Stroke Unit Care Benefits Patients With Intracerebral Hemorrhage
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Patients with any type of stroke managed in organized inpatient (stroke unit) care are more likely to survive, return home, and regain independence. However, it is uncertain whether these benefits apply equally to patients with intracerebral hemorrhage and ischemic stroke. METHODS: We conducted a secondary analysis of a systematic review of controlled clinical trials comparing stroke unit care with general ward care, including only trials published after 1990 that could separately report outcomes for patients with intracerebral hemorrhage and ischemic stroke. We performed random-effects meta-analyses and tested for subgroup interactions by stroke type. RESULTS: We identified 13 trials (3570 patients) of modern stroke unit care that recruited patients with intracerebral hemorrhage and ischemic stroke, of which 8 trials provided data on 2657 patients. Stroke unit care reduced death or dependency (risk ratio [RR], 0.81; 95% confidence interval [CI], 0.471-0.92; P=0.0009; I2=60%) with no difference in benefits for patients with intracerebral hemorrhage (RR, 0.79; 95% CI, 0.61-1.00) than patients with ischemic stroke (RR, 0.82; 95% CI, 0.70-0.97; Pinteraction=0.77). Stroke unit care reduced death (RR, 0.79; 95% CI, 0.64-0.97; P=0.02; I2=49%) to a greater extent for patients with intracerebral hemorrhage (RR, 0.73; 95% CI, 0.54-0.97) than patients with ischemic stroke (RR, 0.82; 95%, CI 0.61-1.09), but this difference was not statistically significant (Pinteraction=0.58). CONCLUSIONS: Patients with intracerebral hemorrhage seem to benefit at least as much as patients with ischemic stroke from organized inpatient (stroke unit) care.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".