Effectiveness of Preprocedural Statin Therapy on Clinical Outcomes for Patients With Stable Coronary Artery Disease After Percutaneous Coronary Interventions
Bibliographic record
Abstract
BACKGROUND: Data have shown that preprocedural statin therapy reduces periprocedural myocardial infarction after percutaneous coronary intervention (PCI). However, whether preprocedural statins improve clinical outcomes in patients with stable coronary artery disease (CAD) has not been established. We aimed to evaluate the clinical effectiveness of preprocedural statin therapy in patients with stable CAD undergoing PCI. METHODS AND RESULTS: We conducted an observational study of 12 980 patients, age >65 years with stable CAD, who underwent PCI from December 1, 2003, to March 31, 2008. Using propensity score-matching analysis, 3098 unique matched pairs (6196 patients) who had similar likelihood of receiving preprocedural statins were identified. Additional analyses adjusting for postprocedural statins as a time-varying variable were performed. The main outcome measure was a composite of death or recurrent acute coronary syndrome. In the propensity-matched cohort, at 90 days, the primary outcome of death and acute coronary syndrome occurred in 5.6% in the preprocedural statin group as compared with 7.4% in the no-pretreatment group (P=0.005). Improved clinical outcomes associated with preprocedural statins were still observed at 2 years (16.7% versus 19.3%, P=0.007). The effectiveness of preprocedural statins was most pronounced at 90 days after PCI (adjusted hazard ratio, 0.80; 95% confidence interval, 0.65 to 0.98) but was no longer significant at 1 year (adjusted hazard ratio, 0.92; 95% confidence interval, 0.79 to 1.07) after accounting for postprocedural statin therapy. CONCLUSIONS: Preprocedural statin therapy was associated with significant reduction in the risk of death or recurrent acute coronary syndrome in stable CAD patients after PCI. These findings support the routine use of preprocedural statins for suitable candidates.
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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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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".