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Record W4391635319 · doi:10.1002/ijgo.15407

Adverse neonatal outcomes in pregnant women with asthma: An updated systematic review and meta‐analysis

2024· review· en· W4391635319 on OpenAlexaboutno aff
Annelies L. Robijn, Soriah Harvey, Megan E. Jensen, Samuel Atkins, Kiah J. D. Quek, Gang Wang, H. Jeff Smith, Christina Chambers, Jennifer A. Namazy, Michael Schätz, Peter G. Gibson, Vanessa E. Murphy

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2024
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsnot available
FundersMedical Research Future Fund
KeywordsMedicineAsthmaMeta-analysisPediatricsPregnancyObstetricsNeonatal deathSystematic reviewMEDLINEFetusInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: A systematic review and meta-analysis from 2013 reported increased risks of congenital malformations, neonatal death and neonatal hospitalization amongst infants born to women with asthma compared to infants born to mothers without asthma. OBJECTIVE: Our objective was to update the evidence on the associations between maternal asthma and adverse neonatal outcomes. SEARCH STRATEGY: We performed an English-language MEDLINE, Embase, CINAHL, and COCHRANE search with the terms (asthma or wheeze) and (pregnan* or perinat* or obstet*). SELECTION CRITERIA: Studies published from March 2012 until September 2023 reporting at least one outcome of interest (congenital malformations, stillbirth, neonatal death, perinatal mortality, neonatal hospitalization, transient tachypnea of the newborn, respiratory distress syndrome and neonatal sepsis) in a population of women with and without asthma. DATA COLLECTION AND ANALYSIS: The study was reported following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Quality of individual studies was assessed by two reviewers independently using the Newcastle-Ottawa Scale. Random effects models (≥3 studies) or fixed effect models (≤2 studies) were used with restricted maximum likelihood to calculate relative risk (RR) from prevalence data and the inverse generic variance method where adjusted odds ratios (aORs) from individual studies were combined. MAIN RESULTS: A total of 18 new studies were included, along with the 22 studies from the 2013 review. Previously observed increased risks remained for perinatal mortality (relative risk [RR] 1.14, 95% confidence interval [CI]: 1.05, 1.23 n = 16 studies; aOR 1.07, 95% CI: 0.98-1.17 n = 6), congenital malformations (RR 1.36, 95% CI: 1.32-1.40 n = 17; aOR 1.42, 95% CI: 1.38-1.47 n = 6), and neonatal hospitalization (RR 1.27, 95% CI: 1.25-1.30 n = 12; aOR 1.1, 95% CI: 1.07-1.16 n = 3) amongst infants born to mothers with asthma, while the risk for neonatal death was no longer significant (RR 1.33, 95% CI: 0.95-1.84 n = 8). Previously reported non-significant risks for major congenital malformations (RR1.18, 95% CI: 1.15-1.21; aOR 1.20, 95% CI: 1.15-1.26 n = 3) and respiratory distress syndrome (RR 1.25, 95% CI: 1.17-1.34 n = 4; aOR 1.09, 95% CI: 1.01-1.18 n = 2) reached statistical significance. CONCLUSIONS: Healthcare professionals should remain aware of the increased risks to neonates being born to mothers with asthma.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.045
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.040
Bibliometrics0.0100.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
GPT teacher head0.365
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations14
Published2024
Admission routes1
Has abstractyes

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