Human Papillomavirus Infection Among Pregnant Women Living With HIV: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: In the general population, human papillomavirus (HPV) prevalence is reportedly increased during pregnancy, and emerging evidence suggests that it may be associated with adverse pregnancy outcomes. Women living with HIV (WLWH) experience higher rates of both HPV infection and certain adverse pregnancy outcomes, yet there are no prior reviews of HPV infection during pregnancy in WLWH. METHODS: We conducted a systematic review and meta-analysis of pooled and type-specific HPV prevalence and associated pregnancy outcomes among pregnant WLWH and, if available, within-study comparators of women without HIV. Subgroup analyses were performed according to polymerase chain reaction primers used and geographic location. RESULTS: Ten studies describing HPV prevalence in 1594 pregnant WLWH were included. The pooled HPV prevalence in pregnant WLWH was 75.5% (95% confidence interval: 50.2 to 90.4) but ranged widely (23%-98%) between individual studies. Among studies that also assessed HPV prevalence in pregnant women without HIV, the pooled prevalence was lower at 48.1% (95% confidence interval: 27.1 to 69.8). Pregnant WLWH had 54% higher odds of being HPV positive compared with pregnant women without HIV. The most common HPV type detected in pregnant WLWH was HPV16. No studies reported pregnancy outcomes by the HPV status. CONCLUSIONS: High prevalence of HPV was documented in pregnant WLWH, exceeding the prevalence among pregnant women without HIV. The limited research on this topic must be addressed with further studies to inform the use of HPV testing as a screening modality for this population as well as the role of HPV in adverse pregnancy outcomes.
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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".