Relationship Between the Bertin Index to Estimate Visceral Adipose Tissue From Dual‐Energy X‐Ray Absorptiometry and Cardiometabolic Risk Factors Before and After Weight Loss
Bibliographic record
Abstract
The purpose of this study was to investigate the relationship between visceral adipose tissue (VAT), estimated with the Bertin index obtained from dual-energy X-ray absorptiometry (DXA), with cardiometabolic risk factors before and after a weight loss program and compare it with VAT measured with computed tomography (CT) scan. The study population for this analysis included 92 nondiabetic overweight and obese sedentary postmenopausal women (age: 58.1 ± 4.7 years, BMI: 31.8 ± 4.2 kg/m(2)) participating in a weight loss intervention that consisted of a caloric restricted diet with and without resistance training (RT). We measured (i) VAT using CT scan, (ii) body composition (using DXA) from which the Bertin index was calculated, (iii) cardiometabolic risk factors such as insulin sensitivity (using the hyperinsulinenic-euglycemic clamp technique), peak oxygen consumption, blood pressure, plasma lipids, C-reactive protein as well as fasting glucose and insulin. VAT levels for both methods significantly decreased after the weight loss intervention. Furthermore, no differences in VAT levels between both methods were observed before (88.0 ± 25.5 vs. 83.8 ± 22.0 cm(2)) and after (76.8 ± 27.8 vs. 73.6 ± 23.2 cm(2)) the weight loss intervention. In addition, the percent change in VAT levels after the weight loss intervention was similar between both methods (-13.0 ± 16.5 vs. -12.5 ± 12.6%). Moreover, similar relationships were observed between both measures of VAT with cardiometabolic risk factors before and after the weight loss intervention. Finally, results from the logistic regression analysis consistently showed that fat mass and lean body mass were independent predictors of pre- and post-VAT levels for both methods in our cohort. In conclusion, estimated visceral fat levels using the Bertin index may be able to trace variations of VAT after weight loss. This index also shows comparable relationships with cardiometabolic risk factors when compared to VAT measured using CT scan.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".