Comparison of Body Composition Assessment Methods in Patients with Human Immunodeficiency Virus-Associated Wasting Receiving Growth Hormone
Bibliographic record
Abstract
CONTEXT: Bioelectrical impedance spectroscopy (BIS) and skinfold anthropometry (SKF) have been used to monitor body composition among patients with HIV wasting; however, validation of these techniques during recombinant human GH (rhGH) treatment has not been performed. OBJECTIVE: Our objective was to evaluate the degree of agreement between criterion measurements of dual-energy x-ray absorptiometry (DXA) and those of BIS and SKF in patients with HIV wasting treated with rhGH. DESIGN AND SETTING: We conducted a randomized, double-blinded, placebo-controlled, two-period crossover trial at the University of Toronto and Mount Sinai Hospital (Toronto, Canada). PATIENTS: A referred sample of 27 community-dwelling men with HIV-associated weight loss (> or =10% over preceding 12 months) despite optimal antiretroviral therapy participated in the study. INTERVENTION: Intervention was one daily injection of rhGH (6 mg) or placebo self-administered for 3 months in a crossover fashion with a 3-month washout. MAIN OUTCOME MEASURES: Fat-free mass (FFM) and fat mass (FM) were measured by BIS, SKF, and DXA before and after rhGH and placebo treatment. RESULTS: FFM(BIS) was not significantly different from FFM(DXA) after rhGH treatment (P = 0.10). Mean differences (bias +/- sd) according to Bland-Altman analysis were smaller for SKF than for BIS (P < 0.05) at all time points, yet treatment-induced change in FM was better detected with BIS than with SKF. BIS estimates of FFM and FM showed better agreement with those of DXA after rhGH treatment (1.6 +/- 4.6 kg and -2.1 +/- 3.9 kg) compared with baseline (3.8 +/- 3.5 kg and -4.1 +/- 3.6 kg) and placebo (2.7 +/- 4.4 kg and -3.1 +/- 4.6) (P < 0.05). BIS overestimated and SKF underestimated the treatment-induced changes in FFM and FM. CONCLUSIONS: SKF was more accurate than BIS when measuring body composition in patients with HIV wasting before and after rhGH treatment; nonetheless, the accuracy of BIS increased after treatment. Change in FM because of treatment was not accurately assessed with SKF.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".