{"title":"动态图的发展和验证预测分娩方式和新生儿重症监护病房入院在产中发烧:回顾性队列研究。","authors":"Jianzhi Ni, Dan Zhang, Yuling Ding, Hongmei Ding, Zvikomborero Panashe Rejoice Munemo, Hongxiu Zhang","doi":"10.2147/IJWH.S544623","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>While maternal intrapartum fever is linked to adverse neonatal outcomes, predictive tools for delivery mode and neonatal intensive care unit (NICU) admission in this population remain scarce.</p><p><strong>Objective: </strong>To develop and validate a dynamic nomogram predicting cesarean delivery and NICU admissions in women with intrapartum fever, facilitating individualized intrapartum decision-making.</p><p><strong>Methods: </strong>This retrospective cohort study analyzed 24,784 deliveries (2019-2021) at a tertiary center. After exclusions, 1,047 women with intrapartum fever were included in the study cohort. The dataset was randomly partitioned into training (n=837) and testing (n=210) sets. Backward stepwise multivariable logistic regression models were developed to predict cesarean delivery and neonatal intensive care unit admission. The discriminative capacity of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Calibration performance was assessed via 1000 nonparametric bootstrap resamples to generate calibration curves, with systematic quantification of agreement between predicted probabilities and observed outcomes through the Brier score and Hosmer-Lemeshow goodness-of-fit test.</p><p><strong>Results: </strong>Predictors of cesarean delivery included advanced maternal age, hypertensive disorders, Intrapartum Antibiotic Prophylaxis (IAP), Meconium-Stained Amniotic Fluid (MSAF), Macrosomia, Postpartum Hemorrhage (PPH), Oligohydramnios, assisted reproductive technology (ART), Hypertensive Disorders of Pregnancy (HDP), Maternal tachycardia, Placental histopathology, intrapartum temperature and Method of inducing labor. Low Birth Weight (LBW), adverse obstetric history (AOH), Fetal tachycardia, Fetal bradycardia, Scarred uterus, Maternal tachycardia and MSAF predicted neonatal intensive care unit admission. The cesarean delivery model achieved AUC of 0.8 (training) and 0.783 (testing); the neonatal intensive care unit admission model showed AUC of 0.681 (training) and 0.748 (testing).</p><p><strong>Conclusion: </strong>This nomogram provides a clinically useful tool to predict delivery mode and neonatal intensive care unit admission in women with intrapartum fever, aiding risk stratification and improving perinatal outcomes.</p>","PeriodicalId":14356,"journal":{"name":"International Journal of Women's Health","volume":"17 ","pages":"3385-3400"},"PeriodicalIF":2.6000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495972/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and Validation of Dynamic Nomograms for Predicting Delivery Mode and Neonatal Intensive Care Unit Admission in Intrapartum Fever: A Retrospective Cohort Study.\",\"authors\":\"Jianzhi Ni, Dan Zhang, Yuling Ding, Hongmei Ding, Zvikomborero Panashe Rejoice Munemo, Hongxiu Zhang\",\"doi\":\"10.2147/IJWH.S544623\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>While maternal intrapartum fever is linked to adverse neonatal outcomes, predictive tools for delivery mode and neonatal intensive care unit (NICU) admission in this population remain scarce.</p><p><strong>Objective: </strong>To develop and validate a dynamic nomogram predicting cesarean delivery and NICU admissions in women with intrapartum fever, facilitating individualized intrapartum decision-making.</p><p><strong>Methods: </strong>This retrospective cohort study analyzed 24,784 deliveries (2019-2021) at a tertiary center. After exclusions, 1,047 women with intrapartum fever were included in the study cohort. The dataset was randomly partitioned into training (n=837) and testing (n=210) sets. Backward stepwise multivariable logistic regression models were developed to predict cesarean delivery and neonatal intensive care unit admission. The discriminative capacity of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Calibration performance was assessed via 1000 nonparametric bootstrap resamples to generate calibration curves, with systematic quantification of agreement between predicted probabilities and observed outcomes through the Brier score and Hosmer-Lemeshow goodness-of-fit test.</p><p><strong>Results: </strong>Predictors of cesarean delivery included advanced maternal age, hypertensive disorders, Intrapartum Antibiotic Prophylaxis (IAP), Meconium-Stained Amniotic Fluid (MSAF), Macrosomia, Postpartum Hemorrhage (PPH), Oligohydramnios, assisted reproductive technology (ART), Hypertensive Disorders of Pregnancy (HDP), Maternal tachycardia, Placental histopathology, intrapartum temperature and Method of inducing labor. Low Birth Weight (LBW), adverse obstetric history (AOH), Fetal tachycardia, Fetal bradycardia, Scarred uterus, Maternal tachycardia and MSAF predicted neonatal intensive care unit admission. The cesarean delivery model achieved AUC of 0.8 (training) and 0.783 (testing); the neonatal intensive care unit admission model showed AUC of 0.681 (training) and 0.748 (testing).</p><p><strong>Conclusion: </strong>This nomogram provides a clinically useful tool to predict delivery mode and neonatal intensive care unit admission in women with intrapartum fever, aiding risk stratification and improving perinatal outcomes.</p>\",\"PeriodicalId\":14356,\"journal\":{\"name\":\"International Journal of Women's Health\",\"volume\":\"17 \",\"pages\":\"3385-3400\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495972/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Women's Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2147/IJWH.S544623\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Women's Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/IJWH.S544623","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
Development and Validation of Dynamic Nomograms for Predicting Delivery Mode and Neonatal Intensive Care Unit Admission in Intrapartum Fever: A Retrospective Cohort Study.
Background: While maternal intrapartum fever is linked to adverse neonatal outcomes, predictive tools for delivery mode and neonatal intensive care unit (NICU) admission in this population remain scarce.
Objective: To develop and validate a dynamic nomogram predicting cesarean delivery and NICU admissions in women with intrapartum fever, facilitating individualized intrapartum decision-making.
Methods: This retrospective cohort study analyzed 24,784 deliveries (2019-2021) at a tertiary center. After exclusions, 1,047 women with intrapartum fever were included in the study cohort. The dataset was randomly partitioned into training (n=837) and testing (n=210) sets. Backward stepwise multivariable logistic regression models were developed to predict cesarean delivery and neonatal intensive care unit admission. The discriminative capacity of the model was evaluated using receiver operating characteristic (ROC) curve analysis. Calibration performance was assessed via 1000 nonparametric bootstrap resamples to generate calibration curves, with systematic quantification of agreement between predicted probabilities and observed outcomes through the Brier score and Hosmer-Lemeshow goodness-of-fit test.
Results: Predictors of cesarean delivery included advanced maternal age, hypertensive disorders, Intrapartum Antibiotic Prophylaxis (IAP), Meconium-Stained Amniotic Fluid (MSAF), Macrosomia, Postpartum Hemorrhage (PPH), Oligohydramnios, assisted reproductive technology (ART), Hypertensive Disorders of Pregnancy (HDP), Maternal tachycardia, Placental histopathology, intrapartum temperature and Method of inducing labor. Low Birth Weight (LBW), adverse obstetric history (AOH), Fetal tachycardia, Fetal bradycardia, Scarred uterus, Maternal tachycardia and MSAF predicted neonatal intensive care unit admission. The cesarean delivery model achieved AUC of 0.8 (training) and 0.783 (testing); the neonatal intensive care unit admission model showed AUC of 0.681 (training) and 0.748 (testing).
Conclusion: This nomogram provides a clinically useful tool to predict delivery mode and neonatal intensive care unit admission in women with intrapartum fever, aiding risk stratification and improving perinatal outcomes.
期刊介绍:
International Journal of Women''s Health is an international, peer-reviewed, open access, online journal. Publishing original research, reports, editorials, reviews and commentaries on all aspects of women''s healthcare including gynecology, obstetrics, and breast cancer. Subject areas include: Chronic conditions including cancers of various organs specific and not specific to women Migraine, headaches, arthritis, osteoporosis Endocrine and autoimmune syndromes - asthma, multiple sclerosis, lupus, diabetes Sexual and reproductive health including fertility patterns and emerging technologies to address infertility Infectious disease with chronic sequelae including HIV/AIDS, HPV, PID, and other STDs Psychological and psychosocial conditions - depression across the life span, substance abuse, domestic violence Health maintenance among aging females - factors affecting the quality of life including physical, social and mental issues Avenues for health promotion and disease prevention across the life span Male vs female incidence comparisons for conditions that affect both genders.