Red cell distribution width and neurological scoring systems in acute stroke patients
Bibliographic record
Abstract
OBJECTIVES: The purpose of the present study was to evaluate the association between the red blood cell distribution width (RDW) and the Glasgow Coma Scale (GCS), Canadian Neurological Scale (CNS), and National Institutes of Health Stroke Scale (NIHSS) scores in patients who had acute ischemic stroke. METHODS: This prospective observational cohort study included 88 patients who have had acute ischemic stroke and a control group of 40 patients who were evaluated in the Emergency Department for disorders other than acute ischemic stroke. All subjects had RDW determined, and stroke patients had scoring with the GCS, CNS, and NIHSS scores. The GCS, CNS, and NIHSS scores of the patients were rated as mild, moderate, or severe and compared with RDW. RESULTS: Stroke patients had significantly higher median RDW than control subjects. The median RDW values were significantly elevated in patients who had more severe rather than milder strokes rated with all three scoring systems (GCS, CNS, and NIHSS). The median RDW values were significantly elevated for patients who had moderate rather than mild strokes rated by GCS and CNS and for patients who had severe rather than mild strokes rated by NIHSS. The area under the receiver operating characteristic curve was 0.760 (95% confidence interval, 0.676-0.844). Separation of stroke patients and control groups was optimal with RDW 14% (sensitivity, 71.6%; specificity, 67.5%; accuracy, 70.3%). CONCLUSION: In stroke patients who have symptoms <24 hours, the RDW may be useful in predicting the severity and functional outcomes of the 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".