Antenatal Care Strategies to Improve Perinatal and Newborn Outcomes
Bibliographic record
Abstract
BACKGROUND: Antenatal care strategies (ANC) play a pivotal role in ensuring a healthy gestational period for expectant mothers and promote optimal outcomes for their babies. Implementing these interventions can contribute to a supportive environment for pregnant women, resulting in positive perinatal and neonatal outcomes. SUMMARY: We summarize evidence for a total of twenty-seven interventions pertaining to ANC from Every Newborn Series published in The Lancet 2014 by identifying the most recent systematic reviews, extracting data from each review, and conducting a subgroup analysis for low-income and lower-middle-income countries (LMICs) for outcomes relevant to maternal and neonatal health. Findings from our paper suggest a paucity in evidence from LMICs, and consolidated efforts are required to narrow this gap to build on more inclusive evidence on ANC. KEY MESSAGES: Evidence from LMICs suggests that antenatal multiple micronutrient supplementation when compared to iron and folic acid had a significant effect on stillbirth, small for gestational age, and low birthweight (LBW). Vitamin D supplementation reduced the risks of preterm birth and LBW. High-dose calcium supplementation, when compared to placebo in pregnancy, lowered the likelihood of developing high blood pressure, preeclampsia, and preterm birth. Antihypertensives significantly reduced the probability of developing severe hypertension, proteinuria/preeclampsia, and severe preeclampsia. Metformin for GDM reduced the risk of neonatal death or serious morbidity composite. Cervical cerclage had no effect on stillbirth, preterm birth, or perinatal and neonatal mortality. Data for anti-D administration for rhesus alloimmunization were limited to HICs. BACKGROUND: Antenatal care strategies (ANC) play a pivotal role in ensuring a healthy gestational period for expectant mothers and promote optimal outcomes for their babies. Implementing these interventions can contribute to a supportive environment for pregnant women, resulting in positive perinatal and neonatal outcomes. SUMMARY: We summarize evidence for a total of twenty-seven interventions pertaining to ANC from Every Newborn Series published in The Lancet 2014 by identifying the most recent systematic reviews, extracting data from each review, and conducting a subgroup analysis for low-income and lower-middle-income countries (LMICs) for outcomes relevant to maternal and neonatal health. Findings from our paper suggest a paucity in evidence from LMICs, and consolidated efforts are required to narrow this gap to build on more inclusive evidence on ANC. KEY MESSAGES: Evidence from LMICs suggests that antenatal multiple micronutrient supplementation when compared to iron and folic acid had a significant effect on stillbirth, small for gestational age, and low birthweight (LBW). Vitamin D supplementation reduced the risks of preterm birth and LBW. High-dose calcium supplementation, when compared to placebo in pregnancy, lowered the likelihood of developing high blood pressure, preeclampsia, and preterm birth. Antihypertensives significantly reduced the probability of developing severe hypertension, proteinuria/preeclampsia, and severe preeclampsia. Metformin for GDM reduced the risk of neonatal death or serious morbidity composite. Cervical cerclage had no effect on stillbirth, preterm birth, or perinatal and neonatal mortality. Data for anti-D administration for rhesus alloimmunization were limited to HICs.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".