Epicardial adipose tissue predicts mortality in incident hemodialysis patients: a substudy of the Renagel in New Dialysis trial
Bibliographic record
Abstract
BACKGROUND: Epicardial adipose tissue (EAT) has been described in the general population as an independent risk marker for incident coronary artery disease. In hemodialysis patients, it correlates with other markers of cardiovascular disease, but it is unknown if it is associated with adverse events. METHODS: post hoc analysis of the Renagel in New Dialysis (RIND) patients study, a randomized trial of sevelamer versus calcium-based phosphate binders in 109 incident hemodialysis patients, followed for all-cause mortality for a median of 49.3 months. Patients underwent baseline cardiac computed tomography imaging within 120 days of dialysis initiation. RESULTS: Baseline EAT measurements were available in 95 patients; EAT was positively correlated with age, body mass index, triglycerides, C-reactive protein, coronary artery calcium and aortic calcium, and negatively correlated with systolic and diastolic blood pressure, serum high density lipoprotein (HPL) cholesterol and serum phosphate (all P < 0.05). During follow-up, a total of 27 (28.4%) patients expired [mortality per 1000 patients/year: 95% confidence interval (95% CI) = 77 (64-94)]. Five-year survival rate was 44. 6% (95% CI: 21.1-65.7) and 71.2% (95% CI: 45.95-86.25) in patients with EAT above or below the median, respectively. Each 10 cc increase in EAT volume was associated with a significant 6% increase in the risk of death during follow-up [hazard ratio (HR): 1.060; 95% CI: 1.013-1.109; P-value = 0.012]. CONCLUSIONS: In this subanalysis of a randomized trial, EAT was an independent predictor of mortality in incident hemodialysis patients after ~4 years of follow-up. These hypothesis-generating findings will need confirmatory evidence.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".