Echocardiographic epicardial adipose tissue measurements provide information about cardiovascular risk in hemodialysis patients
Bibliographic record
Abstract
Epicardial adipose tissue (EAT) is a cardiovascular risk predictor in general population. However, its value has not been well validated in maintainance hemodialysis (MHD) patients. We aimed to assess associations of EAT with cardiovascular risk predictors in nondiabetic MHD patients. In this cross-sectional study, we measured EAT thickness by transthoracic echocardiography in 50 MHD patients (45.8 ± 14.6 years of age, 37 male). Antropometric measurements, bioimpedance analysis, left ventricular (LV) mass, carotis intima media thickness, blood tests, homeostasis model assessment for insulin resistance (HOMA-IR) and hemodialysis dose by single-pool urea clearence index (spKt/V) were determined. The mean EAT thickness was 3.28 ± 1.04 mm. There were significant associations of EAT with body mass index (β = 0.590, P < 0.001), waist circumference (β = 0.572, P < 0.001), body fat mass (β = 0.562, P < 0.001), percentage of body fat mass (β = 0.408, P = 0.003), percentage of lean tissue mass (β = -0.421, P = 0.002), LV mass (β = 0.426, P = 0.002), carotis intima media thickness (β = 0.289, P = 0.042), triglyceride/high-density lipoprotein cholesterol ratio (β = 0.529, P < 0.001), 1/HOMA-IR (β = -0.386, P = 0.006), and spKt/V (β = -0.311, P = 0.028). No association was exhibited with visfatin C, high-sensitivity C-reactive protein, interleukin-6, and tumor necrosis factor-alpha (for all, P > 0.05). Body mass index, waist circumference, body fat mass, percentage of lean tissue mass, LV mass, triglyceride/high-density lipoprotein cholesterol ratio, HOMA-IR, and spKt/V appeared as independent predictors of EAT. EAT was significantly associated with body fat measures, cardiovascular risk predictors, and dialysis dose in MHD patients.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".