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Predictive Model for Histological Chorioamnionitis Risk in Parturients with Intrapartum Fever
Xiufang Shao1, Bingqing Lv1, Yingling Xiu1
1Department of Gynecology and Obstetrics, Fujian Provincial Maternity and Children's Hospital, Fuzhou, China.
This study aimed to analyze the causative factors of histological chorioamnionitis (HCA) in parturients with intrapartum fever, assess the implications for maternal and neonatal outcomes, and develop a predictive model to enhance clinical decision-making. A retrospective analysis was performed on 408 parturients with intrapartum fever at Fujian Provincial Maternal and Child Health Hospital from January 2022 to June 2023. Based on post-delivery placental pathology, the data were categorized into HCA (249 cases) and non-HCA groups (159 cases). Variables were first screened using univariate analysis, followed by multivariate logistic regression to identify high-risk factors and develop a predictive model. The model's accuracy was validated using Bootstrap resampling and receiver operating characteristic (ROC) curve analysis. Significant differences were found between the HCA and non-HCA groups in terms of duration of premature rupture of membranes (≥24 hours), peak body temperature during labor (≥38°C), and levels of white blood cell count and C-reactive protein (CRP) at the onset of fever (p < 0.05). The predictive model showed strong accuracy, with an ROC area under the curve of 0.715. Intrapartum fever linked with HCA markedly exacerbates maternal and neonatal outcomes. Key risk factors for HCA include a peak labor temperature ≥38°C, CRP levels at fever onset, and grade III contamination of amniotic fluid. The developed model accurately predicts the HCA risk, enabling enhanced clinical interventions.
This study aimed to analyze the causative factors of histological chorioamnionitis (HCA) in parturients with intrapartum fever, assess the implications for maternal and neonatal outcomes, and develop a predictive model to enhance clinical decision-making. A retrospective analysis was performed on 408 parturients with intrapartum fever at Fujian Provincial Maternal and Child Health Hospital from January 2022 to June 2023. Based on post-delivery placental pathology, the data were categorized into HCA (249 cases) and non-HCA groups (159 cases). Variables were first screened using univariate analysis, followed by multivariate logistic regression to identify high-risk factors and develop a predictive model. The model's accuracy was validated using Bootstrap resampling and receiver operating characteristic (ROC) curve analysis. Significant differences were found between the HCA and non-HCA groups in terms of duration of premature rupture of membranes (≥24 hours), peak body temperature during labor (≥38°C), and levels of white blood cell count and C-reactive protein (CRP) at the onset of fever (p < 0.05). The predictive model showed strong accuracy, with an ROC area under the curve of 0.715. Intrapartum fever linked with HCA markedly exacerbates maternal and neonatal outcomes. Key risk factors for HCA include a peak labor temperature ≥38°C, CRP levels at fever onset, and grade III contamination of amniotic fluid. The developed model accurately predicts the HCA risk, enabling enhanced clinical interventions.
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