Obesity in Heart Failure with Preserved Ejection Fraction: Insights from the REDUCE LAP-HF II Trial
Bibliographic record
Abstract
Abstract Aims Obesity is causally related to the development of heart failure with preserved ejection fraction (HFpEF) but complicates the diagnosis and treatment of this disorder. We aimed to determine the relationship between severity of obesity and clinical, echocardiographic and haemodynamic parameters in a large cohort of patients with documented HFpEF. Methods and results The REDUCE LAP-HF II trial randomized 626 patients with ejection fraction ≥40% and exercise pulmonary capillary wedge pressure (PCWP) ≥25 mmHg to atrial shunt or sham procedure. We tested for associations between body mass index (BMI), clinical characteristics, cardiac structural and functional abnormalities, physical limitations, quality of life and outcomes with atrial shunt therapy. Overall, 60.9% of patients had BMI ≥30 kg/m2. As the severity of obesity increased, symptoms (Kansas City Cardiomyopathy Questionnaire score) and 6-min walk distance worsened. More severe obesity was associated with lower natriuretic peptide levels despite more cardiac remodelling, higher cardiac filling pressures, and higher cardiac output. Lower cut points for E/e′ were needed to identify elevated PCWP in more obese patients. Strain measurements in all four chambers were maintained as BMI increased. Pulmonary vascular resistance at rest and exercise decreased with higher BMI. Obesity was associated with more first and recurrent heart failure events. However, there was no significant interaction between obesity and treatment effects of the atrial shunt. Conclusions Increasing severity of obesity was associated with greater cardiac remodelling, higher right and left ventricular filling pressures, higher cardiac output and increased subsequent heart failure events. Despite significant obesity, many HFpEF patients have preserved right heart and pulmonary vascular function and thus, may be appropriate candidates for atrial shunt therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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 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".