Evidence map›Paper›PMID 37149590›Full record

ArticleBMC pregnancy and childbirth2023

Nomogram for predicting the risk of preterm birth in women undergoing in vitro fertilization cycles.

Mohan Wang, Mengzhe Hao, Ning Liu, Xiao Yang, Yubin Lu, Ruizhi Liu, Hongguo Zhang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Mohan WangPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Mengzhe HaoPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Ning LiuPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Xiao YangPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Yubin LuPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Ruizhi LiuPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Hongguo ZhangPrenatal Diagnosis Center, Reproductive Medicine Center, The First Hospital of Jilin University, Changchun, Jilin, China. zhanghguo@jlu.edu.cn.
Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to develop a nomogram for predicting the risk of preterm birth in women undergoing in vitro fertilization (IVF) cycles.

methodsA retrospective study of 4266 live birth cycles collected from January 2016 to October 2021 at the Center for Reproductive Medicine, First Hospital of Jilin University was performed. The sample size was sufficient based on the minimal ten events per variable (EPV) rule. The primary outcome of this study was preterm birth. The cycles were divided into the preterm birth group (n = 827) and the full-term delivery group (n = 3439). A nomogram was established based on the multivariate logistic regression analysis results. The area under the curve (AUC) was calculated to assess the prediction accuracy of the nomogram model. The calibration curve was used to measure the calibration of the nomogram.

resultsMultivariate logistic regression analyses showed that female obesity or overweight (OR = 1.366, 95% CI: 1.111-1.679; OR = 1.537, 95% CI: 1.030-2.292), antral follicle count (AFC) of more than 24 (OR = 1.378, 95% CI: 1.035-1.836), multiple pregnancies (OR = 6.748, 95% CI: 5.559-8.190), gestational hypertension (OR = 9.662, 95% CI: 6.632-14.078) and gestational diabetes (OR = 4.650, 95% CI: 2.289-9.445) were the independent risk factors for preterm birth in IVF patients. The area under curve (AUC) under the receiver operating characteristic (ROC) curve in the prediction model was 0.781(95%CI: 0.763-0.799). The calibration curve of the nomogram showed that the prediction model had a good calibration.

conclusionsWe used five risk factors to conduct a nomogram to predict preterm birth rates for patients undergoing IVF cycles. This nomogram can provide a visual assessment of the risk of preterm birth for clinical consultation.

Indexed as

Premature BirthFemaleFertilization in VitroHumansInfant, NewbornNomogramsPregnancyRetrospective StudiesRisk FactorsInfertilityIn vitro fertilizationNomogramPreterm birth

Identifiers

PMID37149590
PMCPMC10163771
OpenAlexW4372351817

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.