Bibliographic record
Abstract
BACKGROUND: A recent post hoc analysis of a large randomized trial in patients with cerebrovascular disease suggested that statins may increase the risk of intracerebral hemorrhage (ICH). OBJECTIVE: To examine the association between statins and ICH in patients with recent ischemic stroke in a population-based setting. DESIGN: Retrospective propensity-matched cohort study with accrual from July 1, 1994, to March 31, 2008. SETTING: Ontario, Canada. PARTICIPANTS: A total of 17 872 patients aged 66 years and older who initiated statin therapy following acute ischemic stroke and were followed for a median of 4.2 years (interquartile range, 2.4-5.0 years). To enhance causal inference, we conducted several tests of specificity to exclude healthy user bias in this sample. Main Outcome Measure Hospitalization or emergency department visit for ICH defined using validated diagnosis coding. RESULTS: Overall, 213 episodes of ICH occurred. In the primary analysis comparing statin users with nonusers, we found no association between statins and ICH (hazard ratio = 0.87; 95% confidence interval, 0.65-1.17). Subgroup and dose-response analyses yielded similar results. In tests of specificity, statin therapy was not associated with bone mineral density testing, vitamin D or B(12) screening, gastrointestinal endoscopy, or elective knee arthroplasty, suggesting that results were not due to healthy user bias or differences in quality of care. CONCLUSION: Statin exposure following ischemic stroke was not associated with ICH.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".