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Updated: Aug 10, 2025

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Predictors of Postoperative Nausea and Vomiting After Same-day Surgery: A Retrospective Study
Lili Qiu1, Jinxia Cai1, Aishuang Mei2
1Department of Anesthesiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Purpose:
Postoperative nausea and vomiting (PONV) are main issues after same-day surgery. This study aimed to retrospectively evaluate the electronic medical records of patients who underwent same-day operations under general anesthesia to identify the potential risk factors for PONV.
Methods:
Records of 7759 adult patients who received general anesthesia with remifentanil were reviewed. The patients were assessed for the incidence and severity of PONV. Multiple logistic regression was used to identify risk factors for PONV. A nomogram was established to predict PONV after same-day operations.
Findings:
Of 7759 patients, 2317 (29.9%) experienced PONV. In multiple logistic regression analysis, female sex, nonsmoker status, history of motion sickness or nausea, high body mass index (BMI), long surgical duration, laparoscopic procedure, and preoperative analgesic intake within 30 days were independent risk factors for PONV. No correlation was found between the severity of PONV and remifentanil exposure (odds ratio = 1.018; 95% CI, 0.861-1.204; P = 0.834) or remifentanil dose (odds ratio = 1.294; 95% CI, 0.760-2.205; P = 0.343). For the nomogram, which involved sex, laparoscopic procedure, BMI, history of nausea or motion sickness, and analgesic intake within 30 days, the receiver operating characteristic analysis revealed that the AUC values in the training and validation cohorts were 0.81 and 0.83, respectively.
Implications:
Predictors for PONV in same-day surgery include female sex, nonsmoker, history of motion sickness or nausea, high BMI, surgical duration >1 hour, laparoscopic procedure, and preoperative analgesic intake within 30 days. A new predictive model is feasible for predicting the incidence of PONV based on the preoperative and intraoperative predictors.
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