Evidence map›Paper›PMID 35931901›Full record

ArticleArchives of gynecology and obstetrics2023

The development of a prediction model for arrest of labour to be used at regular check-ups, during 36 or 37 gestational weeks, for primiparas: a retrospective cohort study.

Noriko Furuita, Satoe Okabayashi, Ayumi Yamanishi, Misako Nakamura, Takashi Kawamura

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In one paragraph

Article in Archives of gynecology and obstetrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Noriko FuruitaDepartment of Preventive Services, School of Public Health in the Graduate School of Medicine, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan.
Satoe OkabayashiKyoto University Health Service, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan. okabayashi.satoe.8c@kyoto-u.ac.jp.ORCID http://orcid.org/0000-0001-9919-6768
Ayumi YamanishiKyoto Min-iren Chuo Hospital, 2-1 Uzumasa Tsuchimoto-cho, Ukyo-ku, Kyoto, 616-8147, Japan.
Misako NakamuraKyoto Min-iren Chuo Hospital, 2-1 Uzumasa Tsuchimoto-cho, Ukyo-ku, Kyoto, 616-8147, Japan.
Takashi KawamuraKyoto University Health Service, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan.
Kyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAn emergency caesarean section (CS) has more complications than a planned CS. The arrest of labour is a major indication for an emergency CS. This study aimed to develop a prediction model for the arrest of labour to be used in regular check-ups at 36 or 37 gestational weeks for primiparas.

methodsThis was a retrospective cohort study conducted at a single institution in Japan using data from January 2007 to December 2013. Primiparas attending regular check-ups during 36 or 37 gestational weeks, with live single foetuses in a cephalic presentation were included. The outcome was the incidence of labour arrest. Candidate predictors included 25 maternal and foetal findings. We developed a prediction model using logistic regression analysis with stepwise selection. A score was assigned to each predictor of the final model based on their respective β coefficients.

resultsA total of 739 women were included in the analysis. Arrest of labour was diagnosed in 47 women (6.4%), and all of them delivered by emergency CS. The predictors in the final model were a Bishop score ≤ 1, maternal height ≤ 154 cm, foetal biparietal diameter ≥ 91 mm, pre-pregnancy weight ≥ 54 kg, maternal haemoglobin concentration ≥ 11.0 g/dl, and amniotic fluid index ≥ 13. The area under the receiver operating characteristic curve was 0.783.

conclusionWe have developed the first model to predict arrested labour before its onset. Although this model requires validation using external samples, it will help clinicians and pregnant women to control gestational conditions and make decisions regarding planned CS.

Indexed as

Cesarean SectionLabor, ObstetricAmniotic FluidFemaleHumansParityPregnancyRetrospective StudiesArrest of labourEmergency caesarean sectionPrediction modelPrimipara

Identifiers

PMID35931901
OpenAlexW4289929998

What OpenQuestion holds

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Registered trials

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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.