ABCD‐GENE Score and Clinical Outcomes Following Percutaneous Coronary Intervention: Insights from the TAILOR‐PCI Trial
Bibliographic record
Abstract
Background In TAILOR‐PCI, genotype‐guided selection of P2Y 12 inhibitors after percutaneous coronary intervention did not significantly reduce the risk of ischemic events at 12 months. The Age, Body Mass Index, Chronic Kidney Disease, Diabetes, and Genotyping (ABCD‐GENE) score identifies patients with high platelet reactivity on clopidogrel at increased risk of ischemic events. The aim of this study was to investigate the value of the ABCD‐GENE score for tailoring P2Y 12 inhibitor selection after percutaneous coronary intervention. Methods and Results In a post hoc analysis of the TAILOR‐PCI, outcomes were analyzed by ABCD‐GENE score and allocation to genotype‐guided or conventional P2Y 12 inhibitor selection. Primary (death, myocardial infarction, or stroke) and secondary (cardiovascular death, myocardial infarction, stroke, stent thrombosis, or severe recurrent ischemia) outcomes were assessed. Among 3883 patients discharged on clopidogrel in the genotype‐guided and conventional therapy groups, 15.8% and 84.2% had high (≥10 points) or low (<10) ABCD‐GENE scores, respectively. At 12 months, both the primary (5.2% versus 2.6%, P <0.001) and secondary outcomes (7.7% versus 4.6%, P =0.001) were significantly increased in patients with high ABCD‐GENE score. Among 4714 patients allocated to genotype‐guided or conventional therapy, the former did not significantly reduce the 12‐month risk of the primary and secondary outcomes in both the high and low ABCD‐GENE score groups (p interaction =0.48 and 0.27, respectively). Conclusions Among patients with percutaneous coronary intervention on clopidogrel, the ABCD‐GENE score was helpful in identifying those at higher risk. The ABCD‐GENE score may potentially enhance the precision of tailored selection of P2Y 12 inhibitors, which needs to be confirmed in prospective investigations. Clinical Trial Registration URL: http://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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".