Maternal and newborn outcomes of antenatal breastmilk expression: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Mothers with diabetes face unique challenges associated with breastfeeding initiation and maintenance. Antenatal breastmilk expression (BME) may be suggested to mothers, including mothers with diabetes, to improve breastfeeding, maternal, and infant outcomes postpartum. However, there have been few evaluations of the potential harms and benefits of this practice. The objective of our scoping review will be to broadly examine the literature describing maternal and infant outcomes of antenatal BME. METHODS AND ANALYSIS: This scoping review will address the research question: 'Among women who engaged in antenatal BME, what maternal and infant outcomes have been evaluated?' A search of published and unpublished studies available in English will be conducted in February 2020 using the following databases: Medline (OVID), Embase (OVID), CINAHL (EBSCOHost), and Cochrane Database of Systematic Reviews (OVID). A search of the British Library E-Theses Online Services (EThOS) database and OpenGrey will be conducted to identify relevant grey literature. This scoping review will use a five-step framework to guide the selection, extraction, and analysis of eligible studies. Clinical consultation will be included as a sixth step to our methodology. Literature reporting on the effect of antenatal BME on maternal and infant outcomes, breastfeeding initiation and duration, and the experiences of women who have engaged in the practice will be considered. The data will be summarised with attention paid to high-risk obstetrical populations such as women with diabetes. Our results will be reported as outlined by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. ETHICS AND DISSEMINATION: Research ethics board approval will not be required due to the nature of the study's methodology. The results of this review will be disseminated through peer-reviewed publication and presentation at relevant conferences. TRAIL REGISTRATION NUMBER: Open Science Framework (osf.io/gfp2q).
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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 | 0.104 | 0.081 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.074 | 0.014 |
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".