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

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.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82722-y
Citations
3
Primary Topic
Preterm Birth and Chorioamnionitis
Type
article
Field-Weighted Citation Impact
1.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Ling Liang, Mengqiao Wang, Ben-zhen Chen, Bo Liu et al.
3 citations
Scientific Reports
Preterm Birth and Chorioamnionitis
1.16
article

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

Ling Liang, Mengqiao Wang, Ben-zhen Chen, Bo Liu, Jia Fei, Yong Tang, Chunping Li, Dan Zhang, Jian Zhang
article en
3 citations

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.

Scientific ReportsVol. 14(1)
Chengdu Medical College (CN), Chengdu Women's and Children's Central Hospital (CN)
Zero hunger
Openalex Percentile: Top 18%
Preterm Birth and Chorioamnionitis
1.16
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.