Association of Abdominal Adiposity with Cardiovascular Mortality in Incident Hemodialysis
Bibliographic record
Abstract
BACKGROUND: The risk of cardiovascular mortality is high among adults with end-stage renal disease (ESRD) undergoing hemodialysis. Waist-to-hip ratio (WHR), a metric of abdominal adiposity, is a predictor of cardiovascular disease (CVD) and mortality in the general population; however, no studies have examined the association with CVD mortality, particularly sudden cardiac death (SCD), in incident hemodialysis. METHODS: Among 379 participants incident (< 6 months) to hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in ESRD study, we evaluated associations between WHR and risk of CVD mortality, SCD, and non-CVD mortality in Cox proportional hazards regression models. RESULTS: At study enrollment, mean age was 55 years with 41% females, 73% African Americans, and 57% diabetics. Mean body mass index was 29.3 kg/m2, and mean WHR was 0.95. During a median follow-up time of 2.5 years, there were 35 CVD deaths, 15 SCDs, and 48 non-CVD deaths. Every 0.1 increase in WHR was associated with higher risk (hazard ratio [95% CI]) of CVD mortality (1.75 [1.06-2.86]) and SCD (2.45 [1.20-5.02]), but not non-CVD mortality (0.93 [0.59-1.45]), independently of demographics, body mass index, comorbidities, inflammation, and traditional CVD risk factors. CONCLUSIONS: WHR is significantly associated with CVD mortality including SCD, independently of other CVD risk factors in incident hemodialysis. This simple, easily obtained bedside metric may be useful in dialysis patients for CVD 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".