Journal of Pain Research (Jan 2024)
Development and Validation of a Nomogram for the Failed Conversion of Labor Analgesia to Cesarean Section Anesthesia
Abstract
Yihan Zheng, Li Zhang, Xizhu Wu, Min Zhou Department of Anesthesiology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350001, Fujian, People’s Republic of ChinaCorrespondence: Min Zhou, Department of Anesthesiology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, 350001, People’s Republic of China, Tel +86 0591-13850101696, Fax +86 0591-86329382, Email [email protected]: The conversion of epidural labor analgesia (ELA) to epidural surgical anesthesia (ESA) for intrapartum cesarean section (CS) often encounters failures. This study aimed to develop a nomogram for predicting the failure rate of this conversion.Patients and Methods: A retrospective analysis was conducted on data from the Fujian Maternity and Child Health Hospital. Pregnant women (n=214) who underwent cesarean section after receiving labor analgesia. We performed correlation heat map and Lasso regression in terms of exclusion confounding factors and screening independent variables. A nomogram was developed to predict the occurrence.Results: The developed nomogram incorporated variables such as pregnant history, weight, premature rupture of membranes (PROM), dural puncture epidural (DPE), anesthesiologist level of cesarean section (ALOCS), and Anesthesiologist level of labor analgesia (ALOLA). The model demonstrated good predictive performance, providing a practical tool for assessing the risk of failure in converting labor analgesia to cesarean section anesthesia.Conclusion: The nomogram can aid anesthesiologists in making informed decisions and optimizing patient care. By utilizing the nomogram, clinicians can estimate the probability of conversion failure based on individual patient characteristics and clinical factors.Keywords: labor analgesia, cesarean section anesthesia, conversion failure, nomogram, predictive model
