Body mass index and early <scp>CD</scp>4 <scp>T</scp>‐cell recovery among adults initiating antiretroviral therapy in <scp>N</scp>orth <scp>A</scp>merica, 1998–2010
Bibliographic record
Abstract
OBJECTIVES: Adipose tissue affects several aspects of the cellular immune system, but prior epidemiological studies have differed on whether a higher body mass index (BMI) promotes CD4 T-cell recovery on antiretroviral therapy (ART). The objective of this analysis was to assess the relationship between BMI at ART initiation and early changes in CD4 T-cell count. METHODS: We used the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) data set to analyse the relationship between pre-treatment BMI and 12-month CD4 T-cell recovery among adults who started ART between 1998 and 2010 and maintained HIV-1 RNA levels < 400 copies/mL for at least 6 months. Multivariable regression models were adjusted for age, race, sex, baseline CD4 count and HIV RNA level, year of ART initiation, ART regimen and clinical site. RESULTS: A total of 8381 participants from 13 cohorts contributed data; 85% were male, 52% were nonwhite, 32% were overweight (BMI 25-29.9 kg/m(2) ) and 15% were obese (BMI > 30 kg/m(2) ). Pretreatment BMI was associated with 12-month CD4 T-cell change (P < 0.001), but the relationship was nonlinear (P < 0.001). Compared with a reference of 22 kg/m(2) , a BMI of 30 kg/m(2) was associated with a 36 cells/μL [95% confidence interval (CI) 14, 59 cells/μL] greater CD4 T-cell count recovery among women and a 19 cells/μL (95% CI 9, 30 cells/μL) greater recovery among men at 12 months. At a BMI > 30 kg/m(2) , the observed benefit was attenuated among men to a greater degree than among women, although this difference was not statistically significant. CONCLUSIONS: A BMI of approximately 30 kg/m(2) at ART initiation was associated with greater CD4 T-cell recovery at 12 months compared with higher or lower BMI values, suggesting that body composition may affect peripheral CD4 T-cell recovery.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".