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Record W4406664926 · doi:10.1159/000543384

Near-Term and Intrapartum Care of Mothers for Perinatal and Newborn Outcomes

2025· review· en· W4406664926 on OpenAlexaff
Rahima Yasin, Maha Azhar, Hamna Amir Naseem, Ayesha Arshad Ali, Jai K Das, Zulfiqar A Bhutta

Bibliographic record

VenueNeonatology · 2025
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsHospital for Sick Children
FundersBill and Melinda Gates Foundation
KeywordsMedicineMeconium aspiration syndromeObstetricsChildbirthPsychological interventionChorioamnionitisChecklistPregnancyRespiratory distressMeconiumPneumoniaPediatricsIntensive care medicineGestational ageFetusNursingAnesthesia

Abstract

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INTRODUCTION: Near-term and intrapartum care play pivotal roles in ensuring a safe childbirth experience and are essential components of a comprehensive approach to maternal and neonatal health. METHODS: The following interventions were identified: antibiotics for preterm premature rupture of membrane, antenatal corticosteroids for fetal lung maturation, partograph use during labor and delivery, induction of labor at or post-term, skilled birth care and safe childbirth checklist during labor and delivery. A scoping exercise was conducted to ascertain the most up-to-date evidence, and reviews of topics of interest were updated in case the evidence was not recent, with a focus on low- and middle-income countries (LMICs). RESULTS: Antibiotics reduced the overall risk of neonatal infection including pneumonia (RR 0.67 [0.52 to 0.85]). LMIC evidence showed a significant effect of antenatal steroids on the risk of neonatal mortality (RR 0.64 [0.43 to 0.97]) and respiratory distress syndrome (RR 0.65 [0.44 to 0.96]). Induction of labor practices at term or post-term reduced the risk of meconium aspiration syndrome (RR 0.51 [0.34 to 0.76]). The use of the WHO childbirth checklist significantly raised the standard of preeclampsia care (OR 8.09 [2.55 to 25.63]) as well as of maternal infection management (OR 25.44 [4.09 to 158.08]). LMIC-specific evidence also demonstrated a significant reduction in the risk of stillbirth (OR 0.92 [0.87 to 0.96]). CONCLUSION: Further research initiatives pertaining to health interventions delivered to expectant mothers near-term or during the intrapartum period can contribute to a more inclusive understanding of health challenges in LMICs. INTRODUCTION: Near-term and intrapartum care play pivotal roles in ensuring a safe childbirth experience and are essential components of a comprehensive approach to maternal and neonatal health. METHODS: The following interventions were identified: antibiotics for preterm premature rupture of membrane, antenatal corticosteroids for fetal lung maturation, partograph use during labor and delivery, induction of labor at or post-term, skilled birth care and safe childbirth checklist during labor and delivery. A scoping exercise was conducted to ascertain the most up-to-date evidence, and reviews of topics of interest were updated in case the evidence was not recent, with a focus on low- and middle-income countries (LMICs). RESULTS: Antibiotics reduced the overall risk of neonatal infection including pneumonia (RR 0.67 [0.52 to 0.85]). LMIC evidence showed a significant effect of antenatal steroids on the risk of neonatal mortality (RR 0.64 [0.43 to 0.97]) and respiratory distress syndrome (RR 0.65 [0.44 to 0.96]). Induction of labor practices at term or post-term reduced the risk of meconium aspiration syndrome (RR 0.51 [0.34 to 0.76]). The use of the WHO childbirth checklist significantly raised the standard of preeclampsia care (OR 8.09 [2.55 to 25.63]) as well as of maternal infection management (OR 25.44 [4.09 to 158.08]). LMIC-specific evidence also demonstrated a significant reduction in the risk of stillbirth (OR 0.92 [0.87 to 0.96]). CONCLUSION: Further research initiatives pertaining to health interventions delivered to expectant mothers near-term or during the intrapartum period can contribute to a more inclusive understanding of health challenges in LMICs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.551

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.352
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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