Increasing Number and Proportion of Adverse Obstetrical Outcomes among Women Living with HIV in the Ottawa Area: A 20-Year Clinical Case Series
Bibliographic record
Abstract
Background. The prevalence and associated risks with adverse obstetrical outcomes among women living with HIV are not well measured. The objective of this study was to longitudinally investigate the prevalence and correlates of adverse obstetrical outcomes among women with HIV. Methods. This 20-year (1990-2010) clinical case series assessed the prevalence of adverse obstetrical outcomes among pregnant women with HIV receiving care at The Ottawa Hospital (TOH). General estimating equation modeling was used to identify factors independently associated with adverse obstetrical outcomes, while controlling for year of childbirth clustering. Results. At TOH, there were 127 deliveries among 94 women (1990-2010): 22 preterm births, 9 births with low birth weight, 12 births small for gestational age, and 4 stillbirths. Per year, the odds of adverse obstetrical outcomes increased by 15% (OR: 1.15, 95% CI: 1.03-1.30). Psychiatric illness (AOR: 2.64, 95% CI: 1.12-6.24), teen pregnancy (AOR: 3.35, 95% CI: 1.04-1.46), and recent immigrant status (AOR: 7.24, 95% CI: 1.30-40.28) were the strongest correlates of adverse obstetrical outcomes. Conclusions. The increasing number and proportion of adverse obstetrical outcomes among pregnant women with HIV over the past 20 years highlight the need for social supports and maternal and child health interventions, especially among adolescents, new immigrants, and those with a history of mental illness.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".