Racial Variation in Initial Stroke Severity
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Blacks experience greater morbidity and mortality from stroke than do whites. The degree to which this is due to the severity of the initial stroke is not known. The objective of this study is to determine whether there is a racial difference in initial stroke severity. METHODS: A secondary analysis of a prospective cohort of 984 veterans (29.7% black) admitted to any of 9 geographically diverse Veterans Administration Hospitals for acute stroke between April 1995 and March 1997 was performed. Initial stroke severity was ascertained by using the modified Canadian Neurological Scale (CNS) applied retrospectively to medical record data. Stroke severity, unadjusted and adjusted for covariates, was compared between black and white patients. RESULTS: Blacks had greater initial stroke severity than did whites (mean CNS score 7.96 versus 8.32, respectively; P=0.039), with a 0.5-point difference on the scale corresponding to a single-level decrement in either speech or strength of half of an extremity. This difference persisted with adjustment for other important predictors of stroke severity (P=0. 035). However, there was no significant racial difference in severity when CNS scores were collapsed into a priori clinically relevant categories. CONCLUSIONS: Compared with whites, blacks show greater severity of stroke at hospital admission. It remains uncertain whether the relatively small but significant difference at presentation fully explains the striking racial differences in morbidity and mortality from stroke.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".