Prediction model of recovery time after gynecological robotic surgical procedures
10.3760/cma.j.cn431274-20201104-01495
- VernacularTitle:妇科机器人手术术后恢复时间的预测模型建立
- Author:
Yi LIU
1
;
Yongzhong TANG
;
Chengxuan QUAN
;
Dong HUANG
;
Wen OUYANG
;
Xuebin YAN
Author Information
1. 长沙市第一医院麻醉科 410005
- Keywords:
Gynecologic surgical procedures;
Robotic surgical procedures;
Intubation, intratracheal;
Length of stay;
Models, statistical
- From:
Journal of Chinese Physician
2021;23(12):1805-1809
- CountryChina
- Language:Chinese
-
Abstract:
Objective:In order to accurately evaluate the postoperative rehabilitation of gynecological robotic surgery, a prediction model for evaluating postanesthesia care unit (PACU) extubation time and hospital stay in gynecological robotic surgery was established.Methods:The clinical data of gynecological patients who underwent robotic surgery in Xiangya Third Hospital of Central South University from October 2015 to May 2017 were retrospectively analyzed, and the data were screened to evaluate the postoperative recovery of patients from two aspects: PACU extubation time and postoperative hospital stay. Binary logistic regression was used to screen out the factors affecting PACU extubation time and postoperative hospital stay, and the prediction model was preliminarily established and verified.Results:Finally, there were 456 patients and 30 variables analyzed in the binary logistics regression. According to these variables, the prediction model of the postoperative recovery evaluation after gynecological robotic surgical procedures was established. Among them, age, intraoperative amount of atracurium and midazolam were independent risk factors affecting PACU extubation time (all P<0.05). American Society of Anesthesiologists (ASA) grade, intraoperative amount of midazolam, intraoperative bleeding and operation time were independent risk factors affecting postoperative hospital stay (all P<0.05). All models passed Hosmer lemeshow test (all P>0.05); The areas under the receiver operating characteristic curve (ROC) were 0.647 and 0.806, respectively. Conclusions:The prediction model of PACU extubation time and the postoperative hospitalization time has been established.
