi/10.1161/STROKEAHA.116.015434

Psychometric Properties

Overview

The NIHSS has established reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
and validityThe degree to which an assessment measures what it is supposed to measure.
for use in prospective clinical research, and predictive validityA form of criterion validity that examines a measure's ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
for long-term strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. More outcome (Adams et al., 1999; Brott et al., 1989; Lyden et al., 1994). For the purposes of this review, we conducted a literature search to identify all relevant publications on the psychometric properties of the NIHSS.

Reliability

Original NIHSS:
Brott et al. (1989) designed the NIHSS and assessed the scale’s reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
in 24 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the scale was adequate (mean kappa = 0.69). Agreement was excellent for six items: papillary response (kappa = 0.95), best motor arm performance (kappa = 0.85), best motor leg performance (kappa = 0.83), best gaze (kappa = 0.82), and level of consciousness questions (kappa = 0.80). The lowest agreement was for the qualitative assessment of level of consciousness (kappa = 0.49). Of the 15 test items, the most inter-rater reliable item was pupillary response. Less reliable items were upper or lower extremity motor function. Test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
was adequate to excellent (mean kappa = 0.66 to 0.77). The correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the first examination scores and the second examination scores (within 24 hours) was excellent (r = 0.98). Test-retest reliabilityA way of estimating the reliability of a scale in which individuals are administered the same scale on two different occasions and then the two scores are assessed for consistency. This method of evaluating reliability is appropriate only if the phenomenon that the scale measures is known to be stable over the interval between assessments. If the phenomenon being measured fluctuates substantially over time, then the test-retest paradigm may significantly underestimate reliability. In using test-retest reliability, the investigator needs to take into account the possibility of practice effects, which can artificially inflate the estimate of reliability (National Multiple Sclerosis Society).
did not differ significantly when administered by different health care professionals such that the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
of one examiner’s score for the first exam with a different examiner’s score for the second examination was excellent; for example, a first examination by the neurologistThis team member is responsible for “the diagnostic evaluation, medical treatment, prevention of stroke recurrence, patient and family education, staff and trainee education, research, program evaluation.”(Suggested by Philips et al, 2002)
of an individual patient correlated with a second examination of that patient by the emergency department nurseIn charge of, but not limited to, the “assessment and provision of care needs; support and education for patients and families; discharge planning.”(Suggested by Philips et al, 2002)
with Spearman’s correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
= 0.98. These results suggest that the NIHSS can be reliably administered to patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More.

Meyer et al. (2002) examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the NIHSS and the mNIHSS in 45 patients with a history of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Two neurologists tested each patient. Dysarthria was the only item of the NIHSS found to have poor inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(kappa = 0.289), and four items were found to have adequate reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
. Ten items were found to have excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
. Kappa scores ranged from 0.289 to 0.975. The kappa value for the total NIHSS score was excellent (kappa = 0.969). The results of this study suggest that the NIHSS has high inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
.

Similarly, Goldstein, Bertels and Davis (1989) examined the inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of the NIHSS in 20 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. A pair of clinical strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More fellows rated each patient. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
ranged from adequate to excellent for 9 out of 13 items.

Goldstein and Samsa (1997) examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of the NIHSS when administered by non-neurologists in the setting of a clinical trial. Thirty physician investigators (30% non-neurologists) and 29 non-physician study coordinators were trained to administer the NIHSS. Four patients were rated and after 3 months had elapsed, then the same four patients were re-rated, in order to provide a measure of intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
. Four new patients were also rated after 3 months and were compared to the initial 4 ratings in order to assess inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
. The intraclass correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficients (ICC’s) were excellent for the initial four cases (ICC = 0.94) and for the four new cases rated 3 months later (ICC = 0.92). The overall ICC based on the ratings of these 8 cases was excellent (ICC = 0.95), suggesting that NIHSS administration by non-neurologists has a high level of inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
for the cases rated during the initial training session and re-rated after 3 months had elapsed (ICC = 0.93), suggesting that NIHSS administration by non-neurologists also has a high level of intra-rater reliabilityThis is a type of reliability assessment in which the same assessment is completed by the same rater on two or more occasions. These different ratings are then compared, generally by means of correlation. Since the same individual is completing both assessments, the rater’s subsequent ratings are contaminated by knowledge of earlier ratings.
.

Lyden et al. (1994) trained raters to administer the NIHSS to 11 patients using a training video. The inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
of this method was then calculated. Moderate to excellent agreement was established on most NIHSS items (unweighted kappa > 0.60). Only two items, ataxia and facial paresis, showed poor agreement (unweighted kappa < 0.40). The results of this study demonstrate the strong reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of the NIHSS when raters are trained by a standardized video.

Shafqat et al. (1999) evaluated the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of administering the NIHSS remotely (by telemedicine link) by obtaining one bedside and one remote NIHSS score independently for 20 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Kappa coefficients were calculated for inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
between bedside and remote administration scores. Excellent agreement was achieved for four items (orientation, kappa = 0.75; motor arm, kappa = 0.82; motor leg, kappa = 0.83; neglect, kappa = 0.77). Six items displayed adequate agreement (language, kappa = 0.65; dysarthria, kappa = 0.55; sensation, kappa = 0.48; visual fields, kappa = 0.60; facial palsy, kappa = 0.40; gaze, kappa = 0.41). Two items achieved poor agreement (commands, kappa = 0.29; ataxia, kappa = -0.07). Total NIHSS scores obtained by bedside and remote methods of administration were highly correlated (r = 0.97). These results suggest that the NIHSS can be reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
administered by telemedicine.

Similar to the study by Shafqat et al. (1999), Meyer et al. (2005) also examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of NIHSS administration by wireless and site-independent telemedicine in 25 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Patients were evaluated by both remote and bedside examination. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
between remote and beside examiners for the NIHSS was found to be poor for two items (facial palsy, kappa = 0.22; limb ataxia, kappa = 0.34), adequate for 3 items (left leg motor, kappa = 0.74; language, kappa = 0.73; dysarthria, kappa = 0.61). Ten items showed excellent agreement (kappa’s ranged from 0.80 to 1.00). The ICC was excellent for the total NIHSS score (ICC = 0.94). Taken together with the results by Shafqat et al. (1999), the NIHSS can be reliably administered by wireless and site-independent telemedicine.

Dewey et al. (1999) examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of the NIHSS in a community-based sample of 31 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Two neurologists and one of two research nurses assessed the patients. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
, as there was a high level of agreement for total scores between the two neurologists (ICC = 0.95) and between each neurologistThis team member is responsible for “the diagnostic evaluation, medical treatment, prevention of stroke recurrence, patient and family education, staff and trainee education, research, program evaluation.”(Suggested by Philips et al, 2002)
and research nurseIn charge of, but not limited to, the “assessment and provision of care needs; support and education for patients and families; discharge planning.”(Suggested by Philips et al, 2002)
(ICC = 0.92 and 0.96). While there was adequate to excellent agreement among neurologists and research nurseIn charge of, but not limited to, the “assessment and provision of care needs; support and education for patients and families; discharge planning.”(Suggested by Philips et al, 2002)
(weighted kappa > 0.4) for the majority of the NIHSS items, there was poor agreement for the item ‘limb ataxia’ item. The results of this study suggest that the NIHSS can be reliably administered to a community-based sample.

Schmülling et al. (1998) examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of the NIHSS when administered by untrained raters in 22 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. All diagnoses were confirmed by computed tomography. Four neurologists assessed the patients. Two raters were video trained and experienced in administering the NIHSS, and the other two were inexperienced and were given no training in administering the NIHSS. Excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(kappa = 0.61) was achieved among the trained raters, however only adequate inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(kappa = 0.33) was achieved among the untrained raters. Between trained and untrained raters, the unweighted kappa was adequate (kappa = 0.45). The reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of individual items also differed between trained and untrained raters. Among trained raters, only two items had adequate agreement (ataxia, kappa = 0.34; neglect, kappa = 0.32), and the rest were excellent. Among the untrained raters, 6 items had adequately reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
, and 4 items had poor reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of “true” variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to “noise” in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
(ataxia, kappa = -0.03; gaze, kappa = 0.06; visual fields, kappa = -0.02; dysarthria, kappa = 0.18). The results of this study suggest that the NIHSS has excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
only when raters are trained and knowledgeable on how to correctly administer the NIHSS.

Kasner et al. (1999) examined whether NIHSS scores could be retrospectively estimated from medical records. NIHSS scores of 39 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More were estimated from notes from medical records by 6 raters. These scores were compared to their actual NIHSS scores to which the raters had been blinded. Overall inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(ICC = 0.82). Agreement between pairs of raters ranged from good to excellent (ICC’s ranged from 0.70 to 0.89). Over 90% of the estimated NIHSS scores were within 5 points at both admission and discharge for all pairs of raters. The results of this study suggest that the NIHSS can be reliably abstracted from medical records for retrospective studies on acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More outcome.

Williams et al. (2000) developed an algorithm for retrospective NIHSS scoring from chart documentation. One investigator prospectively scored the admission NIHSS in 32 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Two raters retrospectively scored the NIHSS by applying the algorithm to photocopied admission notes. Linear regression was used to assess inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
and agreement between prospective and retrospective NIHSS scores. Weighted kappa statistics were calculated to assess the level of agreement of individual NIHSS items. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
was excellent, (r = 0.98) as was agreement between prospective and retrospective NIHSS scores (r = 0.94). Agreement for individual items ranged from adequate (response to commands, kappa = 0.54; visual, kappa = 0.64; ataxia, kappa = 0.66; sensory, kappa = 0.60; dysarthria, kappa = 0.69, extinction/inattention, kappa = 0.57) to excellent (response to questions, kappa = 0.87; best gaze, kappa = 0.94; facial palsy, kappa = 0.76; left arm, kappa = 0.85; left leg, kappa = 0.87; right arm, kappa = 0.79; right leg, kappa = 0.75; best language, kappa = 0.80). Only one item, level of consciousness, had poor agreement (kappa = -0.10). The results of this study suggest that retrospective NIHSS scoring with the developed algorithm is reliable and unbiased even if information is missing from chart documentation.

Bushnell et al. (2001) looked at the retrospective scoring of both the Canadian Neurological Scale and the NIHSS. They compared data from academic medical centers to community hospitals with neurologists and community hospitals without neurologists. More data was missing for the NIHSS in comparison to the amount of data missing for the Canadian Neurological Scale. Almost perfect levels of inter-rater agreement was found for NIHSS scores retrospectively at the academic medical centers (ICC = 0.93) and at community hospitals with neurologists (ICC = 0.89), however, only adequate agreement was found at community hospitals without neurologists (ICC = 0.48). These results suggest that scoring the NIHSS retrospectively may not be reliable unless the medical record contains evaluation material from a neurologistThis team member is responsible for “the diagnostic evaluation, medical treatment, prevention of stroke recurrence, patient and family education, staff and trainee education, research, program evaluation.”(Suggested by Philips et al, 2002)
.

Modified NIHSS:
Lyden et al. (2001) developed the mNIHSS and assessed the scale’s reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
using the certification data originally collected to assess the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of investigators in the National Institute of Neurological Disorders and StrokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. More rtPA (recombinant tissue plasminogen activator) Trial. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
was improved with the mNIHSS in comparison to the original NIHSS. The number of scale items with poor kappa coefficients decreased from 8 (20%) to 3 (14%): loss of consciousness commands, gaze, and language. The mNIHSS remains to be tested prospectively, as the original NIHSS may be more appropriate for clinical monitoring"The process of checking the task over time for ‘quality control’ and the adjustment of behavior" (Stuss, 2009, p. 9-10)
of patients.

Meyer et al. (2002) also examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of the mNIHSS in 45 patients with a history of strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. More. Two neurologists tested each patient. Ten out of eleven mNIHSS kappa scores showed excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(ranging from kappa = 0.841 to kappa = 0.975). Only gaze had a adequate kappa score of 0.661. The total mNIHSS kappa was excellent (kappa = 0.988). In this study, the mNIHSS was found to be more reliable than the original NIHSS.

Meyer et al. (2005) examined the reliabilityReliability can be defined in a variety of ways. It is generally understood to be the extent to which a measure is stable or consistent and produces similar results when administered repeatedly. A more technical definition of reliability is that it is the proportion of "true" variation in scores derived from a particular measure. The total variation in any given score may be thought of as consisting of true variation (the variation of interest) and error variation (which includes random error as well as systematic error). True variation is that variation which actually reflects differences in the construct under study, e.g., the actual severity of neurological impairment. Random error refers to "noise" in the scores due to chance factors, e.g., a loud noise distracts a patient thus affecting his performance, which, in turn, affects the score. Systematic error refers to bias that influences scores in a specific direction in a fairly consistent way, e.g., one neurologist in a group tends to rate all patients as being more disabled than do other neurologists in the group. There are many variations on the measurement of reliability including alternate-forms, internal consistency , inter-rater agreement , intra-rater agreement , and test-retest .
of mNIHSS administration by wireless and site-independent telemedicine in 25 patients with strokeAlso called a "brain attack" and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a "schemic stroke", or the formation of a blood clot in a vessel supplying blood to the brain. More. Patients were evaluated by both remote and bedside examination. Inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
between remote and beside examiners for the mNIHSS was found to be adequate for two items (left leg motor, kappa = 0.74; language, kappa = 0.69). Nine items showed excellent inter-rater reliabilityA method of measuring reliability . Inter-rater reliability determines the extent to which two or more raters obtain the same result when using the same instrument to measure a concept.
(kappas ranged from 0.80 to 1.00). The ICC was excellent for the total mNIHSS score (ICC = 0.95). The results of this study suggest that the mNIHSS can be reliably administered by wireless and site-independent telemedicine.

Validity

Construct:
Original NIHSS:
N/A

Modified NIHSS:
Meyer et al. (2002) tested the construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the NIHSS and mNIHSS in 45 patients with a history of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Two neurologists tested each patient. The Spearman correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
coefficient between NIHSS and mNIHSS (for both examiners) was excellent (r = 0.947 and r = 0.941), with an overall average correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
of r = 0.944. Construct validityReflects the ability of an instrument to measure an abstract concept, or construct. For some attributes, no gold standard exists. In the absence of a gold standard , construct validation occurs, where theories about the attribute of interest are formed, and then the extent to which the measure under investigation provides results that are consistent with these theories are assessed.
of the mNIHSS was demonstrated in this study as the scale was found to perform similarly to the NIHSS.

Criterion:
Concurrent:
Original NIHSS:
Meyer et al. (2002) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the NIHSS and mNIHSS by comparing the scales with the Barthel Index and the Modified Rankin Scale. The coefficients for the examiners combined for NIHSS versus Barthel Index and Modified Rankin Scale were -0.165 (the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
is negative because a high score on the NIHSS indicates severe neurological impairment, whereas a high score on the BI indicates functional independence) and 0.219 respectively. The authors suggest that the poor relationships observed may be due to the fact that patients in this study had only mild deficits, rendering it difficult to determine concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
, especially at the higher end of the scale.

Brott et al. (1989) assessed the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the NIHSS by comparing the scale scores obtained prospectively on 65 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More to the patients’ infarction size as measured by computed tomography at 1 week. The Spearman’s correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the total NIHSS score at 7 days and the computed tomography scan lesion volume at 7 days was excellent (r = 0.74). The patients’ initial neurologic deficit as measured by the scale also correlated with the 7-10 day computed tomography lesion volume (r = 0.78). The scale-computed tomography correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
at 7 days for patients with left hemisphere infarctions was 0.72, while this correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
for patients with right hemisphere infarctions was 0.74. The results of this study demonstrate that the NIHSS has excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
with infarct volumes using computed tomography.

Schiemanck, Post, Witkamp, Kappelle and Prevo (2005) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of infarct volumes in 94 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More as assessed by magnetic resonance imaging (MRI) with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More severity as measured by the NIHSS at 2 weeks post-stroke. A strong correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between lesion volume and NIHSS score was found (r = 0.61), suggesting that the NIHSS has excellent concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
with infarct volumes using MRI.

However, Saver et al. (1999) also investigated the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of infarct volumes with 3-month NIHSS scores in 191 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. In this study, computed tomography scans at days 6 to 11 were only adequately correlated with 3-month NIHSS scores (r=0.54).

Similarly, Lyden, Claesson, Havstad, Ashwood, and Lu (2004) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of baseline NIHSS scores with 30-day infarct volumes using computed tomography in patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More seen within 12 hours of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More onset. Baseline NIHSS scores and lesion volumes were also found to be only adequately correlated (r = 0.37).

Derex et al. (2004) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the NIHSS with lesion volumes in 49 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Patients underwent MRI prior to thrombolysis and were then administered the NIHSS at day one. Baseline NIHSS scores were highly correlated with baseline diffusion-weighted imaging lesion volumes (r = 0.71), and correlated adequately with perfusion-weighted imaging abnormality volumes (r = 0.58) and time to peak delays (r = 0.41). The NIHSS score also correlated with the site of arterial occlusion.

Fink et al. (2002) examined the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the NIHSS with lesion volumes measured by diffusion weighted imaging within 24 hours of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More in 153 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. The NIHSS was adequately correlated with acute diffusion weighted imaging lesion volumes (r = 0.48, right; r = 0.58, left) and with acute NIHSS scores and perfusion-weight imaging hypoperfusion volumes (r = 0.62, right; r = 0.60, left). However, a difference was observed in left- versus right-sided strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Among patients with diffusion weighted imaging lesions larger than the median volume, 8/37 with right-sided strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More had an NIHSS score of 0 – 5 compared with 1/39 patients with left-sided strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. However, multiple linear regression analysis revealed a significantly lower acute NIHSS on the right compared with the left side when adjusted for strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More volume, suggesting that patients with a right-sided strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More may have a low NIHSS score despite substantial lesion volume.

Woo et al. (1999) concurred with the findings of Fink et al. (2002). By using the placebo arm of the National Institute of Neurological Disorders and StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More rtPA (recombinant tissue plasminogen activator) Trial to examine whether total volume of cerebral infarction in patients with right hemisphere strokes would be greater than the volume of cerebral infarction in patients with left hemisphere strokes who have similar NIHSS scores. The results of this study suggested that the volume for right hemisphere strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More was statistically greater than the volume for left hemisphere strokes, when the baseline NIHSS score was adjusted. For each 5-point category of the NIHSS score (eg. from 16-20), the median volume of right hemisphere strokes was approximately double the median volume of left hemisphere strokes. The Spearman rank correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between the 24-hour NIHSS score and 3-month lesion volume was 0.72 for patients with left hemisphere strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More and 0.71 for patients with right hemisphere strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. The results of this study show that for a given NIHSS score, the median volume of right hemisphere strokes is consistently larger than the median volume of left hemisphere strokes. Therefore, care must be taken when infarction size is being predicted from NIHSS score.

Modified NIHSS:
In a retrospective analysis, Lyden et al. (2001) measured the concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
of the mNIHSS by comparing the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
of mNIHSS with the other neurological scales (the Barthel Index, the Modified Rankin Scale, and the Glasgow Outcome Scale) measured at 3 months. The mNIHSS showed an excellent correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
with these scales at all time points, with correlations being strongest at 90 days (r = -0.82 for Barthel Index; r = 0.83 for modified Rankin Scale; r = 0.82 for Glasgow Outcome Scale). CorrelationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
with the Barthel Index is negative because a high score on the Barthel Index indicates functional independence whereas a high score on the mNIHSS indicates neurological deficit.

In a prospective analysis, Meyer et al. (2002) found that the mNIHSS demonstrated poor concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
with the Barthel Index and the Modified Rankin Scale. The coefficients for mNIHSS versus Barthel Index and modified Rankin Scale were -0.238 (the correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
is negative because a high score on the NIHSS indicates severe neurological impairment, whereas a high score on the Barthel Index indicates functional independence) and 0.296, respectively. The absolute Spearman correlations were higher with the use of the mNIHSS in comparison to the original NIHSS, however, values were not statistically significant. The weak relationships observed with the mNIHSS and the other scales may be due to the fact that patients in this study had only mild deficits, rendering it difficult to determine concurrent validityTo validate a new measure, the results of the measure are compared to the results of the gold standard obtained at approximately the same point in time (concurrently), so they both reflect the same construct. This approach is useful in situations when a new or untested tool is potentially more efficient, easier to administer, more practical, or safer than another more established method and is being proposed as an alternative instrument. See also “gold standard.”
, especially at the higher end of the scale.

Predictive:
Original NIHSS:
Lyden et al. (1999) used data from the National Institute of Neurological Disorders and StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More (NINDS) tPA StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Trial to determine whether the NIHSS was valid in patients treated with tissue plasminogen activator. To assess the predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the NIHSS, the scale was compared over time with the 3-month outcome of the Barthel Index, the Rankin Scale, and the Glasgow Outcome Scale. The correlations between the NIHSS and the other clinical outcomes were significant but adequate at baseline (Placebo group: Barthel Index, r = -0.48; Rankin Scale, r = 0.51; Glasgow Outcomes Scale, r = 0.49; Treatment group: Barthel Index, r = -0.51, Rankin Scale, r = 0.56; Glasgow Outcomes Scale, r = 0.56) and at 2 hours (Placebo group: Barthel Index, r = -0.58; Rankin Scale, r = 0.61; Glasgow Outcomes Scale, r = 0.60; Treatment group: Barthel Index, r = -0.65; Rankin Scale, r = 0.70; Glasgow Outcomes Scale, r = 0.68) after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. The correlations were greater for the measurements later in time (24 hours, 7-10 days, 90 days post-stroke), which suggests that after 2 hours from strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, the NIHSS may have greater predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
in terms of the 3-month outcome.

Schlegel et al. (2003) tested whether the NIHSS in the first 24 hours after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More onset could predict the next level of care after acute hospitalization in a retrospective study of 94 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. From medical records it was determined that 59% of patients were discharged home, 30% to rehabilitation, and 11% to a long-term nursing facility. For each 1-point increase in NIHSS score, the likelihood of going home was significantly reduced (OR = 0.79). The category of NIHSS score also predicted the next level of care. An NIHSS score 5 was strongly associated with discharge home. When compared with patients with an NIHSS ≤ 5, patients with a score from 6 to 13 were nearly 5 times more likely to be discharged to rehabilitation (OR = 4.8). Patients who scored >13 were nearly 10 times more likely to require rehabilitation (OR = 9.5) and more than 100-fold more likely to be placed in a long-term nursing facility (OR = 310). The results of this study suggest that the NIHSS, administered in the first 24 hours after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More onset, can retrospectively predict the next level of care after acute hospitalization.

Schlegel et al. (2004) examined whether the NIHSS could predict the next level of care in 46 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More treated with thrombolysis (recombinant tissue plasminogen activator). In a multinomial regression analysis, increasing NIHSS score was a strong independent predictor of discharge to rehabilitation or nursing facilities, roughly doubling for each 5-point increment (score 6 – 10: rehabilitation OR = 1.78, nursing facility OR = 2.31; score 11 – 15: rehabilitation OR = 2.66, nursing facility OR = 5.05; score 16 – 20: rehabilitation OR = 5.31, nursing facility OR = 16.30; score > 20 rehabilitation OR = 8.36, nursing facility OR = 27.40). The results of this study suggest that strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More severity as determined by the admission NIHSS score is a major independent predictor of the next level of care following hospitalization and treatment with thrombolysis for acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More.

Demchuk et al. (2001) examined factors that were independently predictive of good outcome among 1,205 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More who were treated with alteplase (a type of thrombolytic therapy). Using multivariable logistic regression modeling, the most important predictor of outcome identified was found to be baseline strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More severity as measured by the NIHSS score. The higher the NIHSS score, the worse the odds were of having a good outcome (OR good outcome = 1.00 for NIHSS score ≤ 5; OR good outcome = 0.05 for NIHSS > 20).

Muir et al. (1996) compared the NIHSS, the Canadian Neurological Scale, and the Middle Cerebral Artery Neurological Score to see which scale best predicted good (alive at home) or poor (alive in care or dead) outcome in 408 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Predictive accuracy of the variables was compared by ROC curves and stepwise logistic regression. Logistic regression showed that the NIHSS added significantly to the predictive value of all other scores. The NIHSS overall accuracy was excellent (0.83). A cutoff point of 13 on the NIHSS best predicted 3-month outcome.

Adams et al. (1999) found that the NIHSS strongly predicts the likelihood of a patient’s recovery after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More in a post-hoc analysis by strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More subtype of 1,268 patients enrolled in an acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More trial. NIHSS scores were taken at baseline, 7 days, and 3 months after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. A score of ≥ 16 forecasted a high probability of death or severe disability whereas a score of ≤ 6 forecasted a good recovery. The baseline NIHSS score strongly predicted outcome at 7 days and at 3 months. By 7 days, 2/3 of the patients scoring ≤ 3 at baseline had an excellent outcome. One additional point on the NIHSS decreased the likelihood of excellent outcomes at 7 days by 24% and at 3 months by 17%. Patients with lacunar infarcts had significantly higher likelihood of an excellent outcome at 7 days and 3 months than did patients with non-lacunar strokes, but odds were poorer compared with patients with other types of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More when scores were 10 or more. At 3 months, excellent outcomes were noted in 46% of patients with NIHSS scores of 7 – 10 and in 23% of patients with scores of 11 – 15. Very few patients with baseline scores of > 15 had excellent outcomes after 3 months.

Albers, Bates, Clark, Bell, Verro, and Hamilton (2000) examined patients administered intravenous tissue-type plasminogen activator for treatment of acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More in 389 patients. A multivariate analysis found a less severe baseline NIHSS score (≤ 10) was a predictor of favorable outcome. For every 5-point increase in baseline NIHSS score, patients had a 22% decrease in the odds of recovery (OR = 0.78), and patients with baseline NIHSS scores greater than 10 had a 75% decrease in the odds of recovery (OR = 0.25).

DeGraba et al. (1999) administered the NIHSS serially to 127 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More for the first 48 hours of admission to the neuroscience intensive care unit and found that a 3-point or greater increase on the NIHSS indicated strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More progression. A significant cutoff that allowed for the greatest likelihood of predicting patient progression occurred when NIHSS scores were stratified as ≤ 7 and > 7. Patients with an initial NIHSS score of ≤ 7 experienced a 14.8% worsening rate and were more likely to be functionally normal (45% were functionally normal at 48 hours). Patients with an initial NIHSS score of > 7 had a 65.9% worsening rate and were less likely to be functionally normal at 48 hours (only 2.4% were functionally normal). These results demonstrate the predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the NIHSS.

Frankel et al. (2000) examined whether a practical method for predicting a poor outcome after acute ischemic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More could be developed. Using data from the placebo arm of Part 1 and 2 of the National Institute of Neurological Disorders and StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More rt-PA (recombinant tissue plasminogen activator) StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Trial, patients with an NIHSS score > 17 with atrial fibrillation, yielded a positive predictive value of 96%. At 24 hours, the best predictor was an NIHSS score > 22, yielding a positive predictive value of 98%. At 7 – 10 days, the best predictor was an NIHSS score > 16, yielding a positive predictive value of 92%. The results of this study suggest that patients with a severe neurologic deficit after acute ischemic strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, as measured by the NIHSS, have a poor prognosis and that during the first week after acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, it is possible to identify a subset of patients who are highly likely to have a poor outcome.

Rundek et al. (2000) examined predictors of discharge destinations following acute care hospitalization in 893 patients who survived acute care hospitalization for a first strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, followed prospectively. Polytomous logistic regression was used to determine predictors for rehabilitation and nursing home placement versus returning home. Among the survivors of acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More care hospitalization, 611 patients were discharged to their homes, 168 to rehabilitation, and 114 to nursing homes. Patients with adequate neurological deficits (NIHSS score from 6 – 13; rehabilitation OR = 8.0, nursing home OR = 3.8) and severe neurological deficits (NIHSS score ≥ 14; rehabilitation OR = 17.9, nursing home OR = 27.9) had more than a threefold increased risk of being sent to a nursing home and more than an eightfold increased risk of being sent to rehabilitation, demonstrating the clinical predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the NIHSS.

Bohannon, Lee, and Maljanian (2002) examined what variables predicted three hospital outcomes (hospital length of stay, hospital charges, and hospital discharge destination). NIHSS scores and Barthel Index scores correlated with all three outcomes. The correlations between NIHSS scores and hospital length of stay and hospital charges (ranging from r = 0.276 to r = 0.381) were positive, indicating that patients with more severe strokes had a longer hospital length of stay and higher hospital charges. The correlations between NIHSS scores and discharge destination were negative (r = -0.344 and r = -0.355), meaning that patients with more severe strokes were less likely to be discharged home. Regression analysis showed that once post-admission Barthel Index scores were accounted for, no other variable added to the prediction of hospital length of stay or discharge destination, however the NIHSS score added to the explanation of hospital charges provided by post-admission Barthel Index scores.

Derex et al. (2003) examined whether pre-treatment MRI parameters predicted clinical outcome in 49 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More treated by intravenous recombinant tissue plasminogen activator. Univariate and multivariate logistic regression analyses were used to identify the predictors of clinical outcome. The results of these analyses suggested that baseline NIHSS score was the best independent predictor of clinical outcome at day 60 (OR = 1.28).

Baird et al (2001) used logistic regression to develop a 3-item scale for predicting good strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More recovery, which was tested in 63 patients. By combining the NIHSS with the time from onset and lesion volume (as detected by diffusion weighted imaging) a score could be obtained to accurately predict strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More recovery. Scores of 0 to 2 indicate low probability of recovery, 3 to 4 medium, and 5 to 7 high. This score can help early decision-making regarding aggressiveness of care, discharge planningPlanning ability involves anticipating future events, formulating a goal or endpoint, and devising a sequence of steps or actions that will achieve the goal or endpoint” (Anderson, 2008, p. 17)
, and rehabilitation options.

Briggs, Felberg, Malkoff, Bratina, and Grotta (2001) examined the NIHSS scores of 138 patients admitted within 24 hours of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More to help determine if patients with mild strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More fared better by admission to a general ward or to the intensive care unit. They found a general positive correlationThe extent to which two or more variables are associated with one another. A correlation can be positive (as one variable increases, the other also increases – for example height and weight typically represent a positive correlation) or negative (as one variable increases, the other decreases – for example as the cost of gasoline goes higher, the number of miles driven decreases. There are a wide variety of methods for measuring correlation including: intraclass correlation coefficients (ICC), the Pearson product-moment correlation coefficient, and the Spearman rank-order correlation.
between baseline NIHSS score and discharge Rankin score in adequate patients regardless of whether they were admitted to the intensive care unit or the ward (R2 = 0.273 and 0.09, respectively). Patients with mild strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More (NIHSS score < 8) admitted to a general ward had fewer complications and more favorable discharge Rankin Scale scores than similar patients admitted to the intensive care unit. There was no obvious cutoff baseline NIHSS score that was predictive of better outcome (lower Rankin) in intensive care unit patients. There was no statistical difference in length of stay. Routinely admitting patients with NIHSS scores < 8 to intensive care appears to have no cost or outcomes benefit.

Di Legge, Saposnik, Nilanont, and Hachinski (2006) identified a subset of variables that were independently associated with major neurological improvement at 24 hours and good outcome at 3 months after treatment for 219 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More who received intravenous recombinant tissue plasminogen activator in the emergency department. Using logistic regression, the results of this study suggested that among other predictors, pre-treatment NIHSS score was an excellent negative predictor of good outcome at 3 months (OR = 0.83).

Chang, Tseng, Tan, and Liou (2006) examined factors related to 3-month mortality at admission in 360 patients with first-ever acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More. Multivariate logistic regression analysis was used to identify the main predictors of 3-month stroke-related mortality. Admission NIHSS score (OR = 1.17), history of cardiac disease (OR = 2.73), and posterior circulation strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More (OR = 5.25) were significant risk factors for 3-month mortality.

Fischer et al. (2005) examined the admission NIHSS scores of 226 patients with strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More who underwent arteriography. Patients with NIHSS scores ≥ 10 had positive predictive values to show arterial occlusions in 97% of carotid and 96% of vertebrobasilar strokes. With an NIHSS score ≥ 12, the positive predictive value to find a central occlusion was 91%. In a multivariate analysis, NIHSS subitems such as level of consciousness questions (OR = 4.0), gaze (OR = 2.9), motor leg (OR = 4.2), and neglect (OR = 3.2) were predictors of central occlusions. There was a significant association between NIHSS scores and the presence and location of a vessel occlusion. With an NIHSS score ≥ 10, a vessel occlusion would likely be seen on arteriography, and with a score ≥ 12, its location would probably be central.

Modified NIHSS:
Lyden et al. (2001) examined the predictive validityA form of criterion validity that examines a measure’s ability to predict some subsequent event. Example: can the Berg Balance Scale predict falls over the following 6 weeks? The criterion standard in this example would be whether the patient fell over the next 6 weeks.
of the mNIHSS using the outcome results of the National Institute of Neurological Disorders and StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More recombinant tissue plasminogen activator StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More Trial. Using the mNIHSS to test for treatment effect on improvement at 24 hours and treatment effect on minimal or no disability at 3 months after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, the scale scores differentiated the two treatment groups at 24 hours and at 3 months. The proportion of patients who improved ≥ 4 points within 24 hours after treatment was significantly increased by recombinant tissue plasminogen activator (OR = 1.3). Likewise, the odds ratio for complete/nearly complete resolution of strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More symptoms 3 months after treatment was significant (OR = 1.7) with the mNIHSS.

Content :
Original NIHSS:
Lyden et al. (1999) used data from the National Institute of Neurological Disorders and StrokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More recombinant tissue plasminogen activator Trial to determine whether the NIHSS was valid in patients treated with tissue plasminogen activator. To assess the content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
of the scale, an exploratory factor analysis of NIHSS data was performed within the first 24 hours after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, to derive an underlying factor structure. The results from this analysis suggested that there were two factors, representing left and right brain function, underlying the NIHSS. The internal scale structure remained consistent in placebo and treated groups and when administered successively over time, confirming the content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
of the scale.

Modified NIHSS:
Lyden et al. (2001) developed and assessed the validityThe degree to which an assessment measures what it is supposed to measure.
of the mNIHSS. Content validityRefers to the extent to which a measure represents all aspects of a given social concept. Example: A depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension.
was determined using factor analysis, and the goodness of fit was recalculated on the basis of a 4-factor solution restricted to the 11 NIHSS items involved in the mNIHSS. To prevent the confounding effects of time or treatment, the goodness of fit was calculated for data collected at 2 hours, 24 hours, 7 to 10 days, and 3 months after recombinant tissue plasminogen activator or placebo treatment. The results suggested that the internal structure of the mNIHSS was identical to that of the NIHSS. The goodness of fit (comparative fit index = 0.96) was equal to that of the NIHSS. When used over time, and in placebo-treated versus active-treated groups, the mNIHSS values ranged from 0.93 to 0.96 and were as strong as those of the NIHSS.

Responsiveness

Original NIHSS:
Brott et al. (1989) assessed the responsivenessThe ability of an instrument to detect clinically important change over time.
of the NIHSS by comparing the scale scores obtained prospectively on 65 patients with acute strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More to the patients’ infarction size as measured by computed tomography at 1 week. Although most patients improved clinically, 4/15 items changed only minimally: facial palsy (-2% improvement for item score at 1 week), plantar reflex (7% improvement for item score at 1 week), dysarthria (-1% improvement for item score at 1 week), and language (6% improvement for item score at 1 week). Also, change in limb ataxia (59% improvement) and best gaze (52% improvement) may have been overstated, based on infarction size observed. The other 10 items changed an average of 25% over 7 days. Raters in this study also had to conclude whether patients changed neurologically from the previous examination and from baseline. This was defined as “Same” (a change of 0-1 scale point), “Better” (an improvement of ≥ 2 scale points), and “Worse” (a deterioration of ≥ 2 scale points). Based on these definitions, from baseline to 7-10 days, agreement was achieved for 40/63 patients surviving at 7-10 days (63%) (compared quantitative criteria for patient change with the investigator’s judgment of patient change). The results of this study demonstrate that the NIHSS is responsive to change.

Modified NIHSS:
Lyden at al. (2001) examined the responsivenessThe ability of an instrument to detect clinically important change over time.
of the mNIHSS in a retrospective analysis. The mNIHSS imitated the original NIHSS in the predictive models, which can be taken as an indicator of responsivenessThe ability of an instrument to detect clinically important change over time.
. That is, the mNIHSS tends to predict response of patients to recombinant tissue plasminogen activator as well as the original scale, when used in the multivariable model. Likewise, the mNIHSS predicts likelihood of hemorrhage after recombinant tissue plasminogen activator treatment as well as the original in the multivariable model of symptomatic hemorrhage. Further, the power to detect a 4-point or greater improvement by 24 hours was increased from 24% with the NIHSS to 51% with the mNIHSS. Within-patient responsivenessThe ability of an instrument to detect clinically important change over time.
could not be assessed in this study.

Floor and Ceiling Effects

Muir et al. (1996) suggested that a potential shortcoming of the NIHSS is that because many scale items cannot be tested in patients with very severe strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, there may be a ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More below the theoretical limit.

Williams, Weinberger, Harris, Clark, and Biller (1999) administered the NIHSS to patients 1 and 3 months post-stroke. A ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More of the NIHSS was observed in the upper extremity domain: although 62% of patients reported upper extremity dysfunction 1 month after strokeAlso called a “brain attack” and happens when brain cells die because of inadequate blood flow. 20% of cases are a hemorrhage in the brain caused by a rupture or leakage from a blood vessel. 80% of cases are also know as a “schemic stroke”, or the formation of a blood clot in a vessel supplying blood to the brain. More, only 11% had an NIHSS arm score > 1.

Pickard, Johnson, and Feeny (2005) compared five health-related quality of life measures administered at baseline and at 6 months. A notable ceiling effectA ceiling effect occurs when test items aren’t challenging enough for a group of individuals. Thus, the test score will not increase for a subsample of people who may have clinically improved because they have already reached the highest score that can be achieved on that test. In other words, because the test has a limited number of difficult items, the most highly functioning individuals will score at the highest possible score. This becomes a measurement problem when you are trying to identify changes – the person may continue to improve but the test does not capture that improvement. Example: A memory test that assesses how many words a participant can recall has a total of five words that each participant is asked to remember. Because most individuals can remember all five words, this measure has a ceiling effect. See also “floor effect.” More was observed with the NIHSS at 6 months (20% of patients).

References

• Adams, H. P., Davis, P. H., Leira, E. C., Chang, K-C., Bendixen, B. H., Clarke, W. R., Woolson, R. F., Hansen, M. D. (1999). Baseline NIH Stroke Scale score strongly predicts outcome after stroke: a report of the Trial of Org 10172 in Acute Stroke Treatment (TOAST). Neurology, 53, 126 -31.
• Albanese, M. A., Clarke, W. R., Adams, H. P., Woolson, R. F., and TOAST Investigators. (1994). Ensuring reliability of outcome measures in multicenter clinical trials of treatments for acute ischemic stroke. Stroke, 25, 1746 -1751.
• Albers GW, Bates, V. E., Clark, W. M., Bell, R., Verro, P., Hamilton, S. A. (2000). Intravenous tissue-type plasminogen activator for treatment of acute stroke: the Standard Treatment with Alteplase to Reverse Stroke (STARS) study. JAMA, 283, 1145 -1150.
• Baird, A. E., Dambrosia, J., Janket, S., Eichbaum, Q., Chaves, C., Silver, B., Barber, P., Parsons, M., Darby, D., Davis, S. (2001). A three-item scale for the early prediction of stroke recovery. Lancet, 357, 2095 -2099. 
• Berger, K., Weltermann, B., Kolominsky-Rabas, P., Meves, S., Heuschmann, P., Bohner, J., Neundorfer, B., Hense, H. W., Buttner, T. (1999). The reliability of stroke scales. The German version of NIHSS, ESS and Rankin scales [German]. Fortschr Neurol Psychiatr, 67(2), 81-93.
• Bohannon, R. W., Lee, N., Maljanian, R. (2002). Postadmission function best predicts acute hospital outcomes after stroke. Am J Phys Med Rehabil, 81, 726 -730.
• Briggs, D. E., Felberg, R. A., Malkoff, M. D., Bratina, P., Grotta, J. C. (2001). Should mild or adequate stroke patients be admitted to an intensive care unit? Stroke, 32, 871-876.
• Brott, T. G., Haley, Jr., E. C., Levy, D. E., Barsan, W., Broderick, J., Sheppard, G. L., Spilker, J., Dongable, G. L., Massey, S., Reed, R. (1992). Urgent therapy for stroke I: Pilot study of tissue plasminogen activator administered within 90 minutes.
  Stroke, 23, 632-640.
• Brott, T. G., Adams, H. P., Olinger, C. P., Marler, J. R., Barsan, W. G., Biller, J., Spilker, J., Holleran, R., Eberle, R., Hertzberg, V., Rorick, M., Moomaw, C. J., Walker, M. (1989). Measurements of acute cerebral infarction: a clinical examination scale. Stroke, 20, 864 -70.
• Bushnell, C. D., Johnston, D. C. C., Goldstein, L. B. (2001). Retrospective assessment of initial stroke severity: comparison of the NIH Stroke Scale and the Canadian Neurological Scale. Stroke, 32, 656 -60.
• Chang, K-C., Tseng, M-C., Tan, T-Y., Liou, C-W. (2006). Predicting 3-month mortality among patients hospitalized for first-ever acute ischemic stroke. Journal of the Formosan Medical Association, 105(4), 310-7.
• DeGraba, T. J., Hallenbeck, J. M., Pettigrew, K. D., Dutha, A. J., Kelly, B. J. (1999). Progression in acute stroke. Value of initial NIH Stroke Scale on patient stratification in future trials. Stroke, 30: 1208 -1212.
• Demchuk, A. M., Tanne, D., Hill, M. D., Kasner, S. E., Hanson, S., Grond, M., Levine, S. R., The Multicentre tPA Stroke Survey Group. (2001). Predictors of good outcome after intravenous tPA for acute ischemic stroke. Neurology, 57, 474 – 480.
• Dewey, H. M., Donnan, G. A., Freeman, E. J., Sharples, C. M., Macdonell, R. A. L., McNeil, J. J., Thrift, A. G. (1999). Interrater Reliability of the National Institutes of Health Stroke Scale: Rating by Neurologists and Nurses in a Community-Based Stroke Incidence Study. Cerebrovascular Diseases, 9, 323-327.
• Dominguez, R., Vila, J. F., Augustovski, F., Irazola, V., Castillo, P. R., Escalante, R. R., Brott, T. G., Meschia, J. F. (2006). Spanish cross-cultural adaptation and validation of the National Institutes of Health Stroke Scale.
• Derex, L., Nighoghossian, N., Hermier, M., Adeleine, P., Berthezene, Y., Philippeau, F., Honnorat, J., Froment, J. C., Trouillas, P. (2004). Influence of pretreatment MRI parameters on clinical outcome, recanalization and infarct size in 49 stroke
  patients treated by intravenous tissue plasminogen activator. J Neurol Sci, 225, 3 -9.
• Fink, J. N., Selim, M. H., Kumar, S., Silver, B., Linfante, I., Caplan, L. R., Schlaug, G. (2002). Is the association of National Institutes of Health Stroke Scale scores and acute magnetic resonance imaging stroke volume equal for patients with right- and left-hemisphere ischemic stroke? Stroke, 33, 954 -958.
• Fischer, U., Arnold, M., Nedeltchev, K., Brekenfeld, C., Ballinari, P., Remonda, L., Schroth, G., Mattle, H. (2005). NIHSS score and arteriographic findings in acute ischemic stroke Stroke, 36, 2121-2125.
• Goldstein, L., Bertels, C., Davis, J. (1989). Interrater reliability of the NIH Stroke Scale. Arch. Neurol, 46, 660-662.
• Goldstein, L. B., Samsa, G. P. (1997). Reliability of the National Institutes of Health stroke scale: Extension to non-neurologists in the context of a clinical trial. Stroke, 28, 307 -310.
• Haley, E. C., Levy, D. E., Brott, T. G., Sheppard, G. L., Wong, M. C., Kongable, G. L., Torner, J. C. Marler, J. R. (1992). Urgent therapy for stroke. II: Pilot study of tissue plasminogen activator administered 91-180 minutes from onset. Stroke, 23,
  641-645.
• Kasner, S. E., Chalela, J. A., Luciano, J. M., Cucchiara, B. L., Raps, E. C., McGarvey, M. L., Conroy, M. B., Localio, A. R. (1999). Reliability and validity of estimating the NIH Stroke Scale score from medical records. Stroke, 30, 1534 -37.
• Kasner, S. E., Cucchiara, B. L., McGarvey, M. L., Luciano, J. M., Liebeskind, D. S., Chalela, J. A. (2003). Modified National Institutes of Health Stroke Scale can be estimated from medical records. Stroke, 34, 568 -70.
• Lai. S. M., Duncan, P. W., Keighley, J. (1998). Prediction of functional outcome after stroke. Comparison of the Orpington Prognostic Scale and the NIH Stroke Scale. Stroke, 29, 1838-1842.
• Lyden, P., Raman, R., Liu, L., Grotta, J., Broderick, J., Olson, S., Shaw, S., Spilker, J., Meyer, B., Emr, M., Warren, M., Marler, J. (2005). NIHSS training and certification using a new digital video disk is reliable. Stroke, 36, 2446-2449.
• Lyden, P. Lau, G. T. (1991). A critical appraisal of stroke evaluation and rating scales. Stroke, 22, 1345-1352. Lyden, P., Brott, T., Tilley, B., Welch, K. M., Mascha, E. ., Levine, S., Haley, E. C., Grotta, J., Marler, J. (1994). Improved reliability of the NIH Stroke Scale using video training. Stroke, 25, 2220-2226.
• Lyden, P., Lu, M. Jackson, C., Marler, J., Kothari, R., Brott, T., Zivin, J. (1999) Underlying structure of the National Institutes of Health Stroke Scale: Results of a factor analysis. Stroke 30, 2347-2354.
• Lyden, P. D., Lu, M., Levine, S. R., Brott, T. G., Broderick, J. (2001). NINDS rtPA Stroke Study Group. A modified National Institutes of Health Stroke Scale for use in stroke clinical trials: preliminary reliability and validity. Stroke, 32, 1310 -17.
• Lyden, P., Claesson, L., Havstad, S., Ashwood, T., Lu, M. (2004). Factor analysis of the National Institutes of Health Stroke Scale in patients with large strokes. Arch Neurol, 61, 1677-80.
• Meyer, B. C., Lyden, P. D., Al-Khoury, L., Cheng, Y., Raman, R., Fellman, R., Beer, J., Rao, R., Zivin, J. A. (2005). Prospective reliability of the STRokE DOC wireless/site independent telemedicine system. Neurology, 64, 1058 -60.
• Meyer, B. C., Hemmen, T. M., Jackson, C. M., Lyden, P. D. (2002). Modified National Institutes of Health stroke scale for use in stroke clinical trials: prospective reliability and validity. Stroke, 33, 1261 -66.
• Muir, K. W., Weir, C. J., Murray, G. D., Povey, C., Lees, K. R. (1996). Comparison of neurological scales and scoring systems for acute stroke prognosis. Stroke, 27, 1817-1820.
• National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group (1995). Tissue Plasminogen activator for acute ischemic stroke. N. Eng. J. Med, 333, 1581-1587.
• Nighoghossian, N., Hermier, M., et al. (2004). Influence of pretreatment MRI parameters on clinical outcome, recanalization and infarct size in 49 stroke patients treated by intravenous tissue plasminogen activator. J Neurol Sci, 225, 3 -9.
• Olinger, C. P., Adams, H. P., Brott, T. G., Biller, J., Barsan, W. G., Toffol, G. J., Eberle, R. W., Marler, J. R. (1990). High-dose intravenous naloxone for the treatment of
  acute ischemic stroke. Stroke, 21, 721-725. 
• Pickard, A. S., Johnson, J. A., Feeny, D. H. (2005). Responsiveness of generic health-related quality of life measures in stroke. Qual Life Res, 14, 207-219.
• Rundek, T., Mast, H., Hartmann, A., Boden -Albala, B., Lennihan, L., Lin, I.-F., Paik, M. C., Sacco, R. L. (2000). Predictors of resource use after acute hospitalization: the Northern Manhattan Stroke Study. Neurology, 55, 1180 -87.
• Saver, J. L., Johnston, K. C., Homer, D., et al. (1999). Infarct volume as a surrogate or auxiliary outcome measure in ischemic stroke clinical trials. Stroke, 30, 293 -98.
• Schiemanck, S. K., Post, M. W. M., Witkamp, T. D., Kappelle, L. J., Prevo, A. J. H. (2005). Relationship between ischemic lesion volume and functional status in the 2nd week after middle cerebral artery stroke. Neurorehabil Neural Repair, 19, 133 -38.
• Schlegel, D., Kolb, S. J., Luciano, J. M., Tovar, J. M., Cucchiara, B. L., Liebeskind, D. S., Kasner, S. E. (2003). Utility of the NIH Stroke Scale as a predictor of hospital disposition. Stroke, 34, 134 -37.
• Schlegel, D. J., Tanne, D., Demchuk, A. M., Levine, S. R., Kasner, S. E. (2004). Multicenter rt-PA Stroke Survey Group. Prediction of hospital disposition after thrombolysis for acute ischemic stroke using the National Institutes of Health Stroke Scale. Arch Neurol, 61, 1061 -64.
• Schmülling, S., Grond, M., Rudolf, J., Kiencke, P. (1998). Training as a prerequisite for reliable use of NIH Stroke Scale [letter]. Stroke,

See the measure

How to obtain the NIHSS:

This measurement tool is available in the following article: https://www.ahajournals.org/doi/10.1161/STROKEAHA.116.015434

See the measure:

Please click here for a copy of the NIHSS