Antiplatelet Therapy After Spontaneous Intracerebral Hemorrhage and Functional Outcomes
Bibliographic record
Abstract
Background and Purpose- Observational data suggest that antiplatelet therapy after intracerebral hemorrhage (ICH) alleviates thromboembolic risk without increasing the risk of recurrent ICH. Given the paucity of data on the relationship between antiplatelet therapy after ICH and functional outcomes, we aimed to study this association in a multicenter cohort. Methods- We meta-analyzed data from (1) the Massachusetts General Hospital ICH registry (n=1854), (2) the Virtual International Stroke Trials Archive database (n=762), and (3) the Yale stroke registry (n=185). Our exposure was antiplatelet therapy after ICH, which was modeled as a time-varying covariate. Our primary outcomes were all-cause mortality and a composite of major disability or death (modified Rankin Scale score 4-6). We used Cox proportional regression analyses to estimate the hazard ratio of death or poor functional outcome as a function of antiplatelet therapy and random-effects meta-analysis to pool the estimated HRs across studies. Additional analyses stratified by hematoma location (lobar and deep ICH) were performed. Results- We included a total of 2801 ICH patients, of whom 288 (10.3%) were started on antiplatelet medications after ICH. Median times to antiplatelet therapy ranged from 7 to 39 days. Antiplatelet therapy after ICH was not associated with mortality (hazard ratio, 0.85; 95% CI, 0.66-1.09), or death or major disability (hazard ratio, 0.83; 95% CI, 0.59-1.16) compared with patients not started on antiplatelet therapy. Similar results were obtained in additional analyses stratified by hematoma location. Conclusions- Antiplatelet therapy after ICH appeared safe and was not associated with all-cause mortality or functional outcome, regardless of hematoma location. Randomized clinical trials are needed to determine the effects and harms of antiplatelet therapy after ICH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.006 | 0.001 |
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 teacher head, 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".