Trends and Outcomes Associated With Bariatric Surgery and Pharmacotherapies With Weight Loss Effects Among Patients With Heart Failure and Obesity
Bibliographic record
Abstract
BACKGROUND: Utilization patterns of bariatric surgery among older patients with heart failure (HF), and the associations with cardiovascular outcomes, are not well known. METHODS: Medicare beneficiaries with HF and at least class II obesity from 2013 to 2020 were identified with Medicare Provider Analysis and Review 100% inpatient files and Medicare 5% outpatient files. Patients who underwent bariatric surgery were matched to controls in a 1:2 ratio (matched on exact age, sex, race, body mass index, HF encounter year, and HF hospitalization rate pre-surgery/matched period). In an exploratory analysis, patients prescribed pharmacotherapies with weight loss effects (semaglutide, liraglutide, naltrexone-bupropion, or orlistat) were identified and matched to controls with a similar strategy in addition to HF medical therapy data. Cox models evaluated associations between weight loss therapies (as a time-varying covariate) and mortality risk and HF hospitalization rate (calculated as the rate of HF hospitalizations following index HF encounter per 100 person-months) during follow-up. RESULTS: Of 298 101 patients with HF and body mass index ≥35 kg/m 2 , 2594 (0.9%) underwent bariatric surgery (45% men; mean age, 56.2 years; mean body mass index, 51.5 kg/m 2 ). In propensity-matched analyses over a median follow-up of 4.7 years, bariatric surgery was associated with lower risk of all-cause mortality (HR, 0.55 [95% CI, 0.49–0.63]; P <0.001), greater reduction in HF hospitalization rate (rate ratio, 0.72 [95% CI, 0.67–0.77]; P <0.001), and lower atrial fibrillation risk (HR, 0.78 [95% CI, 0.65–0.93]; P =0.006). Use of pharmacotherapies with weight loss effects was low (4.8%), with 96.3% prescribed GLP-1 (glucagon-like peptide-1) agonists (semaglutide, 23.6%; liraglutide, 72.7%). In propensity-matched analysis over a median follow-up of 2.8 years, patients receiving pharmacotherapies with weight loss effects (versus matched controls) had a lower risk of all-cause mortality (HR, 0.82 [95% CI, 0.71–0.95]; P =0.007) and HF hospitalization rate (rate ratio, 0.87 [95% CI, 0.77–0.99]; P =0.04). CONCLUSIONS: Bariatric surgery and pharmacotherapies with weight loss effects are associated with a lower risk of adverse outcomes among older patients with HF and obesity; however, overall utilization remains low.
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 | 0.001 |
| 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".