Impact of a Multidisciplinary Heart Failure Post-hospitalization Program on Heart Failure Readmission Rates
Bibliographic record
Abstract
BACKGROUND: Specialized chronic heart failure (HF) clinics have demonstrated significant reductions in readmissions. Limited evidence is available regarding HF clinics in the immediate post-discharge period. OBJECTIVE: To evaluate the effect of a multidisciplinary HF clinic on 90-day readmission rates and all-cause mortality in those recently discharged from a HF hospitalization. METHODS: In this retrospective cohort study, patients discharged with a primary HF diagnosis who attended the HF postdischarge clinic in 2010-2012 were compared with controls from 2009. During 6 clinic visits, patients were seen by a physician assistant, clinical pharmacist specialist, and case manager, with care overseen by a cardiologist. The program focused on optimizing therapy, identifying HF etiology/precipitating factors, medication titration, education, and medication adherence. The primary outcome was 90-day HF readmission. A multivariate Cox proportional hazards model was used to compare outcomes. RESULTS: Among the 277 patients (144 clinic, 133 control) in the study, 7.6% of patients in the clinic and 23.3% of patients in the control group were readmitted for HF within 90 days (aHR (adjusted hazard ratio) = 0.17; 95% CI = 0.07-0.41; P < 0.001; ARR (absolute risk reduction) = 15.7%; NNT (number needed to treat) = 7). Clinic patients had lower 90-day time-to-first HF readmission or all-cause mortality (9.0% vs 28.6%; aHR = 0.28; 95% CI = 0.06-0.31; P < 0.001; ARR = 19.6%; NNT = 6). CONCLUSIONS: The multidisciplinary HF posthospitalization outpatient program was associated with a significant reduction in 90-day HF readmissions in patients who were recently discharged from a HF hospitalization.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".