Evidence map›Paper›PMID 35305610›Full record

ArticleBMC pregnancy and childbirth2022

Establishment of a nomogram model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia.

Bohan Lv, Yan Zhang, Guanghui Yuan, Ruting Gu, Jingyuan Wang, Yujiao Zou, Lili Wei

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 8 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 2 institutions in 1 country.

Bohan LvSchool of Nursing, Qingdao University, Qingdao, China.
Yan ZhangDepartment of Nursing, The Affiliated Hospital of Qingdao University, #16 Jiangsu Road, Qingdao, 266003, Shandong Province, China.
Guanghui YuanMedical College of Qingdao University, Qingdao, China.
Ruting GuDepartment of Nursing, The Affiliated Hospital of Qingdao University, #16 Jiangsu Road, Qingdao, 266003, Shandong Province, China.
Jingyuan WangDepartment of Respiratory and Critical Care Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yujiao ZouSchool of Nursing, Qingdao University, Qingdao, China.
Lili WeiDepartment of Nursing, The Affiliated Hospital of Qingdao University, #16 Jiangsu Road, Qingdao, 266003, Shandong Province, China. weilili@qduhospital.cn.
Qingdao University · CNAffiliated Hospital of Qingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo establish a model for predicting adverse outcomes in advanced-age pregnant women with preterm preeclampsia in China.

methodsWe retrospectively collected the medical records of 896 pregnant women with preterm preeclampsia who were older than 35 years and delivered at the Affiliated Hospital of Qingdao University from June 2018 to December 2020. The pregnant women were divided into an adverse outcome group and a non-adverse outcome group according to the occurrence of adverse outcomes. The data were divided into a training set and a verification set at a ratio of 8:2. A nomogram model was developed according to a binary logistic regression model created to predict the adverse outcomes in advanced-age pregnant women with preterm preeclampsia. ROC curves and their AUCs were used to evaluate the predictive ability of the model. The model was internally verified by using 1000 bootstrap samples, and a calibration diagram was drawn.

resultsBinary logistic regression analysis showed that platelet count (PLT), uric acid (UA), blood urea nitrogen (BUN), prothrombin time (PT), and lactate dehydrogenase (LDH) were the factors that independently influenced adverse outcomes (P < 0.05). The AUCs of the internal and external verification of the model were 0.788 (95% CI: 0.737 ~ 0.764) and 0.742 (95% CI: 0.565 ~ 0.847), respectively. The calibration curve was close to the diagonal.

conclusionsThe model we constructed can accurately predict the risk of adverse outcomes of pregnant women of advanced age with preterm preeclampsia, providing corresponding guidance and serving as a basis for preventing adverse outcomes and improving clinical treatment and maternal and infant prognosis.

Indexed as

Maternal AgeNomogramsAdultAsian PeopleChinaFemaleHumansPre-EclampsiaPregnancyPregnancy ComplicationsPregnancy, High-RiskPregnancy OutcomePrognosisRetrospective StudiesRisk FactorsROC CurveAdvanced age pregnant womenNomogramPrediction modelPreterm preeclampsia

Identifiers

PMID35305610
PMCPMC8933958
OpenAlexW4220788378

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.