2025 AHA/ACC Clinical Performance and Quality Measures for Patients With Chronic Coronary Disease: A Report of the American College of Cardiology/American Heart Association Joint Committee on Performance Measures
Bibliographic record
Abstract
Chronic coronary disease (CCD) is the leading cause of death in the United States. There is an ongoing imperative to disseminate evidence-based and patient-centered care recommendations that further align the management of patients with CCD to updated evidence-based guidelines. The writing committee developed a comprehensive CCD measure set comprising 10 performance measures and 3 quality measures, the focus of which is to include practical steps to specifically advance care in the CCD population. The measure set begins with an assessment of tobacco use and evidence-based cessation interventions. Also included are topics such as antiplatelet therapy, lipid assessment and low-density lipoprotein cholesterol goals, and guideline-directed management and therapy for hypertension and reduced left ventricular dysfunction in patients with CCD. The measure set concludes with an emphasis on the importance of cardiac rehabilitation referral and patient education, including symptom management and lifestyle modification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.070 | 0.116 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".