Evidence map›Paper›PMID 38713295›Full record

ArticleArchives of gynecology and obstetrics2024

Predictors and a scoring model for maternal near-miss and maternal death in Southern Thailand: a case-control study.

Wipawan Raktong, Rapphon Sawaddisan, Krantarat Peeyananjarassri, Chitkasaem Suwanrath, Alan Geater

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Article in Archives of gynecology and obstetrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wipawan RaktongDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Rapphon SawaddisanDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand. sai.sawaddisan@gmail.com.ORCID 0000-0003-1588-8789
Krantarat PeeyananjarassriDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Chitkasaem SuwanrathDepartment of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand.
Alan GeaterDepartment of Epidemiology, Faculty of Medicine, Prince of Songkla, University, Songkhla, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify predictors and develop a scoring model to predict maternal near-miss (MNM) and maternal mortality.

methodsA case-control study of 1,420 women delivered between 2014 and 2020 was conducted. Cases were women with MNM or maternal death, controls were women who had uneventful deliveries directly after women in the cases group. Antenatal characteristics and complications were reviewed. Multivariate logistic regression and Akaike information criterion were used to identify predictors and develop a risk score for MNM and maternal mortality.

resultsPredictors for MNM and maternal mortality (aOR and score for predictive model) were advanced age (aOR 1.73, 95% CI 1.25-2.39, 1), obesity (aOR 2.03, 95% CI 1.22-3.39, 1), parity ≥ 3 (aOR 1.75, 95% CI 1.27-2.41, 1), history of uterine curettage (aOR 5.13, 95% CI 2.47-10.66, 3), history of postpartum hemorrhage (PPH) (aOR 13.55, 95% CI 1.40-130.99, 5), anemia (aOR 5.53, 95% CI 3.65-8.38, 3), pregestational diabetes (aOR 5.29, 95% CI 1.27-21.99, 3), heart disease (aOR 13.40, 95%CI 4.42-40.61, 5), multiple pregnancy (aOR 5.57, 95% CI 2.00-15.50, 3), placenta previa and/or placenta-accreta spectrum (aOR 48.19, 95% CI 22.75-102.09, 8), gestational hypertension/preeclampsia without severe features (aOR 5.95, 95% CI 2.64-13.45, 4), and with severe features (aOR 16.64, 95% CI 9.17-30.19, 6), preterm delivery <37 weeks (aOR 1.65, 95%CI 1.06-2.58, 1) and < 34 weeks (aOR 2.71, 95% CI 1.59-4.62, 2). A cut-off score of ≥4 gave the highest chance of correctly classified women into high risk group with 74.4% sensitivity and 90.4% specificity.

conclusionsWe identified predictors and proposed a scoring model to predict MNM and maternal mortality with acceptable predictive performance.

Indexed as

Maternal DeathMaternal MortalityNear Miss, HealthcarePregnancy ComplicationsAdultCase-Control StudiesFemaleHumansLogistic ModelsParityPostpartum HemorrhagePregnancyRisk AssessmentRisk FactorsThailandYoung AdultMorbidityMortalityNear-missPredictionPregnancy

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.