Pregnancy incidence and intention after HIV diagnosis among women living with HIV in Canada
Bibliographic record
Abstract
BACKGROUND: Pregnancy incidence rates among women living with HIV (WLWH) have increased over time due to longer life expectancy, improved health status, and improved access to and HIV prevention benefits of combination antiretroviral therapy (cART). However, it is unclear whether intended or unintended pregnancies are contributing to observed increases. METHODS: We analyzed retrospective data from the Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS). Kaplan-Meier methods and GEE Poisson models were used to measure cumulative incidence and incidence rate of pregnancy after HIV diagnosis overall, and by pregnancy intention. We used multivariable logistic regression models to examine independent correlates of unintended pregnancy among the most recent/current pregnancy. RESULTS: Of 1,165 WLWH included in this analysis, 278 (23.9%) women reported 492 pregnancies after HIV diagnosis, 60.8% of which were unintended. Unintended pregnancy incidence (24.6 per 1,000 Women-Years (WYs); 95% CI: 21.0, 28.7) was higher than intended pregnancy incidence (16.6 per 1,000 WYs; 95% CI: 13.8, 20.1) (Rate Ratio: 1.5, 95% CI: 1.2-1.8). Pregnancy incidence among WLWH who initiated cART before or during pregnancy (29.1 per 1000 WYs with 95% CI: 25.1, 33.8) was higher than among WLWH not on cART during pregnancy (11.9 per 1000 WYs; 95% CI: 9.5, 14.9) (Rate Ratio: 2.4, 95% CI: 2.0-3.0). Women with current or recent unintended pregnancy (vs. intended pregnancy) had higher adjusted odds of being single (AOR: 1.94; 95% CI: 1.10, 3.42), younger at time of conception (AOR: 0.95 per year increase, 95% CI: 0.90, 0.99), and being born in Canada (AOR: 2.76, 95% CI: 1.55, 4.92). CONCLUSION: Nearly one-quarter of women reported pregnancy after HIV diagnosis, with 61% of all pregnancies reported as unintended. Integrated HIV and reproductive health care programming is required to better support WLWH to optimize pregnancy planning and outcomes and to prevent unintended pregnancy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".