Cardiac Rehabilitation Use After Heart Failure Hospitalization Associated With Advanced Heart Failure Center Status
Bibliographic record
Abstract
PURPOSE: Cardiac rehabilitation (CR) is an evidence-based, guideline-endorsed therapy for patients with heart failure with reduced ejection fraction (HFrEF) but is broadly underutilized. Identifying structural factors contributing to increased CR use may inform quality improvement efforts. The objective here was to associate hospitalization at a center providing advanced heart failure (HF) therapies and subsequent CR participation among patients with HFrEF. METHODS: A retrospective analysis was performed on a 20% sample of Medicare beneficiaries primarily hospitalized with an HFrEF diagnosis between January 2008 and December 2018. Outpatient claims were used to identify CR use (no/yes), days to first session, number of attended sessions, and completion of 36 sessions. The association between advanced HF status (hospitals performing heart transplantation or ventricular assist device implantations) and CR participation was evaluated with logistic regression, accounting for patient, hospital, and regional factors. RESULTS: Among 143 392 Medicare beneficiaries, 29 487 (20.6%) were admitted to advanced HF centers (HFCs) and 5317 (3.7%) attended a single CR session within 1 yr of discharge. In multivariable analysis, advanced HFC status was associated with significantly greater relative odds of participating in CR (OR = 2.20: 95% CI, 2.08-2.33; P < .001) and earlier initiation of CR participation (-8.5 d; 95% CI, -12.6 to 4.4; P < .001). Advanced HFC status had little to no association with the intensity of CR participation (number of visits or 36 visit completion). CONCLUSIONS: Medicare beneficiaries hospitalized for HF were more likely to attend CR after discharge if admitted to an advanced HFC than a nonadvanced HFC.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".