Prevalence of post-acute sequelae of SARS-CoV-2 infection in people living with HIV: a systematic review with meta-analysis
Bibliographic record
Abstract
Background Given the chronic immune activation and inflammatory milieu associated with Long COVID and HIV, we assessed the prevalence of Long COVID in adults living with HIV; and investigated whether adults living with HIV were associated with increased chance of developing Long COVID compared to adults living without HIV Methods In this systematic review and meta-analysis, we searched Medline, EMBASE, CINHAL, PubMed and CENTRAL from inception until June 14th, 2024, for observational studies that measured the prevalence of Long COVID in adults living with HIV and the odds of developing Long COVID following a SARS-CoV-2 infection in people living with HIV compared to people living without HIV. Reviews, case reports, randomised control trials and editorials were excluded. The search was conducted without language restrictions. We performed meta-analysis of proportions to synthesise prevalence estimates using logit transformation and a sensitivity analysis using mixed-effects logistic regression. We used random-effects meta-analyses to summarize the odds ratio (OR) of developing Long COVID in adults living with HIV compared to adults living without HIV and conducted a sensitivity analysis including only studies with covariate-adjusted estimates that was planned a-priori. We used ROBINS-E for the risk of bias assessment and GRADE to rate the certainty of evidence. We identified statistical heterogeneity using Cochran's Q test and quantified it using the I 2 statistic. For the Q test, a P < 0.10 was considered statistically significant. PROSPERO registration: CRD42024577616. Findings Our search returned 831 results, of which 8 studies (4489 participants) were deemed eligible for inclusion in the systematic review and meta-analysis. The prevalence of Long COVID in adults with HIV was 43% (95% CI: 32–54%, 8 studies; 1227 participants; low certainty, P < 0.0001). The association of HIV status with Long COVID was inconclusive, with wide confidence intervals (OR: 1.16, 95% CI: 0.58–2.29; 4 studies; 3556 participants, low certainty, P = 0.013). When the analysis was restricted to studies reporting covariate-adjusted estimates, adults living with HIV were associated with a higher odds of Long COVID than those not living with HIV (OR: 2.21, 95% CI: 1.12–4.36; 2 studies; 374 participants, low certainty, P = 0.51). Interpretation Current evidence indicates that the prevalence of Long COVID in adults living with HIV may be high, suggesting the need for increased awareness and education of healthcare providers and policy makers. Evidence on whether HIV positivity increases the risk of Long COVID is limited and inconclusive, highlighting a need for further research to clarify this potential association. Funding None.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.022 | 0.004 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".