Evidence map›Paper›PMID 39732828›Full record

ArticleScientific reports2024

Development and validation of a prediction model for intrapartum fever related to chorioamnionitis in parturients undergoing epidural analgesia.

Liang Ling, Bo Liu, Chunping Li, Dan Zhang, Fei Jia, Yong Tang, Benzhen Chen, Mengqiao Wang, Jian Zhang

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

6 citing papers in PubMed.

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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

9 authors.

Liang Ling *Department of Anesthesiology, Sichuan Women's and Children's Hospital/Women's and Children's Hospital, Chengdu Medical College, Chengdu, 610000, China.
Bo Liu *Department of Anesthesiology, Chengdu Jinjiang District Women & Children Health Hospital, Chengdu, 610000, China.
Chunping LiDepartment of Anesthesiology, Sichuan Jinxin Xinan Women & Children Hospital, Chengdu, 610000, China.
Dan ZhangDepartment of Women Health Care, Sichuan Women's and Children's Hospital/Women's and Children's Hospital, Chengdu Medical College, Chengdu, 610000, China.
Fei JiaDepartment of Anesthesiology, Chengdu Jinjiang District Women & Children Health Hospital, Chengdu, 610000, China.
Yong TangDepartment of Anesthesiology, Sichuan Jinxin Xinan Women & Children Hospital, Chengdu, 610000, China.
Benzhen ChenDepartment of Anesthesiology, Sichuan Women's and Children's Hospital/Women's and Children's Hospital, Chengdu Medical College, Chengdu, 610000, China.
Mengqiao WangDepartment of Epidemiology and Biostatistics, Chengdu Medical College, Chengdu, 610500, China.
Jian ZhangDepartment of Anesthesiology, Sichuan Women's and Children's Hospital/Women's and Children's Hospital, Chengdu Medical College, Chengdu, 610000, China. anesthesiologyzj@foxmail.com.

Funding

Chengdu medical research projects 2023012
6 · The paper itself

Abstract

Intrapartum fever is a common complication in parturients undergoing epidural analgesia (EA), significantly increasing the incidence of maternal and infant complications. This study aims to develop and validate a prediction model for intrapartum fever related to chorioamnionitis (IFTC) in parturients undergoing epidural analgesia. A total of 596 parturients with fever (axillary temperature ≥ 38℃) who received EA from January 2020 to December 2023 were included and randomly assigned to the training set (N = 417) and the validation set (N = 179) according to the ratio of 7:3. The independent risk factors were screened by univariate and multivariate logistic regression analysis to develop a nomogram model. Decision curve analysis (DCA) was used to evaluate the clinical effectiveness and discrimination of the model; calibration curve was used to assess the accuracy of the model. Maximum temperature, meconium-stained amniotic fluid, C-reactive protein (CRP), gestational age and BMI were independent risk factors for predicting IFTC, and the area under receiver operating characteristic curve (AUC) of the training set and the validation set were 0.744 (0.691-0.796) and 0.793 (0.714-0.872), respectively. The calibration curve showed good consistency between predicted and actual results. DCA curve showed that the model had clinical value throughout a broad threshold probability range. The nomogram prediction model based on CRP, meconium-stained amniotic fluid, maximum temperature, gestational age and BMI has good predictive performance for the risk of IFTC in EA parturients.

Indexed as

Analgesia, EpiduralChorioamnionitisFeverNomogramsAdultAnalgesia, ObstetricalC-Reactive ProteinFemaleHumansPregnancyRisk FactorsROC CurveC-Reactive ProteinAnalgesiaChorioamnionitisEpiduralFeverLabor painPrediction

Identifiers

PMID39732828
PMCPMC11682342

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.