Frailty, body composition and the risk of mortality in incident hemodialysis patients: the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease study
Bibliographic record
Abstract
Background: Frail obese community-dwelling older adults are at increased mortality risk. Among hemodialysis (HD) patients, frailty is common and associated with increased mortality risk; however, in dialysis, obesity is associated with decreased mortality risk. Whether the frail-obese phenotype is associated with increased mortality risk among HD patients remains unclear. Methods: This study included 370 incident HD patients enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study. We measured frailty using the Fried phenotype, general obesity [body mass index (BMI) ≥30 kg/m2] and abdominal obesity [waist:hip ratio (WHR) ≥median WHR] and estimated their associations with mortality. Results: The mean age was 55 years, with 42% female, 73% African American, 57% diabetic and 52% frail. Frail HD patients had higher mean BMI (frail = 30.3 kg/m2, non-frail = 28.3 kg/m2; P = 0.02) and similar WHR (P = 0.8). Twenty-two percent were frail with general obesity and 27% were frail with abdominal obesity. Frailty was associated with 1.66-fold increased mortality risk [95% confidence interval (CI) 1.03-2.67]. BMI was associated with a decreased mortality risk [25.0-29.9 kg/m2 hazard ratio (HR) 0.53 (95% CI 0.31-0.93); ≥30 kg/m2 HR 0.34 (95% CI 0.19-0.62)]. Frailty was associated with elevated mortality risk among HD patients with general [HR 3.77 (95% CI 1.10-12.92)] and abdominal obesity [HR 2.38 (95% CI 1.17-4.82)]. Frailty was not associated with mortality among HD patients without general or abdominal obesity. Conclusions: In adults initiating HD, frailty was associated with elevated mortality risk, even among the obese. Frail-obese HD patients may be a high-risk, often-overlooked population, as obesity is assumed to be protective. Measurement of frailty and obesity may facilitate risk stratification.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".