Weight Loss Associated with Semaglutide Treatment Among People with HIV
Bibliographic record
Abstract
Purpose There is limited real-world evidence about the effectiveness of semaglutide for weight loss among people with HIV (PWH). We aimed to investigate weight change in a US cohort of PWH who initiated semaglutide treatment. Methods We conducted an observational study using data from the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort. We identified adult PWH who initiated semaglutide between 2018 and 2022 and with ≥2 weight measurements. The primary outcome was within-person bodyweight change (kg/year). The secondary outcome was within-person Hemoglobin A1c percent (HbA1c) change per year. Both outcomes were estimated using multivariable linear mixed model. Results In total, 222 new users of semaglutide met inclusion criteria. Mean follow up was 1.1 years. Approximately 75% of new semaglutide users were male, and at baseline, mean age was 53 years (standard deviation [SD]: 10), average weight was 108 kg (SD: 23), mean body mass index was 35.5 kg/m 2, mean HbA1c was 7.7% and 77% had clinically recognized diabetes. At baseline, 97% were on ART and 89% were virally suppressed (VL < 50 copies/mL). In the adjusted mixed model analysis, treatment with semaglutide was associated with significant weight loss of 6.47 kg per 1 year (95% CI: -7.67 to -5.18) and with a reduction in HbA1c of 1.07% per 1 year (95% CI -1.64 to -0.50) among the 157 PWH with a post-index HbA1c value. Conclusions Semaglutide was associated with significant weight loss and HbA1c reduction among PWH, comparable to results of previous studies from the general population.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".