Partners in Inner‐City Integrated Prenatal Care (PIIPC) Project in Winnipeg, Canada: Effect on Rates of Inadequate Prenatal Care at a Population Level
Bibliographic record
Abstract
while accounting for the potential impacts of underlying maternal psychiatric illness.Methods: Retrospective cohort study of 3,024 women delivering liveborn preterm infants (<37 weeks gestation) between January 2004 and December 2008 at a tertiary teaching hospital in Adelaide, Australia.The primary outcome was postnatal domperidone use, considered a valid proxy for presence and pharmacological management of low milk supply.Relative risks adjusted for maternal sociodemographics and comorbidities (aRRs) were calculated for low milk supply, comparing women with late pregnancy exposure to SRI antidepressants (n = 86), women with a psychiatric illness but no antidepressant use (n=126), and women with neither antenatal exposures (n=2812).Results: Compared to non-exposed women, non-medicated psychiatric illness (aRR 1.67; 95%CI 1.18-2.35)but not late pregnancy SRI use (aRR 0.96; 95%CI 0.54-1.71)was associated with an increased risk of domperidone use, indicative of low milk supply.Conclusions: These findings do not support the previously observed negative impacts of antidepressant use on breastfeeding, instead suggesting that women with an underlying psychiatric illness appear at greatest risk of experiencing low milk supply and could benefit from additional breastfeeding education and support.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".