Semaglutide in HFpEF across obesity class and by body weight reduction: a prespecified analysis of the STEP-HFpEF trial
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In the STEP-HFpEF trial, semaglutide improved symptoms, physical limitations and exercise function and reduced body weight in patients with obesity phenotype of heart failure and preserved ejection fraction (HFpEF). This prespecified analysis examined the effects of semaglutide on dual primary endpoints (change in Kansas City Cardiomyopathy Questionnaire-Clinical Summary Score (KCCQ-CSS) and body weight) and confirmatory secondary endpoints (change in 6-minute walk distance (6MWD), hierarchical composite (death, HF events, change in KCCQ-CSS and 6MWD) and change in C-reactive protein (CRP)) across obesity classes I–III (body mass index (BMI) 30.0–34.9 kg m − 2 , 35.0–39.9 kg m − 2 and ≥40 kg m − 2 ) and according to body weight reduction with semaglutide after 52 weeks. Semaglutide consistently improved all outcomes across obesity categories ( P value for treatment effects × BMI interactions = not significant for all). In semaglutide-treated patients, improvements in KCCQ-CSS, 6MWD and CRP were greater with larger body weight reduction (for example, 6.4-point (95% confidence interval (CI): 4.1, 8.8) and 14.4-m (95% CI: 5.5, 23.3) improvements in KCCQ-CSS and 6MWD for each 10% body weight reduction). In participants with obesity phenotype of HFpEF, semaglutide improved symptoms, physical limitations and exercise function and reduced inflammation and body weight across obesity categories. In semaglutide-treated patients, the magnitude of benefit was directly related to the extent of weight loss. Collectively, these data support semaglutide-mediated weight loss as a key treatment strategy in patients with obesity phenotype of HFpEF. ClinicalTrials.gov identifier: NCT04788511 .
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it