Retrospective Assessment of Initial Stroke Severity With the NIH Stroke Scale

Abstract

Background and Purpose-It is important to adjust stroke outcomes for differences in initial stroke severity. The NIH Stroke Scale (NIHSS) is a commonly used stroke severity measure but has been validated for retrospective scoring only in a subset of stroke clinical trial participants. The purpose of this research was to assess the validity and reliability of an algorithm for retrospective NIHSS scoring in a setting with usual chart documentation. Methods-An algorithm for retrospective NIHSS scoring was developed with written history and physical admission notes.Missing physical examination data were scored as normal. One investigator prospectively scored the admission NIHSS in 32 consecutive stroke patients. Two raters retrospectively scored the NIHSS by applying the algorithm to photocopied admission notes. Linear regression was used to assess interrater reliability and agreement between prospective and retrospective NIHSS scores. The Wilcoxon signed rank test was used to assess systematic scoring bias. Weighted kappa statistics were calculated to assess the level of agreement of individual NIHSS items. Results-Only 1 admission note was complete for all NIHSS elements. Interrater reliability was near perfect (r 2 ϭ0.98, PϽ0.001). Agreement between prospective and retrospective NIHSS score was also excellent (r 2 ϭ0.94, PϽ0.001) and there was no systematic bias in retrospective scores. Agreement for individual items was moderate to high for all items except level of consciousness. Conclusions-Retrospective NIHSS scoring with the algorithm is reliable and unbiased even when physical examination elements are missing from the written record. Stroke research using retrospective review of charts or of administrative databases should adjust for differences in stroke severity using such an algorithm. (Stroke. 2000;31:858-862.)Key Words: outcome Ⅲ prognosis Ⅲ stroke assessment T here is increasing emphasis on assessing quality of care at both local and national levels. Quality is usually inferred by linking specific structure or process of care indicators to patient-level outcomes such as mortality, length of stay, or functional outcome. Interpreting these data, particularly across institutions, requires case mix adjustment. This can be difficult, because quality assessments and case mix adjustment are usually done from retrospective analyses of administrative databases that do not contain clinically relevant variables for measuring disease severity.When patient-level stroke outcomes are assessed, initial stroke severity is one of the variables that must be taken into account in adjusting outcomes for differences in case mix. 1,2 This adjustment is critical, because it is well established that stroke severity at onset influences many outcomes, including mortality, length of stay, progression of deficit, and eventual functional recovery. [3][4][5][6][7][8] Although initial stroke severity can be validly assessed in prospective studies, requisite variables are not typically recorded in a quantifiable way in most patientca...

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