Clinical characteristics and outcomes of patients with angina and heart failure in the CHARM (Candesartan in Heart Failure Assessment of Reduction in Mortality and Morbidity) Programme
Bibliographic record
Abstract
AIMS: To investigate the relationship between angina pectoris and fatal and non-fatal clinical outcomes in heart failure with reduced and preserved ejection fraction (HF-REF and HF-PEF, respectively). METHODS AND RESULTS: Of 7599 patients in the CHARM program, 5408 had ischaemic heart disease; 3855 had HF-REF (ejection fraction ≤45%) and 1553 had HF-PEF. These patients were separated into three groups: no history of angina, previous angina, and current angina. Three coronary outcomes were examined: fatal or non-fatal myocardial infarction (MI); MI or hospitalization for unstable angina (UA); and MI, UA or coronary revascularization. The composite heart failure outcome of cardiovascular death or heart failure hospitalization (HFH) was also analysed, along with its components and all-cause mortality. New York Heart Association functional class was worse in both HF-REF and HF-PEF patients with current angina compared with patients without angina (P < 0.001 and P = 0.005 respectively), despite similar clinical examination findings and ejection fraction. Patients with current angina had a higher risk of all three coronary outcomes (adjusted hazard ratios ranging from 1.8-3.1) than those without angina but did not have a higher risk of heart failure outcomes or all-cause mortality. CONCLUSION: In patients with heart failure current angina is associated with significantly more functional limitation and a higher risk of coronary events, across the spectrum of left ventricular ejection fraction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".