Statins May Increase Intracerebral Hemorrhage Volume
Bibliographic record
Abstract
BACKGROUND: Some studies have suggested an association between hypocholesterolemia and intracerebral hemorrhage (ICH). In the SPARCL trial, statin use increased ICH risk. We tested the hypothesis that use of statins affects the volume of spontaneous ICH and contributes to the progression of ICH volume between baseline and follow-up CT scans. METHODS: Consecutive cases of spontaneous ICH were reviewed. Secondary causes were excluded. We measured ICH volume on the baseline and follow-up CT scans using the AxBxC/2 method. Multivariate analysis and logistic regression modeling were used. The primary outcome was the ICH volume on the baseline CT scan. Secondary outcomes included volume variation between the baseline and the first follow up CT scans and death. RESULTS: Of 303 subjects, 71 were taking a statin at the time of the ICH (23%). Statin users were significantly more likely to be younger, to have co-morbidities and take anticoagulant or anti-platelet medication. They also had a higher baseline ICH volume than non-statin users (median 31.2 [10, 82.1] ml vs 16 [4, 43.8] ml; p=0.006). Adjusting for possible confounders, statins remained associated with an increased ICH volume (p=0.007). There was a significant mean ICH volume progression between the first and second CT scans in statin users (+10.8 vs +0.9 ml; p=0.03; 95% CI: [-1, +22.6] [-2.5, +4.3]). No difference in mortality was seen between the two groups. CONCLUSION: Treatment with HMG-CoA reductase inhibitors may be a risk factor for increased ICH volume in spontaneous brain hemorrhages and could contribute to hemorrhage's volume progression.
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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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".