Evidence map›Paper›PMID 39544382›Full record

ArticleFrontiers in medicine2024

The value of ultrasonographic factors in predicting cesarean following induction.

Guangpu Liu, Chaofan Zhou, Zhifen Yang, Jingya Zhang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Guangpu LiuDepartment of Obstetrics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Chaofan ZhouDepartment of Neurology, Children's Hospital of Hebei Province, Shijiazhuang, Hebei, China.
Zhifen YangDepartment of Obstetrics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Jingya ZhangDepartment of Obstetrics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to develop and validate a prediction model of cesarean following induction of labor (IOL). A nomogram for the prediction of cesarean following IOL for singleton, cephalic term deliveries was created by comparing combinations of ultrasonographic and nonultrasonographic factors in a retrospective manner using patient data collected from a Chinese hospital between July, 2017 and December, 2023. Model discrimination and calibration were evaluated using the area under the receiver operating characteristic curve (AUROC) and a calibration curve. Subsequently, decision curve analysis (DCA) was conducted to pinpoint the optimal probability threshold for the predictive model to exhibit practical significance for clinical decision-making. A total of 738 women were included. The inclusion of ultrasound factors yielded a higher AUC when combined with nonultrasonographic factors. Of the three ultrasonographic factors analyzed, the most predictive factor for cesarean following IOL was fetal head circumference. After generating a nomogram with eight validated factors, including maternal age, gestational age, height, prior caesarean delivery, previous vaginal delivery, modified Bishop score, body mass index at delivery, and fetal head circumference by ultrasound, the trained and validated AUC values were 0.826 (95% confidence interval 0.786-0.867) and 0.883 (95% confidence interval 0.839-0.926), respectively. Decision curve analysis indicated that the model provided net benefits of between 0% and 80% of the probability threshold, indicating the benefits of using the model to make decisions concerning patients who fall within the identified range of the probability threshold. Our nomogram based on obstetric factors and fetal head circumference as obtained by ultrasound could be used to help counsel women who are considering IOL. The model demonstrates favorable net benefits within a probability threshold range of 0 to 80%.

Indexed as

cesarean following inductionfetal head circumferenceinduction of laborprediction modelultrasound

Identifiers

PMID39544382
PMCPMC11560775

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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.