Dual antithrombotic treatment in chronic coronary syndrome: European Society of Cardiology criteria vs. CHADS-P2A2RC score
Bibliographic record
Abstract
AIMS: According to the 2019 European Society of Cardiology (ESC) guidelines on chronic coronary syndromes (CCS), adding a P2Y12 inhibitor or rivaroxaban to aspirin should be considered in high-risk patients. We estimated the proportion of patients eligible for treatment with the ESC criteria and examined if a recently validated risk score (CHADS-P2A2RC) could improve risk prediction. METHODS AND RESULTS: We included 61 338 CCS patients undergoing first-time coronary angiography in Western Denmark (2003-16) and classified them according to the ESC criteria and the CHADS-P2A2RC score. The ESC criteria identified 33.9% as high risk, 53.3% as moderate risk, and 12.8% as low risk. The CHADS-P2A2RC score identified 24.9% as high risk (≥4 points), 48.1% as moderate risk (2-3 points), and 27.0% as low risk (≤1 points). Major adverse cardiovascular events per 100 person-years were 4.8 [95% confidence interval (CI) 4.6-5.0] in patients considered high risk with both schemes, 2.1 (95% CI 2.0-2.2) in patients considered high risk with the ESC but low-to-moderate risk with the CHADS-P2A2RC criteria, 3.8 (95% CI 3.6-4.1) in patients considered low-to-moderate risk with the ESC but high risk with the CHADS-P2A2RC criteria, and 1.5 (95% CI 1.5-1.6) in patients considered low-to-moderate risk with both schemes. The CHADS-P2A2RC score enabled correct downward risk reclassification of 5161 patients (8%) without events, yielding an improved specificity of 9.7%, a loss of sensitivity of 4.4%, and an overall net reclassification index of 0.053. CONCLUSION: Based on the 2019 ESC guidelines, dual antithrombotic treatment should be considered in one-third of CCS patients. The CHADS-P2A2RC score improved risk classification and may particularly identify low-risk patients with limited benefit from treatment.
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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 | 0.001 | 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) | 0.001 | 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".