Obesity and renal impairment in patients with heart failure and reduced ejection fraction: another obesity paradox?
Bibliographic record
Abstract
Abstract Background Obesity is associated with poor cardiovascular outcomes in patients with HF and reduced ejection fraction (HFrEF). However, whether obesity is associated with worse kidney outcomes in HFrEF has not been evaluated. Purpose To estimate the association between obesity and change in estimated glomerular filtration rate (eGFR) over time in patients with HFrEF. Methods In this post hoc analysis of the PARADIGM-HF trial, body mass index (BMI) and eGFR was collected in 8,389 patients. Change in eGFR over time was assessed according to baseline BMI (normal weight: BMI <25.0, overweight: BMI 25-29.9, and obesity: BMI ≥30). Results The number of patients in each BMI category was: 2,421 (BMI <25.0), 3,249 (BMI 25-29.9), and 2,719 (BMI ≥30), respectively. Patients with obesity were younger but had worse health status (worse NYHA class and KCCQ scores) and had more comorbidities including diabetes mellitus and hypertension. At baseline, eGFR was lower in patients who were overweight (BMI 25-29.9) and obese (BMI ≥30), compared to those with normal weight. Urine albumin-creatinine ratio (UACR) and kidney injury molecule-1 (KIM-1) were also higher in patients with obesity. However, the rate of change in eGFR per year (eGFR "slope") in the overall cohort did not differ according to BMI: change in eGFR per year was -1.8 [-2.1, -1.6] mL/min/1.73m2 for the normal weight category, -1.6 [-1.8, -1.3] mL/min/1.73m2 for those who were overweight, and -1.5 [-1.8, -1.3] mL/min/1.73m2 for those with obesity; P=0.21) (Figure 1). Among those without diabetes at baseline, those who were obese had a significantly less steep eGFR slope compared to patients in the other BMI categories. In those with diabetes at baseline, the eGFR slope was steeper than in patients without diabetes but was similar across all three BMI categories (Figure 2). Conclusions Although baseline kidney function was more impaired in HFrEF patients with obesity, high BMI was not associated with a more rapid subsequent rate of decline in eGFR. Figure 1. eGFR slope over time according to BMI at baseline in patients with HFrEF in PARADIGM-HF Figure 2. eGFR slope over time according to BMI at baseline in patients with HFrEF in PARADIGM-HF with and without diabetes at baselineFigure 1Figure 2-A and 2-B
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".