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(Stroke. 1999;30:2347-2354.)
© 1999 American Heart Association, Inc.

Original Contributions

Underlying Structure of the National Institutes of Health Stroke Scale

Results of a Factor Analysis

Patrick Lyden, MD; Mei Lu, PhD; Christy Jackson, MD; John Marler, MD; Rashmi Kothari, MD; Thomas Brott, MD Justin Zivin, MD, PhD

From the Department of Neurology, Veterans Administration Medical Center, San Diego, Calif, and Department of Neurosciences, University of California at San Diego School of Medicine (P.L., C.J., J.Z.); Department of Biostatistics and Research Epidemiology, Henry Ford Health Science Center, Detroit, Mich (M.L.); National Institute of Neurological Disorders and Stroke, Bethesda, Md (J.M.); and Departments of Emergency Medicine and Neurology, University of Cincinnati Medical Center (Ohio) (R.K., T.B.).

Correspondence to Patrick D. Lyden, MD, Stroke Center (8466), 3rd Floor, OPC, Suite 3, 200 W Arbor Dr, San Diego, CA 92103-8466.

	Abstract

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
Background and Purpose—No stroke scale has been validated as an outcome measure using data from a clinical trial demonstrating a positive therapeutic effect. Therefore, we proposed to use data from the National Institute of Neurological Disorders and Stroke (NINDS) tPA Stroke Trial to determine whether the National Institutes of Health Stroke Scale (NIHSS) was valid in patients treated with tissue plasminogen activator (tPA) and to explore the underlying clinimetric structure of the NIHSS.

Methods—We performed an exploratory factor analysis of NIHSS data from Part 1 (n=291) of the NINDS tPA Stroke Trial to derive a hypothesized underlying factor structure. We then performed a confirmatory factor analysis of this structure using NIHSS data from Part 2 of the same trial (n=333). We then tested whether this final factor structure could be found in tPA- and placebo-treated patients serially over time after stroke treatment. Using 3-month outcome data, we tested for an association between the NIHSS and other measures of stroke outcome.

Results—The exploratory analysis suggested that there were 2 factors underlying the NIHSS, representing left and right brain function, confirming the content validity of the scale. An alternative structure composed of 4 factors could be derived, with a better goodness of fit: the first 2 factors could represent left brain cortical and motor function, respectively, and the second 2 factors could represent right brain cortical and motor function, respectively. The same factor structures were then found in tPA and placebo patient groups studied serially over time, confirming the exploratory analysis. All 3-month clinical outcomes were associated with each other at subsequent time points, confirming predictive validity.

Conclusions—This is the first study of the validity of a stroke scale in patients treated with effective stroke therapy. The NIHSS appeared to be valid in patients with acute stroke and for finding treatment-related differences. The scale was valid when used serially over time after stroke, up to 3 months, and showed good agreement with other measures of outcome.

Key Words: cerebrovascular disorders • clinimetrics • factor analysis, statistical • neuropsychological tests

	Introduction

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
Demonstration of effective stroke therapy requires a standardized measurement of outcome.^{1 2 3 4 5 6 7} For use in multicenter stroke treatment trials, a rating scale should be reliable, valid, and time efficient.^{8 9} Currently, no stroke scale fulfills all the requirements of rigorous psychometric scale design; however, a few scales, including the National Institutes of Health Stroke Scale (NIHSS), are generally accepted because of their simplicity and relatively rigorous design.^{5 6 7 10 11} The NIHSS contains 15 items, including level of consciousness, eye movement, visual field deficit, and motor and sensory involvement.^{12 13 14} Scale items are scored by degree of severity using weighted scores; reliability has been demonstrated for neurologists, other physicians, and nonphysicians.^{13 14 15 16 17 18} The items contained in the NIHSS were selected on the basis of expert opinion and literature review, thus satisfying the requirements for content validity.^{1 4 5 7} The NIHSS correlates with lesion volume, suggesting that the NIHSS can be used to estimate current clinical status (concurrent criterion validity) on the basis of 1 complementary outcome measure.^{19 20} The scale correlates with alternative measures of neurological outcome, such as Activities of Daily Living (ADL) scales, and other deficit scales, further suggesting concurrent criterion validity.²¹ Another type of criterion validity, known as predictive validity, is demonstrated by using a scale to predict future health status; this type of validity has not previously been demonstrated for the NIHSS.

Another approach to validity is to explore the internal structures or dimensions underlying a scale.^{2 3 4 5 22 23} This sort of data demonstrates the construct validity of a scale: a valid scale should measure 1 or a small number of underlying constructs. We sought to study the underlying structure of the NIHSS using factor analysis, a widely accepted method for deriving the internal structure of a scale.^{5 22 24 25 26 27 28 29 30} Such factors should reflect biological phenomena that make sense to the investigator, such as right or left hemispheric function. Scale items that do not contribute to such factors can be eliminated, thus simplifying the scale and improving its internal reliability.²² We also desired to determine whether the scale structure identified at baseline was independent of therapy and time, that is, we questioned whether the same dimensions could be identified at later time points and in patients who received tissue plasminogen activator (tPA) compared with placebo. This property of a scale is critical; if the structure underlying the scale differs between 2 treatment groups, then the scale is invalid for treatment studies because scale scores would not be comparable between treatment groups. Essentially, 1 group would be tested with 1 version of the scale, and the other group would be tested with a different version. The National Institute of Neurological Disorders and Stroke (NINDS) tPA Stroke Trial afforded an appropriate opportunity for studying this clinimetric property, since the 2 treatment groups differed significantly.³¹

	Subjects and Methods

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
The NINDS tPA Stroke Trial results and the methods used to ensure reliable use of the scale have been published.^{13 31} To participate in the NINDS tPA Stroke Trial, the investigators underwent NIHSS certification by viewing training and testing videotapes.^{13 14} Recertification, using another tape, was conducted every 6 months. Each patient in the trial was scored by a trained, certified investigator at the time of initial stroke evaluation (baseline) and 2 hours, 24 hours, 7 to 10 days, and 3 months later.

To explore the structure underlying the NIHSS, a factor analysis was conducted.²⁴ The NINDS tPA Stroke Trial was conducted in 2 parts using nearly identical methods: We elected to use baseline (pretreatment) NIHSS scores from part 1 (291 patients randomly divided between treatment and placebo) for an exploratory factor analysis. On the basis of the findings of the exploratory analysis, we planned a confirmatory factor analysis using the baseline part 2 data (333 patients randomly divided between treatment and placebo).

The purpose of factor analysis is to describe and explain a large set of independent variables in terms of a few underlying new variables, called factors. If a variable correlates well with the factor, it is said to "load" on that factor. By studying the factor loadings, which is interpreted as a correlation coefficient, one can determine how well the factors explain the data. A group of items in an outcome scale may represent any number of underlying factors, from a single factor to the total number of items. In the latter case, each item represents a unique factor, which is an undesirable property for outcome scales. In general, an ideal scale represents a small number of underlying factors.

To gain an initial estimate of how many factors may underlie the NIHSS, we examined the Scree plot (Figure 1). Once the initial number of factors was selected, a factor analysis was conducted, and we examined the factor loadings on each respective factor. We assessed the goodness of fit of the factor structure using Bentler's Comparative Fit Index (CFI).^{32 33} CFI ranges from 0 to 1 and is viewed as the percentage of variation of the observed measure (the scale items) explained by a given structure (such as R² in a regression model); values >0.90 indicate excellent goodness of fit.³² Several factor structures were examined in this way until we obtained the best solution, defined as the structure that had reasonable goodness of fit (CFI >0.90) and made clinical sense.

View larger version (7K): [in this window] [in a new window]   Figure 1. From the initial set of data, an exploratory factor analysis yields the eigenvalues associated with the data. A Scree plot shows the eigenvalues plotted over the number of factors that could be extracted from the data set. The plot shows that 2 factors, with eigenvalues >2.5, account for the majority of the variance in the data set. However, the third and fourth factors, although <1.0, contribute to more of the variance than the remaining factors. Thus, we selected 2-, 3-, and 4-factor solutions for further study.

A confirmatory factor analysis on a new data set (baseline scores in part 2) was conducted to validate the factor structure identified in the previous, exploratory analyses. CFI was calculated on the basis of the new data; the structure was considered valid if it had reasonable goodness of fit and was consistent with that seen in the previous analyses. Data collected after placebo or tPA treatment were used to determine whether the factor structure identified from baseline data were independent of time and tPA therapy. The data (placebo or tPA) could be used to identify a new factor structure if, in fact, the factor structure depends on time and/or treatment. Patients from parts 1 and 2 were analyzed together for this aspect of the study to allow for greater power. In this part of the analysis only, patients who died, missed 1 of the follow-up NIHSS examinations, or had a scale item recorded as unknown were excluded from the specific analysis involving the missing datum. The factor structure would be considered independent of time or therapy if the CFI goodness of fit at each time point was >0.90 using the same factor structure derived from baseline data.^{32 33}

In addition, the exploratory and confirmatory analyses were conducted, including 15 NIHSS items and 2 extra items regarding distal motor function in the left arm or the right arm. These distal motor items were attached to the scale at the time the trial was begun but were never validated, in response to the criticism that the NIHSS did not measure distal limb strength.^{7 31}

To assess predictive validity, the associations between the NIHSS at each time point and late outcome at 3 months, as measured by Barthel Index, Glasgow Outcome Scale, and Rankin Scale, were calculated with Spearman rank correlation coefficients. We expected significant correlation between the NIHSS at several time intervals and the 3-month clinical outcomes.

	Results

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
There are several versions of the NIHSS; the stroke scale and item labeling used in this study are shown in Table 1. We obtained valid baseline scores on 284 of 291 part 1 patients for the exploratory analyses and 331 of 333 part 2 patients for the confirmatory analyses; invalid scores were either incomplete or missing. The demographic data for these patients are contained in our prior report.³¹ There were similar numbers of lacunar, large-vessel, and cardioembolic strokes in the 2 parts, and there was a similar distribution of subtypes between tPA treatment and placebo.

View this table: [in this window] [in a new window]   Table 1. Current Form of the NIHSS

View this table: [in this window] [in a new window]   Table 1A. Continued

The initial exploratory analysis of the part 1 baseline scores was unstructured and yielded the Scree plot in Figure 1. From the plot, it is clear that 2 factors account for the majority of the variance in the data. The first 2 factors explained 88% and the first 4 factors explained 100% of the variance in the data; the 4-factor solution was considered further. The ataxia item loaded weakly (loadings 0.40) on all factors in the exploratory phase, and therefore this item was excluded; it did not correlate with any factors underlying the scale. The consciousness item (item 1A) loaded on all 4 factors with equal loads 0.4. Similarly, item 4, facial palsy, exhibited loading values of <0.40, suggesting that it contributed little to the scale and could be excluded from the analysis. The final exploratory 4-factor solution using the remaining 12 items produced the best goodness of fit (CFI=0.96). Table 2 lists each factor and the loading of each variable on each factor. The final column in Table 2, R² (also called communality), represents the percentage of variance in the variable that is explained by all the factors. Additional variance could be attributed to other sources, such as interindividual variation or examiner-to-examiner error. From Table 2, it is apparent that the first factor relates to language function, since the aphasia and level-of-consciousness items load most heavily. The second factor is difficult to interpret because it includes the gaze, neglect, visual field, and sensory items. We suspect that a large right hemisphere cortical lesion would impair these items and thus underlie this factor. Factors 3 and 4 clearly represent right and left brain motor functions, respectively.

View this table: [in this window] [in a new window]   Table 2. Exploratory 4-Factor Solution of the 12-Item Scale

We used the baseline data from part 2 for the confirmatory analysis, excluding the level-of-consciousness, face palsy, and ataxia items. The results of the confirmatory analysis on the remaining 12 items (Table 3) again showed excellent goodness of fit (CFI=0.93). The factor structure is identical to that of the exploratory analysis: factor 1 appears to represent left cortical function, and factor 2 represents right cortical function. Factors 3 and 4 again seem to represent left and right brain motor function, respectively.

View this table: [in this window] [in a new window]   Table 3. Confirmatory 4-Factor Solution of the 12-Item Scale

To determine whether the scale is valid within treatment groups, we repeated the analyses in tPA- and placebo-treated patients using data obtained 2 and 24 hours, 7 to 10 days, and 3 months after stroke. The resulting goodness-of-fit statistics are shown in Table 4. The factor structures (ie, loadings) were identical to that at baseline (data not shown). The consistency of the structure and the goodness-of-fit statistics over time and treatment (Table 4) suggest that the scale remains valid, regardless of time from stroke onset or treatment given.

View this table: [in this window] [in a new window]   Table 4. Stability of the 12-Item NIHSS Over Time and Treatment

To assess the predictive validity of the NIHSS using alternative scales, we compared the NIHSS over time with the 3-month outcome using the Barthel Index, Rankin Scale, and Glasgow Outcome Scale. The correlations between the scale and the other clinical outcomes were significant (P<0.001; Table 5) but modest in magnitude at baseline and 2 hours after stroke. The correlation between the NIHSS at baseline and the measures at 90 days demonstrates predictive validity. The absolute values of the correlation coefficients were greater for the later measurements, suggesting that after 2 hours from stroke, the NIHSS values may have greater predictive validity with respect to the 3-month outcome.

View this table: [in this window] [in a new window]   Table 5. Correlation Coefficients of Outcome Measures Serially Over Time After Randomization

	Discussion

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
We explored the NIHSS to identify the constructs, or factors, underlying the scale.²² The Scree plot (Figure 1) suggested 2 factors, and the underlying structure analysis suggested that these 2 factors related to the functions of the 2 cerebral hemispheres. The 4-factor solution, which actually resulted in better goodness of fit, may be viewed as a refinement of the 2-factor solution (Tables 2 and 3). Each of the hemisphere factors seemed to resolve into 2 subfactors, one representing cortical and the other representing motor function (Figure 2). Our data may also be interpreted as confirmation of the construct validity of the scale, since it was designed to detect and measure deficit in either cerebral hemisphere.¹² Brain stem deficits fail to appear as a separate factor here, perhaps because of the low numbers of such patients included in our data set (<15% of the subjects). Thus, the factor structure we determined here may not apply in studies that contain large numbers of patients with brain stem events.

View larger version (10K): [in this window] [in a new window]   Figure 2. The 4-factor solution can be viewed as a subset or refinement of the 2-factor solution. GOF indicates goodness of fit.

Factor analysis depends heavily on the specific data set used; the factor structure we obtained may not necessarily be found in another set of patients.²² To obtain some assurance that the exploratory results are generalizable, a second, confirmatory analysis was required. As shown in Table 3, that analysis confirmed the exploratory study: the NIHSS contained 4 factors corresponding to the 2 cerebral hemispheres, with loadings essentially identical to the exploratory analysis (Table 3). In interpreting these results, it is important to recall that the 2 parts of the NINDS trial were conducted in sequence by investigators who were blinded to the results of part 1 during part 2; the protocol was essentially unchanged during the 2 parts.³¹ The confirmatory analysis is somewhat limited, however, by the fact that the 2 study populations were quite homogeneous. In a future study, using a different study population, it is very likely, but not certain, that the internal structure of the scale would be the same as we determined here.

Further confirmation of the robustness of these findings comes from the analyses conducted on the data collected serially after stroke treatment (Table 4). On repeated administrations, when different examiners were used for patients seen up to 3 months after stroke, the same factors were found. These repeated confirmations suggest that the 4-factor solution is likely to be found in future study populations.

Our data provide a unique opportunity to explore the response of the scale to treatment effects, since the treated group differed significantly from the placebo group. This is an important property of the scale, for if the factor analysis showed that the scale behaved differently in placebo- versus tPA-treated groups, the scale could not be used to measure outcome in further treatment trials. In such an event, the NIHSS would become essentially 2 different scales, 1 for placebo- and 1 for tPA-treated patients, an untenable state. From our study, it is clear that the NIHSS clearly reports deficits in placebo- and tPA-treated patients in a like manner (Table 4). The 4-factor solutions in the 2 treatment groups were similar in the exploratory and confirmatory analyses. The consistency of these repeated analyses suggests that the internal scale structure is the same in patients who receive tPA or placebo. Furthermore, our prior report clearly showed that the scale reported true differences between the groups.³¹ Taken together, these findings confirm the utility of the scale as an outcome measure, its most important function in large clinical trials of putative therapies. However, this assertion will be stronger when a factor analysis yields similar results in another trial of a different, also efficacious, compound.

The ataxia item did not correlate with any factor in the structures we examined. The variance in this question exceeded the variance attributable to the factors, suggesting that this item is either a unique factor or unreliable in its administration. We favor the latter explanation because this item has been shown to have very low reproducibility in some studies^{13 18 21 34} but was reliable in the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) certification study.¹⁴ In a series of videotaped patients, multiple examiners could not clearly grade degrees of ataxia.¹³ Using rating scale analysis of the predecessor of the NIHSS, the University of Cincinnati Stroke Rating Scale, a study of rehabilitation inpatients showed results similar to ours³⁴ : ataxia was found to be an unreliable item that contributed little to the scale; reliability measures improved when this item was deleted. The ataxia item was included in earlier versions of the scale to increase the sensitivity for detecting brain stem deficits, but only a small number of brain stem strokes occurred in our study group. If our sample is highly representative of the distribution of lesions typically entered into multicenter acute therapeutic trials, then it is likely that future stroke trials will likewise contain few brain stem strokes. Deleting ataxia from the scale will not affect validity and may increase reliability of the NIHSS when used acutely (data not shown). Similarly, the items relating to level of consciousness and facial palsy also exhibited smaller loadings in the acute phase, as well as poor reliability in our prior study, and were deleted in the confirmatory analyses. The facial item exhibited poor reliability in a study of the Unified Stroke Scale.² The sensory and dysarthria items showed moderate loadings, but low communalities, throughout our analyses, consistent with their known poor reliability.²¹ It would be appropriate to collapse these items into responses with fewer choices or to eliminate them in a future version of the scale. Our data suggest further, however, that the elimination of the dysarthria item would not change the predictive validity of the NIHSS, given its loadings of 0.49 (Tables 2 and 3). Finally, our data showed that the unvalidated item 12 (distal motor function) should be deleted from the scale because it contributes little to the measurement of the structures underlying the scale. This is true, despite the common assertion that distal limb function should be measured in addition to proximal limb function.

It may seem inconsistent that the questions concerning level of consciousness (items 1b and 1c) load on the left hemisphere factor, but this result likely reflects the role that language plays in clinical assessment of these items. Although these questions are intended to measure level of consciousness, in fact they depend heavily on the presence of intact comprehension. Similarly, the visual field question (item 3) loads heavily on the right hemisphere factor, although there were an equal number of patients with left- and right-sided visual field deficits (data not shown). Patients with left cerebral stroke, because of aphasia, may be more difficult to evaluate, and visual field testing may not be reliable. Right brain stroke patients may exhibit neglect and could therefore appear to exhibit a visual field deficit. Both phenomena might work to enhance the correlation of the visual field item with the right hemisphere factor, although other explanations of this phenomenon might be explored.

Factor analysis has been used previously to study the inherent properties of other scales. Wade and Hewer³⁵ reported finding 2 factors underlying the Barthel Index administered 6 months after stroke, but >67% of the variance in the data was explained by the first factor. This study suggested that the Barthel Index measured only 1 underlying construct, functional independence. A similar analysis of the Fugl-Meyer recovery scale and 3 measures of functional independence was performed on data obtained in the first week after stroke.³⁶ Again, although 3 factors could reasonably be extracted from the data, the first factor explained >80% of the variance. In this study the recovery scale and all 3 functional independence measures correlated very highly with each other.³⁶ Factor analysis has been used to derive the structure underlying global outcome and ADL scales.^{27 29 30} In a study of 1328 patients with presumed transient ischemic attack, factor analysis determined the correlation of various symptoms with vascular territories and neurologists' presumptive localization.²⁶ A caregiver burden scale was factor analyzed to derive key dimensions.²⁸

We identified 2 underlying constructs of the NIHSS when used in the first 24 hours after stroke. These 2 constructs seem to reflect the function of the 2 cerebral hemispheres, confirming the construct validity of the scale. Most importantly, the internal scale structure appears to remain consistent in treated and placebo groups and when administered serially over time. These findings support the validity of the scale for use in future treatment trials as an outcome measure. Some NIHSS items were found to exhibit poor concordance with the 2 constructs and with other items in the scale; when combined with our prior investigations of the scale's clinimetric properties, these results suggest that it may be possible to simplify the NIHSS. A proposal for a simplified scale will be the subject of a future publication.

	Acknowledgments

 
This study was supported by grants from the National Stroke Association, the NINDS (N01-NS02382, N01-NS02374, N01-NS02377, N01-NS02381, N01-NS02379, N01-NS02373, N01-NS02376, N01-NS02378, N01-NS02380), and the Veterans Affairs Research Service.

	Footnotes

 
A list of all NINDS tPA Trial Investigators is found in the Appendix.

	Appendix 1

Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
The following persons and institutions participated in the NINDS tPA Stroke Trial: Clinical Centers: University of Cincinnati (150 patients): Principal Investigator: T. Brott; Co-investigators: J. Broderick, R. Kothari; M. O'Donoghue, W. Barsan, T. Tomsick; Study Coordinators: J. Spilker, R. Miller, L. Sauerbeck; Affiliated Sites: St Elizabeth Hospital (South), J. Farrell, J. Kelly, T. Perkins, R. Miller; University Hospital, T. McDonald; Bethesda North Hospital, M. Rorick, C. Hickey; St Luke Hospital (East), J. Armitage, C. Perry; Providence Hospital, K. Thalinger, R. Rhude; The Christ Hospital, J. Armitage, J. Schill; St Luke Hospital (West), P.S. Becker, R.S. Heath, D. Adams; Good Samaritan Hospital, R. Reed, M. Klei; St Francis/St George Hospital, A. Hughes, R. Rhude; Bethesda Oak Hospital, J. Anthony, D. Baudendistel; St Elizabeth Hospital (North), C. Zadicoff, R. Miller; St Luke's Hospital–Kansas City, M. Rymer, I. Bettinger, P. Laubinger; University of California, San Diego (146 patients): Principal Investigator: P. Lyden; Co-investigators: J. Dunford, J. Zivin; Study Coordinators: K. Rapp, T. Babcock, P. Daum, D. Persona; Affiliated Sites: University of California, San Diego, M. Brody, C. Jackson, S. Lewis, J. Liss, Z. Mahdavi, J. Rothrock, T. Tom, R. Zweifler; Sharp Memorial Hospital, R. Kobayashi, J. Kunin, J. Licht, R. Rowen, D. Stein; Mercy Hospital, J. Grisolia, F. Martin; Scripps Memorial Hospital, Chaplin, N. Kaplitz, J. Nelson, A. Neuren, D. Silver; Tri-City Medical Center, T. Chippendale, E. Diamond, M. Lobatz, D. Murphy, D. Rosenberg, T. Ruel, M. Sadoff, J. Schim, J. Schleimer; Mercy General Hospital, Sacramento, R. Atkinson, D. Wentworth, R. Cummings, R. Frink, P. Heublein; San Diego Veterans Administration Medical Center. University of Texas Medical School, Houston (104 patients): Principal Investigator: J.C. Grotta; Co-investigators: T. DeGraba, M. Fisher, A. Ramirez, S. Hanson, L. Morgenstern, C. Sills, W. Pasteur, F. Yatsu, K. Andrews, C. Villar-Cordova, P. Pepe; Study Coordinators: P. Bratina, L. Greenberg, S. Rozek, K. Simmons; Affiliated Sites: Hermann Hospital; St Luke's Episcopal Hospital; Lyndon Baines Johnson General Hospital; Memorial Northwest Hospital; Memorial Southwest Hospital; Heights Hospital; Park Plaza Hospital; Twelve Oaks Hospital; Houston Fire Department Emergency Medical Services. Long Island Jewish Medical Center (72 patients): Principal Investigators: T.G. Kwiatkowski, S.H. Horowitz; Co-investigators: R. Libman, R. Kanner, R. Silverman, J. LaMantia, C. Mealie, R. Duarte; Study Coordinators: R. Donnarumma, M. Okola, V. Cullin, E. Mitchell. Henry Ford Hospital (62 patients): Principal Investigator: S.R. Levine; Co-investigators: C.A. Lewandowski, G. Tokarski, N.M. Ramadan, P. Mitsias, M. Gorman, B. Zarowitz, J. Kokkinos, J. Dayno, P. Verro, C. Gymnopoulos, R. Dafer, L. D'Olhaberriague; Study Coordinators: K. Sawaya, S. Daley, M. Mitchell. Emory University School of Medicine (39 patients): Principal Investigators: M. Frankel, B. Mackay; Co-investigators: J. Weissman, J. Washington, B. Nguyen, A. Cook, H. Karp, M. Williams, T. Williamson; Study Coordinators: C. Barch, J. Braimah, B. Faherty, J. MacDonald, S. Sailor; Affiliated Sites: Grady Memorial Hospital; Crawford Long Hospital; Emory University Hospital; South Fulton Hospital, M. Kozinn, L. Hellwick. University of Virginia Health System (37 patients): Principal Investigator: E.C. Haley, Jr; Co-investigators: T.P. Bleck, W.S. Cail, G.H. Lindbeck, M.A. Granner, S.S. Wolf, M.W. Gwynn, R.W. Mettetal, Jr, C.W.J. Chang, N.J. Solenski, D.G. Brock, G.F.Ford; Study Coordinators: G.L. Kongable, K.N. Parks, S.S. Wilkinson, M.K. Davis; Affiliated Sites: University of Virginia Health System, E.C. Haley, Jr; Winchester Medical Center, G.L. Sheppard, D.W. Zontine, K.H. Gustin, N.M. Crowe, S.L. Massey. University of Tennessee (14 patients): Principal Investigator: M. Meyer, K. Gaines; Study Coordinators: A. Payne, C. Bales, J. Malcolm, R. Barlow, M.Wilson; Affiliated Sites: Baptist Memorial Hospital, C. Cape; Methodist Hospital Central, T. Bertorini; Jackson Madison County General Hospital, K. Misulis; University of Tennessee Medical Center, W. Paulsen, D. Shepard.

Other participants are as follows: Coordinating Center: Henry Ford Health Sciences Center: Principal Investigator: B.C. Tilley; Co-investigators: K.M.A. Welch, S.C. Fagan, M. Lu, S. Patel, E. Masha, J. Verter; Study Coordinators: J. Boura, J. Main, L. Gordon; Programmers: N. Maddy, T. Chociemski; CT Reading Centers: Part A—Henry Ford Health Sciences Center, J. Windham, H. Soltanian Zadeh; Part B—University of Virginia Medical Center, W. Alves, M.F. Keller, J.R. Wenzel; Central Laboratory: Henry Ford Hospital, N. Raman, L. Cantwell; Drug Distribution Center: A. Warren, K. Smith, E. Bailey. NINDS, Project Officer: J.R. Marler. Data and Safety Monitoring Committee: J.D. Easton, J.F. Hallenbeck, G. Lan, J.D. Marsh, M.D. Walker. Genentech, Inc, Participants: J. Froelich, MD, J. Breed, F. Wang-Chow.

Received September 28, 1998; revision received July 27, 1999; accepted July 27, 1999.

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Top Abstract Introduction Subjects and Methods Results Discussion Appendix 1 References

 
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