Patient Selection and Clinical Outcomes in the STOPDAPT-2 Trial
Bibliographic record
Abstract
Background: We sought to evaluate the impact of patient selection for the STOPDAPT-2 trial (Short and Optimal Duration of Dual Antiplatelet Therapy After Everolimus-Eluting Cobalt-Chromium Stent-2) on clinical outcomes in a registry from a single center that participated in the STOPDAPT-2 trial. Methods: Among 2190 consecutive patients who underwent percutaneous coronary intervention using stent in Kokura Memorial Hospital during the enrollment period of the STOPDAPT-2 trial, 521 patients had exclusion criteria such as in-hospital major complications, anticoagulant use, or prior intracranial bleeding (ineligible group). Among 1669 patients who met the eligibility criteria (eligible group), 582 were enrolled (enrolled group) and 1087 were not enrolled (nonenrolled group) in the STOPDAPT-2 trial. The primary outcome measure was defined as a composite of cardiovascular death, myocardial infarction, definite stent thrombosis, stroke, or Thrombolysis in Myocardial Infarction major and minor bleeding. Results: Compared with the enrolled group, patients in the nonenrolled group more often had high bleeding risk according to the Academic Research Consortium for High Bleeding Risk definition (52.6% versus 41.2%; P <0.001) and were frailer according to the Canadian Study of Health and Aging Clinical Frailty Scale (intermediate, 21.4% versus 14.1%; high, 6.4% versus 2.1%; P <0.001). The cumulative 1-year incidences of the primary outcome measure, all-cause death, and major bleeding were significantly higher in the nonenrolled group than in the enrolled group (7.2% versus 4.5%, P =0.03; 4.1% versus 0.9%, P <0.001; and 4.3% versus 2.1%, P =0.03, respectively) and in the ineligible group than in the eligible group (21.2% versus 6.3%, P <0.001; 9.9% versus 3.0%, P <0.001; and 13.5% versus 3.5%, P <0.001, respectively). Conclusions: Patients who were ineligible, eligible but not enrolled, and enrolled in the STOPDAPT-2 trial had different risk profiles and clinical outcomes, suggesting important implications in applying the trial results in daily clinical practice.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".