Sex‐Specific Differences in Clinical Outcomes After Percutaneous Coronary Intervention: Insights from the TAILOR‐PCI Trial
Bibliographic record
Abstract
Background TAILOR‐PCI (Tailored Antiplatelet Initiation to Lessen Outcomes due to decreased Clopidogrel Response After Percutaneous Coronary Intervention) studied genotype‐guided selection of antiplatelet therapy after percutaneous coronary intervention versus conventional therapy with clopidogrel. The presence of CYP2C19 loss‐of‐function alleles in patients treated with clopidogrel may be associated with increased risk for ischemic events. We report a prespecified sex‐specific analysis of genotyping and associated cardiovascular outcomes from this study. Methods and Results Associations between sex and major adverse cardiac events (MACE: cardiovascular death, myocardial infarction, stroke, stent thrombosis, and severe recurrent ischemia) and Bleeding Academic Research Consortium (BARC) bleeding at 12 months were analyzed using Cox proportional‐hazards models. Among 5276 randomized patients, loss‐of‐function carriers were observed in ≈36% of both sexes, and >80% of carriers were heterozygotes. At 12 months, after adjustment for baseline differences, risks of MACE (HR , 1.28 [0.97 to 1.68]; P =0.088) and BARC bleeding (hazard ratio [HR], 1.36 [0.91 to 2.05]; P =0.14) were comparable among women and men. There were no significant interactions between sex and treatment strategy for MACE interaction P value ( P int =0.59) or BARC bleeding ( P int =0.47) nor for sex and genotype (MACE P int =0.15, and BARC bleeding P int =0.60). Conclusions CYP2C19 loss‐of‐function alleles were present in ≈1 in 3 women and men. Women had similar adjusted risks of MACE and bleeding as men following percutaneous coronary intervention. Genotype‐guided therapy did not significantly reduce the risk of MACE or bleeding relative to conventional therapy for both sexes. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01742117.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".