Construction of a prediction model for intrapartum fever related to chorioamnionitis in parturients undergoing epidural labor analgesia
10.3760/cma.j.cn131073.20240126.00703
- VernacularTitle:硬膜外分娩镇痛产妇绒毛膜羊膜炎相关产时发热预测模型的建立
- Author:
Liang LING
1
;
Bo LIU
;
Dayuan WEI
;
Benzhen CHEN
;
Hongquan XIAO
;
Jian ZHANG
Author Information
1. 川北医学院临床医学院，南充 637100
- Keywords:
Labor pain;
Analgesia, epidural;
Fever;
Chorioamnionitis;
Prediction
- From:
Chinese Journal of Anesthesiology
2024;44(7):780-785
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop a predictive model for intrapartum fever related to chorioamnionitis in parturients undergoing epidural labor analgesia.Methods:This was a retrospective study. The parturients with intrapartum fever (axillary temperature ≥38 ℃) who received epidural labor analgesia from January 2020 to December 2022 in Sichuan Maternal and Child Health Hospital were selected as model group, and parturients with intrapartum fever who received epidural labor analgesia from January to October 2023 in Sichuan Maternal and Child Health Hospital were selected as validation group. The parturients in model group were divided into histological chorioamnionitis stage ≥Ⅱ group (HCA≥Ⅱ group) and histological chorioamnionitis stage <Ⅱ group (HCA<Ⅱ group) according to the results of placental histopathological examination. Logistic regression analysis was used to screen the independent risk factors for intrapartum fever related to chorioamnionitis in parturients, and then a nomogram model was established. The discrimination of the model was verified by the area under the the receiver operating characteristic curve. The consistency of the model was verified by the calibration curve, and the clinical effectiveness of the model was determined by the decision curve. The validation dataset was used to further evaluate the model.Results:A total of 308 parturients were finally included in model group and 99 parturients in validation group. Multivariate logistic regression analysis showed that the gestational age, meconium-stained amniotic fluid, c-reactive protein concentration and maximum body temperature were independent risk factors for intrapartum fever related to chorioamnionitis in parturients undergoing epidural labor analgesia ( P<0.05). Based on this, a nomogram risk prediction model was developed. The area under the curve (95% confidence interval) was 0.844 (0.744-0.944) in model group and 0.812 (0.674-0.950) in validation group. The calibration curve showed that the prediction probability of the model had good consistency with the actual probability of diagnosis. The decision curve showed that the threshold probability of the prediction model in model group and validation group was 10%-98% and 10%-78%, respectively. Conclusions:A nomogram prediction model for intrapartum fever related to chorioamnionitis is successfully established based on the gestational age, c-reactive protein concentration, meconium-stained amniotic fluid and maximum body temperature in parturients undergoing epidural labor analgesia. The model has good predictive performance and clinical value.
