Incident Heart Failure in Outpatients with Chronic Coronary Syndrome: Results from the International Prospective CLARIFY Registry
Bibliographic record
Abstract
Abstract Aim The contemporary incidence of heart failure (HF) in patients with chronic coronary syndrome is unclear. We aimed to study the incidence and predictors of cardiovascular (CV) death, HF hospitalization or new-onset HF not requiring hospitalization, in patients included in the CLARIFY registry. Methods and results CLARIFY is a contemporary, international registry of ambulatory patients with chronic coronary artery disease, conducted in 45 countries. At baseline, data on demographics, ethnicity, CV risk factors, medical history, cardiac parameters and medication were collected. Patients were followed up yearly up to 5 years. In this analysis, 26 769 patients with no HF history were included. At 5-year follow-up, 4393 patients (16.4%) reached the primary endpoint comprising CV death, HF hospitalization, or new-onset HF. Only 16.7% of them (n = 732) required hospitalization for HF. All-cause death occurred in 6.6% of patients (61.4% were CV). Age over 70 years, left ventricular ejection fraction <50%, Canadian Cardiovascular Society class ≥2 angina, atrial fibrillation or paced rhythm on the ECG, body mass index <20 kg/m2, and a history of stroke, were the most robust predictors of the primary outcome. Age <50 years, Asian ethnicity, and percutaneous revascularization were negative predictors of the outcome. Conclusion A sizeable proportion of patients with chronic coronary syndrome develop HF, which only infrequently requires hospitalization. Early identification of patients with HF may lead to early treatment, and help to further decrease mortality and morbidity. This concept needs confirmation in future studies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".