Predicting postoperative nausea and vomiting after cesarean section ： a nomogram model combined with gastric ultrasound

Abstract

Abstract We aimed to explore the independent risk factors for postoperative nausea and vomiting (PONV) after caesarean section and to establish and validate a nomogram prediction model combined with gastric ultrasound. Clinical data from 116 patients were randomly divided into training (n = 87) and validation groups (n = 29). Univariate and multivariate logistic regression were used to analyse the risk factors for PONV after the caesarean section. Independent risk factors related to PONV were identified, and a nomogram model was established. Receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) were employed to assess the predictive efficacy, accuracy, and clinical practicability of the model and internally verified. Twenty-four patients experienced PONV in the training group. Motion sickness history, a systolic blood pressure fall > 20%, and gastric volume were identified as independent PONV risk factors, which were used to construct a nomogram model. The area under the ROC curve values for predicting the training and validation groups were 0.813 and 0.738, respectively. DCA confirmed the clinical practicability and application. The nomogram model provides an intuitive and visual tool for rapid PONV risk assessment before a caesarean section, facilitating accurate, individualised perioperative management strategies and promoting rapid recovery.