Risk factors for spontaneous preterm birth among Aboriginal and non‐Aboriginal women in Manitoba
Bibliographic record
Abstract
In the province of Manitoba, the incidence of preterm birth has been increasing and the rate is higher among Aboriginal than non-Aboriginal women. The purpose of this study was to identify risk factors for spontaneous preterm birth in Manitoba women, and to compare risk factors among Aboriginal and non-Aboriginal women. A case-control study was performed at two tertiary care hospitals in Winnipeg, Manitoba, Canada from October 1999 to December 2000. Cases delivered a live singleton infant at < 37 weeks gestation (n = 226; 36% Aboriginal), while controls delivered between 37 and 42 weeks gestation (n = 458; 38% Aboriginal). An interview was conducted with each subject on the postpartum unit, and information was collected from the health record. Using stratified analyses to control for race/ethnicity, several risk factors for preterm birth had a uniform effect measure across strata, while others demonstrated heterogeneity. After adjusting for other maternal characteristics in a multivariable logistic regression model, significant risk factors for all women included previous preterm birth, two or more previous spontaneous abortions, vaginal bleeding after 12 weeks gestation, gestational hypertension, antenatal hospitalisation, and prelabour rupture of membranes. In addition, potentially modifiable risk factors included low weight gain during pregnancy and inadequate prenatal care for all women, and high levels of perceived stress for Aboriginal women. These modifiable risk factors lend themselves to public health interventions, and should be targeted in future prevention efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".