Protective Effects of Statins on Limb and Cardiovascular Outcomes in Patients with Peripheral Artery Disease and End-Stage Renal Disease.
Bibliographic record
Abstract
Background: Previous studies have reported that statins have inconsistent and marginal cardiovascular (CV) benefits in patients with end-stage renal disease (ESRD). However, whether statins play a secondary preventive role in patients with peripheral artery disease (PAD) and ESRD remains unclear. Objectives: This study aimed to compare the long-term clinical outcomes between statin users and nonusers with PAD and ESRD. Methods: This retrospective cohort study assessed the long-term protective effects of statins using data from the National Health Insurance Research Database in Taiwan. Propensity score matching was performed according to sex, age, index year, related comorbidities, and medications. The main outcomes were limb events and major adverse CV events (MACEs). Results: The statin user group (n = 4,460) was compared with the propensity score-matched statin nonuser group (n = 4,460). The mean age of the matched patients was 64 years, and 40% of the patients were men. The baseline characteristics of the groups were well-balanced. The overall limb event and MACE rates were not different between the two groups. However, the statin user group had lower rates of limb amputation [adjusted hazard ratio (aHR): 0.85, 95% confidence interval (CI): 0.73-0.99], stroke (aHR: 0.71, 95% CI: 0.62-0.83), CV death (aHR: 0.46, 95% CI: 0.32-0.66), and all-cause death (aHR: 0.45, 95% CI: 0.42-0.48) despite having a higher rate of percutaneous transluminal angioplasty for PAD. Conclusions: This population-based retrospective cohort study demonstrated that statin therapy was associated with a lower risk of limb amputation, nonfatal stroke, CV death, and all-cause death in patients with PAD and ESRD.
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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 | 0.002 |
| 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 | 0.000 | 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".