Use of multiple micronutrient supplementation integrated into routine antenatal care: A discussion of research priorities
Bibliographic record
Abstract
Optimal maternal nutrition, including adequate intake and status of essential micronutrients, is important for the health of women and developing infants. Currently, the World Health Organization (WHO) Antenatal care recommendations for a positive pregnancy experience recommend daily iron and folic acid (IFA) supplementation as the standard of care. The use of multiple micronutrient supplements (MMS) is recommended in the context of rigorous research as more evidence was needed regarding the impact of switching from IFA supplements to MMS, including evaluation of critical clinical maternal and perinatal outcomes, acceptability, feasibility, sustainability, equity and cost-effectiveness. WHO convened a technical consultation of key stakeholders to discuss research priorities with the objective of providing guidance and clarity to donors, implementers and researchers about this recommendation. The overarching principles of the research agenda include the use of clinical indicators and impact measures that are applicable across studies and settings and the inclusion of outcomes that are important to women. Future studies should consider using standardized protocols based on current best practices to measure critical outcomes such as gestational age (GA) and birthweight (BW) in studies. As GA and BW are influenced by multiple factors, more research is needed to understand the biological impact pathways, and how initiation and considerations for timing of MMS influence these outcomes. A set of core clinical indicators was agreed upon during the technical consultation. For implementation research, the Evidence-to-Decision framework was used as a resource for discussing components of implementation research. The implementation research questions, key indicators and performance measures will depend on country-specific context and bottlenecks that require further research and improved solutions to enable the successful implementation of iron-containing supplements.
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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 | 0.304 | 0.262 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.023 | 0.024 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".