Abstract
BACKGROUND AND PURPOSE: Initial National Institutes of Health Stroke Scale (NIHSS) score is highly predictive of outcome after ischemic stroke. We examined whether grouping strokes by presence of individual NIHSS symptoms could provide prognostic information additional or alternative to the NIHSS total score. METHODS: Ischemic strokes from the Greater Cincinnati Northern Kentucky Stroke Study in 2005 were used to develop the model. Latent class analysis was implemented to form groups of patients with similar retrospective NIHSS (rNIHSS) item responses. Profile group was then used as an independent predictor of discharge modified Rankin and mortality, using logistic regression and Cox proportional hazards model. RESULTS: A total of 2112 stroke patients were identified in 2005. Six distinct profiles were characterized. Consistent with the profile patterns, the median rNIHSS total score decreased from profile A "most severe" (median [interquartile range], 20 [15-25]) to profile F "mild" (1[1-2]). Two profiles falling between these extremes, C and D, both had median rNIHSS total score of 5, but different survival rates. Compared with A, C was associated with 59% risk reduction for death, whereas D with 70%. C patients were more likely to have decreased level of consciousness and abnormal language, whereas D patients were more likely to have abnormal right arm and right leg motor function. CONCLUSIONS: Six rNIHSS profiles were identifiable using latent class analysis. In particular, 2 symptom profiles with identical median rNIHSSS were observed with widely disparate outcomes, which may prove useful both clinically and for research studies as an enhancement to the overall NIHSS score.