Lipid control and stroke risk in atrial fibrillation patients treated with direct oral anticoagulants and statins
Bibliographic record
Abstract
Abstract Introduction: The risk of ischemic stroke and intracerebral hemorrhage (ICH) with intensive lipid control by statins among patients with atrial fibrillation (AF) who require direct oral anticoagulants (DOAC) is unclear. We aimed to determine the risks of ischemic stroke and ICH in AF patients treated with DOAC and statins. Patients and methods: In a population-based retrospective cohort study, we identified AF patients concurrently on DOAC and statins from 2015 to 2021 in Hong Kong. Primary outcome was ischemic stroke. Secondary outcomes were ICH and death. We correlated study outcomes with low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) as time-varying, continuous variables with restricted cubic spline. In secondary analyses, the risks of study outcomes with statin intensity (low, moderate, high) were determined by multivariable time-dependent marginal structural Cox models. Results: We identified 32,752 AF patients co-prescribed with DOAC and statins. Lower LDL-C (p < 0.001) and higher HDL-C (p < 0.001) levels were associated with lower risk of ischemic stroke but not significantly associated with ICH. LDL-C of <1.8 mmol/L (70 mg/dL) was not associated with mortality (19.6% vs 18.4%, difference 1.2% [95% CI −0.35 to 2.13]). High-intensity statin was associated with a lower risk of ischemic stroke compared with low-intensity statin (weighted Cox-specific hazard ratio [95% CI]: 0.82 [0.67–0.99], p = 0.040) independent of LDL-C levels. Similar associations were found in 11,444 AF patients with a history of ischemic stroke. Discussion and conclusion: Intensive lipid control by high-intensity statins was associated with a lower risk of ischemic stroke in AF patients who required DOACs and did not appear to increase the risk of 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".