Association Between Beta-Blocker or Statin Drug Use and the Risk of Hemorrhage From Cerebral Cavernous Malformations
Bibliographic record
Abstract
Background: We aimed to determine the association between beta-blocker or statin drug use and the future risk of symptomatic intracranial hemorrhage or persistent/progressive focal neurological deficit from cerebral cavernous malformations (CCM). Methods: The population-based Scottish Audit of Intracranial Vascular Malformations prospectively identified adults resident in Scotland first diagnosed with CCM during 1999 to 2003 or 2006 to 2010. We compared the association between beta-blocker or statin drug use after first presentation and the occurrence of new intracranial hemorrhage or persistent/progressive focal neurological deficit due to CCM for up to 15 years of prospective follow-up. We confirmed proportional hazards and used survival analysis with multivariable adjustment for age, intracranial hemorrhage at CCM presentation, and brain stem CCM location. Results: Sixty-three (21%) of 300 adults used beta-blockers (27/63 [43%] used propranolol), and 73 (24%) used statin drugs over 3634 person-years of follow-up. At baseline, the only statistically significant imbalances in prespecified potential confounders were age by statin use and intracranial hemorrhage at presentation by beta-blocker use. Beta-blocker use was associated with a lower risk of new intracranial hemorrhage or persistent/progressive focal neurological deficit (adjusted hazard ratio, 0.09 [95% CI, 0.01–0.66]; P =0.018). Statin use was associated with a nonsignificant lower risk of intracranial hemorrhage or persistent/progressive focal neurological deficit (adjusted hazard ratio, 0.37 [95% CI, 0.01–1.07]; P =0.067). Conclusions: Beta-blocker, but not statin, use was associated with a lower risk of intracranial hemorrhage or persistent/progressive focal neurological deficit in patients with CCM.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".