Outpatient Office, Chun'an First People's Hospital, Chun'an 311700, China.
Department of Nursing, Chun'an First People's Hospital, Chun'an 311700, China.
J Healthc Eng. 2022 Apr 21;2022:8237620. doi: 10.1155/2022/8237620. eCollection 2022.
In order to explore the construction and implementation effect of a procedural nursing system for laparoscopic surgery in general surgery based on deep learning, this article selects 150 cases of laparoscopic surgery patients admitted to our hospital from January 2020 to January 2021 for research. According to the time of enrollment, the control set and the study set were included in order, with 75 cases in each set. The control set was given routine nursing methods, and the research set was given the management of programmed nursing system based on deep learning. The nursing quality, pain, postoperative recovery, and incidence of complications were compared between the two sets. Logistic regression multivariate analysis of the risk factors for postoperative complications in patients undergoing laparoscopic surgery in general surgery was performed. Based on deep learning, the construction of the procedural nursing system for laparoscopic surgery in general surgery is applied to the nursing management of general surgery laparoscopic surgery, which can improve the quality of care and the VAS score of the patient's pain level, and reduce the incidence of complications. Underlying diseases and routine nursing are risk factors for complications of general surgery laparoscopic surgery, suggesting that corresponding prevention and control work should be done in the procedural nursing of general surgery laparoscopic surgery based on deep learning.
为了探索基于深度学习的普外科腹腔镜手术程序化护理体系的构建与实施效果,本文选取 2020 年 1 月至 2021 年 1 月我院收治的 150 例腹腔镜手术患者进行研究。根据纳入时间顺序,将对照组和研究组纳入,每组各 75 例。对照组给予常规护理方法,研究组给予基于深度学习的程序化护理体系管理。比较两组患者的护理质量、疼痛、术后恢复情况和并发症发生率。对普外科腹腔镜手术患者术后并发症的危险因素进行基于深度学习的逻辑回归多因素分析。基于深度学习构建普外科腹腔镜手术程序化护理体系应用于普外科腹腔镜手术护理管理,可以提高护理质量和患者疼痛水平的 VAS 评分,降低并发症发生率。基础疾病和常规护理是普外科腹腔镜手术并发症的危险因素,提示在基于深度学习的普外科腹腔镜手术程序化护理中应做好相应的预防和控制工作。