Surrogate markers of visceral adipose tissue in treated <scp>HIV</scp>‐infected patients: accuracy of waist circumference determination
Bibliographic record
Abstract
OBJECTIVES: The accuracy of the use of anthropometrics to quantify visceral adipose tissue (VAT) in treated HIV-infected patients is unknown. We evaluated the predictive accuracy of waist circumference (WC) with and without dual-energy X-ray absorptiometry (DXA)-derived trunk : limb fat ratio [fat mass ratio (FMR)] as surrogates for VAT determined using computerized axial tomography (CT-determined VAT). METHODS: We performed a retrospective cohort analysis of treated HIV-infected male patients followed at the Modena HIV Clinic. We developed prediction equations for VAT using linear regression analysis and Spearman correlations. Receiver operating characteristic (ROC) analysis evaluated the accuracy of WC alone or with FMR at discrete VAT thresholds. RESULTS: The 1500 Caucasian male patients had a median age of 45 years, body mass index (BMI) of 24, WC of 87 cm, VAT area of 127 cm(2) and body fat percentage of 14%. The correlation between WC-predicted VAT and CT-VAT was 0.613, and this increased significantly if FMR was added. The WC-associated R(2) of 0.35 increased to 0.51 if the prediction equation included WC plus FMR. The area under the ROC curve (AUC) using WC was 0.795-0.820 at all VAT thresholds. The positive predictive value (PPV) and negative predictive value (NPV) changed reciprocally at CT-VAT thresholds from 75 to 200 cm(2) and ranged from 0.72 to 0.74, respectively, at a representative VAT of 125 cm(2). Adding the FMR to the predictive equations increased the AUC in the range of 0.854-0.889 with the PPV and NPV increasing minimally, ranging from 0.780 to 0.821. Limits of precision were wide, especially at the highest CT-VAT levels, and varied from 24 to 68 cm(2). CONCLUSIONS: WC is a limited surrogate for CT-VAT in this population and DXA-derived parameters do not improve performance indices to a clinically relevant level. These findings should inform the applicability of WC to predict VAT in treated HIV-infected male patients.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".