Contribution of HIV to Maternal Morbidity Among Refugee Women in Canada
Bibliographic record
Abstract
OBJECTIVES: We compared severe maternal morbidity (SMM) and SMM subtypes, including HIV, of refugee women with those of nonrefugee immigrant and nonimmigrant women. METHODS: We linked 1,154,421 Ontario hospital deliveries (2002-2011) to immigration records (1985-2010) to determine the incidence of an SMM composite indicator and its subtypes. We determined SMM incidence according to immigration periods, which were characterized by lifting restrictions for all HIV-positive immigrants (in 1991) and refugees who may place "excessive demand" on government services (in 2002). RESULTS: Refugees had a higher risk of SMM (17.1 per 1000 deliveries) than did immigrants (12.1 per 1000) and nonimmigrants (12.4 per 1000). Among SMM subtypes, refugees had a much higher risk of HIV than did immigrants (risk ratio [RR] = 7.94; 95% confidence interval [CI] = 5.64, 11.18) and nonimmigrants (RR = 17.37; 95% CI = 12.83, 23.53). SMM disparities were greatest after the 2002 policy came into effect. After exclusion of HIV cases, SMM disparities disappeared. CONCLUSIONS: An apparent higher risk of SMM among refugee women in Ontario, Canada is explained by their high prevalence of HIV, which increased over time parallel to admission policy changes favoring humanitarian protection.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".