Postpartum domperidone use in British Columbia: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Domperidone is commonly used off-label to stimulate milk production in mothers who have low milk supply. The aim of this study was to describe trends, patterns and determinants of postpartum domperidone use. METHODS: This is a retrospective, population-based study involving all women with a live birth between Jan. 1, 2002, and Dec. 31, 2011, in the province of British Columbia. We examined administrative data sets containing person-specific information on filled prescriptions and use of medical services, and we used logistic regression to examine associations between domperidone use and maternal characteristics. RESULTS: The study population consisted of 225 532 women with 320 351 live births. The prevalence of postpartum domperidone use more than doubled between 2002 and 2011. In 2011, 1 in 3 women with a preterm birth and 1 in 5 women with a full-term birth were prescribed domperidone in the first 6 months postpartum. Women who were older, had a higher body mass index, had a chronic disease, were first-time mothers, delivered more than 1 baby (multiple pregnancy), had a preterm birth or had a cesarian delivery were more likely to fill a postpartum domperidone prescription. INTERPRETATION: We found an increase in postpartum domperidone use over a 10-year period. More research is needed on maternal and infant health outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".