Quantification of epicardial fat using non contrast cardiac CT in an HIV population: Reproducibility and association with other body fat indices
Bibliographic record
Abstract
PURPOSE: To assess the reproducibility of different epicardial fat measurement and their association with other adiposity measurements in HIV-infected and non-HIV-infected patients. METHODS AND MATERIALS: In this cross-sectional study, 167 HIV-infected and 58 non-HIV-infected consecutive participants (200 males; mean age 56 years) with low/intermediate cardiovascular risk were recruited between 2012 and 2017 from a large prospective cohort and underwent non-contrast cardiac CT. Two independent observers measured epicardial fat volume, area and thickness in all participants. For intra-observer agreement, one observer did a second assessment in a subset of 40 patients. Agreement was assessed with the intraclass correlation coefficient (ICC). Pearson's correlation was estimated to assess the association between epicardial fat, body-mass index (BMI) and dual-energy x-ray absorptiometry (DEXA) derived percentage of body fat. RESULTS: Inter-observer agreement was excellent for epicardial fat volume (ICC 0.75) and area (ICC 0.95) and good for epicardial fat thickness (ICC near the left anterior descending artery (LAD) 0.64, ICC near right coronary artery (RCA) 0.64). Intra-observer agreement was excellent for epicardial fat volume (ICC 0.97), area (ICC 0.99), thickness at LAD (ICC 0.71) and good for epicardial fat thickness at RCA (ICC 0.68). Epicardial fat volume had a better correlation to total body fat (r = 0.28, p < 0.001) and trunk fat (r = 0.37, p < 0.001), in comparison to other epicardial fat indices. CONCLUSION: Assessment of epicardial fat volume is highly reproducible in both HIV-infected and non-HIV-infected patients and shows a superior correlation with DEXA-based body and trunk fat measurements. Epicardial fat volume should be considered over other CT assessment methods when quantifying epicardial fat in HIV 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".