Original Article
Prediction model of recovery time after gynecological robotic surgical procedures
Liu Yi, Tang Yongzhong, Quan Chengxuan, Huang Dong, Ouyang Wen, Yan Xuebin
Published 2021-12-20
Cite as J Chin Physician, 2021, 23(12): 1805-1809. DOI: 10.3760/cma.j.cn431274-20201104-01495
Abstract
ObjectiveIn 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.
MethodsThe 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.
ResultsFinally, 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.
ConclusionsThe prediction model of PACU extubation time and the postoperative hospitalization time has been established.
Key words:
Gynecologic surgical procedures; Robotic surgical procedures; Intubation, intratracheal; Length of stay; Models, statistical
Contributor Information
Liu Yi
Department of Anesthesiology, the First Hospital of Changsha, Changsha 410005, China
Tang Yongzhong
Hunan Province Key Laboratory of Brain Homeostasis, Changsha 410013, China
Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
Quan Chengxuan
Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
Huang Dong
Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
Ouyang Wen
Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
Yan Xuebin
Department of Anesthesiology, The Third Xiangya Hospital, Central South University, Changsha 410013, China
