Predicting postoperative nausea and vomiting after cesarean section: a nomogram model combined with gastric ultrasound - Yingchao Liu; Huohu Zhong; Zhisen Dai; Yuxin Huang; Yibin Liu; Hefan He; Yuewen Liao; Weifeng Liu (BMC Anesthesiology)
Abstract Background To investigate the independent risk factors associated with postoperative nausea and vomiting (PONV) following Cesarean section procedures, and establish and validate a nomogram to predict them. Methods The clinical data of 116 adult patients who underwent Cesarean section procedures between August 2022 and February 2023 were included. Participants were randomly divided into training (n = 87) and verification sets (n = 29) in a 3:1 ratio. Univariate and multivariate logistic regression were used to analyze the risk factors for PONV following Cesarean sections and the independent risk factors were then used for the prediction model. Simultaneously, 29 adult patients who underwent caesarean section between February 2023 and April 2023 were included in the hospital as a test set to conduct external verification of the nomogram and Apfel scoring models, and compare their diagnostic efficacy in predicting PONV after caesarean section. Results A history of motion sickness, systolic blood pressure reduction > 20%, and gastric volume were independent risk factors for PONV and used to construct the model. The AUC for predicting the risk of PONV in the training and validation sets was 0.814 (95% confidence interval [CI] = 0.709–0.918) and 0.792 (95% CI = 0.621–0.962), respectively. In the test set, the AUCs of the nomogram and the Apfel scoring models were 0.779 (95% CI = 0.593–0.965) and 0.547 (95% CI = 0.350–0.745), respectively, with the former being significantly higher (Z = 2.165, P < 0.05). Conclusions Our nomogram model was superior to the Apfel scoring model and may be helpful in formulating appropriate individualized management strategies for nausea and vomiting following Cesarean sections, to promote the rapid recovery of patients.