Lower incidence of cerebral infarction correlates with improved functional outcome after aneurysmal subarachnoid hemorrhage
Bibliographic record
Abstract
Despite an undisputed association between vasospasm and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage (SAH), there is debate if this association implies causality. It has been suggested that cerebral infarction is a better outcome measure than vasospasm in clinical trials and observational studies. To further investigate the relationship between infarction and outcome, we performed a systematic review and meta-analysis of all randomized, double-blind, placebo-controlled trials that studied the efficacy of pharmaceutical preventive strategies in SAH patients, and had both cerebral infarction and clinical outcome as outcome events. Effect sizes were expressed in (pooled) risk ratio (RR) estimates with corresponding 95% confidence intervals (CIs). Sensitivity analyses were performed for studies with a low risk of bias and for those who reported outcome at 3 months after SAH. Twenty-four studies including 8,552 patients were included. Pharmaceutical treatments decreased the incidence of both cerebral infarction (RR: 0.83; 95% CI: 0.74 to 0.93) and of poor functional outcome (RR: 0.92; 95% CI: 0.86 to 0.98). The sensitivity analyses did not change the results essentially. These data suggest that the previously observed association between cerebral infarction and functional outcome implies causality, and that cerebral infarction is a better outcome measure than vasospasm in clinical trials and observational studies.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".