Is there sufficient evidence for a causal association between antiretroviral therapy and diabetes in HIV‐infected patients? A meta‐analysis
Bibliographic record
Abstract
The association of antiretroviral therapy (ART) with diabetes is inconsistent and varies widely across primary epidemiological studies. A comprehensive and more precise estimate of this association is fundamental to establishing a plausible causal link between ART and diabetes. We identified epidemiological studies that compared mean fasting plasma glucose (FPG) concentrations and proportions of diabetes and metabolic syndrome between HIV-infected patients naïve and exposed to ART. Mean difference in FPG concentrations and odds ratios of diabetes and metabolic syndrome were pooled using random-effects meta-analyses. Data on 20 178 participants from 41 observational studies were included in the meta-analyses. Mean FPG concentrations (Pooled mean difference: 4.66 mg/dL; 95% confidence interval [CI], 2.52 to 6.80; 24 studies) and the odds of diabetes (Pooled odds ratios: 3.85; 95% CI, 2.93 to 5.07; 10 studies) and metabolic syndrome (Pooled odds ratios: 1.45; 95% CI, 1.03 to 2.03; 18 studies) were significantly higher among ART-exposed patients, compared to their naïve counterparts. ART was also associated with significant increases in FPG levels in studies with mean ART duration ≥18 months (Pooled mean difference: 4.97 mg/dL; 95% CI, 3.10 to 6.84; 14 studies), but not in studies with mean ART duration <18 months (Pooled mean difference: 4.40 mg/dL, 95% CI, -0.59 to 9.38; 7 studies). ART may potentially be the single most consistent determinant of diabetes in people living with HIV worldwide. However, given the preponderance of cross-sectional studies in the meta-analysis, the association between ART and diabetes cannot be interpreted as cause and effect.
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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 | 0.022 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.058 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".