Evidence synthesis evaluating body weight gain among people treating HIV with antiretroviral therapy - a systematic literature review and network meta-analysis
Bibliographic record
Abstract
Background: This systematic review aimed to compare body weight gain associated outcomes over time between dolutegravir (DTG)-based antiretroviral (ART) regimens to other ART regimens, to compare tenofovir alafenamide (TAF)-based regimens, and to evaluate the associated prognostic factors. Methods: Systematic searches of MEDLINE, Embase, and CENTRAL for RCTs and observational studies comparing ART regimens were conducted on 13 September 2021. Outcomes of interest included: change in body weight, body mass index (BMI), waist circumference; and risk of hyperglycaemia and diabetes. Network meta-analyses were conducted at 12, 24, 48, 96 and 144 weeks using two networks differentiated by 3rd agents and backbone agents. Findings: The review identified 113 publications reporting on 73 studies. DTG-based regimens led to statistically higher weight gains than efavirenz-based regimens at all time points (mean difference: 1·99 kg at 96 weeks; 95% credible interval: 0·85-3·09) and was higher over time than low-dose efavirenz-, elvitegravir-, and rilpivirine-based regimens. They were comparable to raltegravir-, bictegravir- and atazanavir-based regimens. For backbones, TAF led to higher weight gain relative to tenofovir disoproxil fumarate (TDF), abacavir, and zidovudine. Prognostic factor analysis showed both low CD4 cell count and high HIV RNA viral load at baseline were consistently associated with higher weight gain, while sex was an effect modifier to African origins. Interpretation: DTG-based regimens lead to larger average weight gains than some other ART regimens and TAF leads to larger average weight gains than all other backbone antiretrovirals. Further research is needed to better understand long-term outcomes and their relationship to other metabolic outcomes. Funding: The WHO Global HIV, Hepatitis and Sexually Transmitted Infections Programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".