Objective:To investigate and compare the predictive effects of two postoperative nausea and vomiting (PONV) prediction models in elderly patients with thoracoscopic partial pneumonectomy.Methods:The total of 227 elderly patients who underwent thoracoscopic partial pneumonectomy in Brain Hospital Affiliated to Nanjing Medical University from October 2021 to January 2022 were collected. Apfel risk score and Koivuranta risk score were used to predict the risk of PONV in each patient. The area under the ROC curve was used to evaluate the discrimination ability of the two prediction models; Hosmer-Lemeshow goodness of fit test was used to evaluate the calibration of the two prediction models.Results:Among 227 patients, 74 had PONV, and the incidence of PONV was 32.6%. The area under the ROC curve of Apfel and Koivuranta risk scores in the risk prediction of PONV in elderly patients with thoracoscopic partial pneumonectomy were 0.640 and 0.683 respectively. There was no significant difference between the two ( Z=1.54, P>0.05). The Hosmer-Lemeshow goodness of fit test showed that the accuracy of the two models in predicting PONV risk in elderly patients with thoracoscopic partial pneumonectomy was better ( P>0.05). Conclusions:The difference between the two models in PONV risk prediction in elderly patients with thoracoscopic partial pneumonectomy is general, Koivuranta model is more suitable for predicting PONV in elderly patients with thoracoscopic partial pneumonectomy, but its applicability is still insufficient.