Absence of Obesity Paradox in Patients with Chronic Heart Failure and Diabetes Mellitus: A Propensity-Matched Study
Bibliographic record
Abstract
AIMS: Obesity is paradoxically associated with survival benefit in patients with chronic heart failure (HF). However, obesity complicates the management of diabetes mellitus (DM), which is common in HF. Yet, little is known about the impact of obesity in HF patients with DM. Therefore, we examined the association between obesity and outcomes in propensity-matched cohorts of HF patient with and without DM. METHODS AND RESULTS: Of the 7788 participants with chronic mild to moderate HF in the Digitalis Investigation Group trial, 7379 were non-cachectic [body mass index (BMI) ≥ 20 kg/m²] at baseline. Of these, 2153 (29%) had DM, of whom 798 (37%) were obese (BMI ≥ 30 kg/m²). Of the 5226 patients without DM, 1162 (22%) were obese. Propensity scores for obesity were used to separately assemble 636 pairs of obese and non-obese patients with DM and 770 pairs of obese and non-obese patients without DM, who were balanced on 32 baseline characteristics. Among matched patients with DM, all-cause mortality occurred in 38 and 39% of obese and non-obese patients, respectively [hazard ratio (HR) when obesity was compared with no obesity 0.99; 95% confidence interval (CI) 0.80-1.22; P = 0.915]. Among matched patients without DM, all-cause mortality occurred in 23 and 27% obese and non-obese patients, respectively (HR associated with obesity 0.77; 95% CI 0.61-0.97; P = 0.025). CONCLUSION: In patients with chronic mild to moderate HF and DM, obesity confers no paradoxical survival benefit. Whether intentional weight loss may improve outcomes in these patients needs to be investigated in future prospective studies.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".