Study protocol: a double blind placebo controlled trial examining the effect of domperidone on the composition of breast milk [NCT00308334]
Bibliographic record
Abstract
BACKGROUND: Domperidone, a drug that enhances upper gastric motility, is an anti-dopaminergic medication that also elevates prolactin levels. It has been shown to safely increase the milk supply of lactating women. To date, researchers have analyzed the effects of domperidone on lactating woman with respect to the quantity of their milk production, adverse effects, and drug levels in the breast milk. However, the effect of domperidone on the macronutrient composition of breast milk has not been studied and current guidelines for fortification of human milk for premature infants do not distinguish between those women using or those not using domperidone. The purpose of this study is to evaluate the effect of domperidone (given to lactating mothers of very preterm infants) on the macronutrient composition of breast milk. METHODS/DESIGN: Mothers of infants delivered at less than 31 weeks gestation, who are at least 3 weeks postpartum, and experiencing lactational failure despite non-pharmacological interventions, will be randomized to receive domperidone (10 mg three times daily) or placebo for a 14-day period. Breast milk samples will be obtained the day prior to beginning treatment and on days 4, 7 and 14. The macronutrient (protein, fat, carbohydrate and energy) and macromineral content (calcium, phosphorus and sodium) will be analyzed and compared between the two groups. Additional outcome measures will include milk volumes, serum prolactin levels (measured on days 0, 4, and 10), daily infant weights and breastfeeding rates at 2 weeks post study completion and at discharge. Forty-four participants will be recruited into the study. Analysis will be carried out using the intention to treat approach. DISCUSSION: If domperidone causes significant changes to the nutrient content of breast milk, an alteration in feeding practices for preterm infants may need to be made in order to optimize growth, nutrition and neurodevelopment 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".