Early Termination of Cardiac Rehabilitation Is More Common With Heart Failure With Reduced Ejection Fraction Than With Ischemic Heart Disease
Bibliographic record
Abstract
PURPOSE: Despite known benefits of cardiac rehabilitation (CR), early termination (failure to complete >1 mo of CR) attenuates these benefits. We analyzed whether early termination varied by referral indication in the context of recent growth in patients referred for heart failure with reduced ejection fraction (HFrEF). METHODS: We reviewed records from 1111 consecutive patients enrolled in the NYU Langone Health Rusk CR program (2013-2017). Sessions attended, demographics, and comorbidities were abstracted, as well as primary referral indication: HFrEF or ischemic heart disease (IHD; including post-coronary revascularization, post-acute myocardial infarction, or chronic stable angina). We compared rates of early termination between HFrEF and IHD, and used multivariable logistic regression to determine whether differences persisted after adjusting for relevant characteristics (age, race, ethnicity, body mass index, smoking, hypertension, chronic obstructive pulmonary disease, and depression). RESULTS: Mean patient age was 64 yr, 31% were female, and 28% were nonwhite. Most referrals (85%) were for IHD; 15% were for HFrEF. Early termination occurred in 206 patients (18%) and was more common in HFrEF (26%) than in IHD (17%) (P < .01). After multivariable adjustment, patients with HFrEF remained at higher risk of early termination than patients with IHD (unadjusted OR = 1.73, 95% CI, 1.17-2.54; adjusted OR = 1.53, 95% CI, 1.01-2.31). CONCLUSIONS: Nearly 1 in 5 patients in our program terminated CR within 1 mo, with HFrEF patients at higher risk than IHD patients. While broad efforts at preventing early termination are warranted, particular attention may be required in patients with HFrEF.
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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 | 0.006 |
| 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) | 0.002 | 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".