Development and assessment of novel machine learning models to predict the probability of postoperative nausea and vomiting for patient-controlled analgesia.
Development and assessment of novel machine learning models to predict the probability of postoperative nausea and vomiting for patient-controlled analgesia.
复制标题
DOI：
10.1038/s41598-023-33807-7
复制
发表时间：
2023-04-20
影响因子：
4.6
通讯作者：
Li, Tao
中科院分区：
文献类型：
--
作者：
Xie, Min;Deng, Yan;Wang, Zuofeng;He, Yanxia;Wu, Xingwei;Zhang, Meng;He, Yao;Liang, Yu;Li, Tao
Postoperative nausea and vomiting (PONV) can lead to various postoperative complications. The risk assessment model of PONV is helpful in guiding treatment and reducing the incidence of PONV, whereas the published models of PONV do not have a high accuracy rate. This study aimed to collect data from patients in Sichuan Provincial People’s Hospital to develop models for predicting PONV based on machine learning algorithms, and to evaluate the predictive performance of the models using the area under the receiver characteristic curve (AUC), accuracy, precision, recall rate, F1 value and area under the precision-recall curve (AUPRC). The AUC (0.947) of our best machine learning model was significantly higher than that of the past models. The best of these models was used for external validation on patients from Chengdu First People’s Hospital, and the AUC was 0.821. The contributions of variables were also interpreted using SHapley Additive ExPlanation (SHAP). A history of motion sickness and/or PONV, sex, weight, history of surgery, infusion volume, intraoperative urine volume, age, BMI, height, and PCA_3.0 were the top ten most important variables for the model. The machine learning models of PONV provided a good preoperative prediction of PONV for intravenous patient-controlled analgesia.
登录
查看更多内容
DOI：
10.1007/bf03021622
发表时间：
2006-07-01
期刊：
CANADIAN JOURNAL OF ANAESTHESIA-JOURNAL CANADIEN D ANESTHESIE
影响因子：
--
作者：
Gurbet, A;Basagan-Mogol, E;Ozcan, B
通讯作者：
Ozcan, B
影响因子：
9.8
作者：
Apfel, CC;Kranke, P;Roewer, N
通讯作者：
Roewer, N
DOI：
10.1007/s00464-015-4071-7
发表时间：
2015-11-01
影响因子：
3.1
作者：
Singh, Basant Narayan;Dahiya, Divya;Jain, Kajal
通讯作者：
Jain, Kajal
影响因子：
2.9
作者：
Wu XW;Zhang JY;Chang H;Song XW;Wen YL;Long EW;Tong RS
通讯作者：
Tong RS
影响因子：
3.6
作者：
Mauermann, Eckhard;Clamer, Damian;Bandschapp, Oliver
通讯作者：
Bandschapp, Oliver