Evidence map›Paper›PMID 36398206›Full record

ArticleAmerican journal of translational research2022

A nomogram to predict preterm birth in twin pregnancies.

Qian Gui, Yajun Yang, Lan Wang, Ya Chen, Linwei Mei, Xue Xiang, Xia Lan

Abstract read
In one paragraph

Article in American journal of translational research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

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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

2 citing papers in PubMed.

  1. Article
  2. Construction of a nomogram model for predicting infectious intrapartum fever.Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2023
    Article
4 · The record

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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.

Qian GuiDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Yajun YangDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Lan WangDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Ya ChenDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Linwei MeiDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Xue XiangDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.
Xia LanDepartment of Obstetrics, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children Chongqing 401132, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo investigate risk factors for preterm birth in twin pregnancies, and to establish a nomogram model for predicting preterm birth and verify its application value.

methodsData from 266 twin pregnancies between January 2015 and December 2020 were analyzed in this retrospective study. According to the gestational weeks of delivery, the included subjects were divided into a preterm birth group (gestational age < 37 weeks) and a full-term group (gestational age ≥ 37 weeks). The general situation and pregnancy complications of the two groups were analyzed by univariate analysis, and the factors with statistical significance were entered into multivariate logistic regression analysis. Furthermore, the nomogram model for predicting the risk of preterm birth was established by using R. The predictive effect of the model was evaluated by the area under the ROC curve, C-index, and decision curve analysis.

resultsDemographic characteristics and their associations with preterm birth and full-term birth in twin pregnancies were summarized and analyzed. After validation, we identified the following significant predictors of preterm birth: chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia. Overall, we constructed preterm risk nomogram model with C-index of 0.783. A nomogram using a 0-100 scale illustrated our final model for predicting preterm birth in twin pregnancies.

conclusionsWe developed and validated a clinical nomogram to predict preterm birth in twin pregnancy. Chorionic status, inconsistent development of twins, premature rupture of membranes, fetal distress, scar uterus, and preeclampsia were independent risk predictors for preterm birth in twin pregnancy.

Indexed as

nomogramPreterm birthrisk predictorstwin pregnancy

Identifiers

PMID36398206
PMCPMC9641497

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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.