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Record W4409983096 · doi:10.1161/hcq.0000000000000140

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

2025· article· en· W4409983096 on OpenAlexaboutno aff
Marlene S. Williams, Glenn N. Levine, Dinesh Kalra, Anandita Agarwala, Diana Baptiste, Joaquin E. Cigarroa, Rebecca L. Diekemper, Marva V. Foster, Martha Gulati, Timothy D. Henry, Dipti Itchhaporia, Jennifer S. Lawton, L. Kristin Newby, Kelly C. Rogers, Krishan Soni, Jacqueline E. Tamis‐Holland

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGuidelineReferralPsychological interventionCanadian Cardiovascular SocietyPhysical therapyIntensive care medicineSmoking cessationPopulationDisease managementQuality managementHealth careRehabilitationDiseaseFamily medicineInternal medicineNursingMyocardial infarctionAnginaPathology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.066
GPT teacher head0.375
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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