摘要
目的探究腹腔镜结直肠癌根治术患者麻醉恢复期停留时间延长的影响因素,构建并验证预测模型。方法回顾性分析2021年1月~2023年6月于合肥市第二人民医院行腹腔镜结直肠癌根治术治疗的120例患者的病历资料。依据80/20定律将患者随机分为分为训练集(96例)和验证集(24例)。根据患者术后麻醉恢复期停留时间分为延长组(38例)和正常组(58例)。筛查腹腔镜结直肠癌根治术患者麻醉恢复期停留时间延长的风险因素,构建并验证风险预测模型。结果96例行腹腔镜结直肠癌根治术患者中,术后麻醉恢复期停留时间延长38例(39.58%),正常58例(60.42%)。延长组患者的合并慢性阻塞性肺疾病占比、术中采取静脉全麻占比、术中使用阿片类麻醉药物占比及术后发生低氧血症的占比均高于正常组(P<0.05)。年龄(OR=3.861,95%CI:1.358~10.981)、合并慢性阻塞性肺疾病(OR=4.080,95%CI:1.435~11.601)、静脉全麻(OR=3.892,95%CI:1.369~11.069)、阿片类麻醉药物(OR=4.267,95%CI:1.501~12.136)、术后低氧血症(OR=3.655,95%CI:1.285~10.393)是腹腔镜结直肠癌根治术患者麻醉恢复期停留时间延长的危险因素(P<0.05)。列线图模型预测麻醉恢复期停留时间延长的灵敏度为0.783(95%CI:0.701~0.843),特异度为0.800(95%CI:0.716~0.881),曲线下面积为0.821(95%CI:0.729~0.903)。列线图模型炎症麻醉恢复期停留时间延长的灵敏度为0.773(95%CI:0.702~0.839),特异度为0.794(95%CI:0.709~0.861),曲线下面积为0.806(95%CI:0.721~0.906)。结论年龄,合并慢性阻塞性肺疾病、静脉全麻、阿片类麻醉药物及术后发生低氧血症与腹腔镜结直肠癌根治术患者术后麻醉恢复期停留时间的延长有关,构建风险预测模型有助于早期筛查患者术后麻醉恢复期停留时间延长的风险。
Objective To investigate the influencing factors of prolonged recovery time in patients undergoing laparoscopic radical resection for colorectal cancer,constructing and validating a prediction model.Methods Retrospective analysis of medical records of 120 patients 435 who underwent laparoscopic radical resection for colorectal cancer at the Second People’s Hospital of Hefei from January 2021 to June 2023.According to the 80/20 rule,patients were randomly divided into training set(96 cases)and validation set(24 cases).Patients were classified into prolonged recovery time group(58 cases)and normal recovery time group(38 cases)based on postoperative anesthesia recovery time.Risk factors for prolonged recovery time in patients undergoing laparoscopic radical resection for colorectal cancer were screened,and a risk prediction model was constructed and validated.Results Among the 96 patients who underwent laparoscopic radical resection for colorectal cancer,38 cases(39.58%)had prolonged postoperative anesthesia recovery time,while 58 cases(60.42%)had a normal recovery time.The proportion of patients with comorbid chronic obstructive pulmonary disease,the use of intravenous general anesthesia during surgery,the use of opioid analgesics during surgery,and the occurrence of postoperative hypoxemia were higher in the prolonged recovery group compared with the normal group(P<0.05).Age(OR=3.861,95%CI:1.358~10.981),comorbid chronic obstructive pulmonary disease(OR=4.080,95%CI:1.435~11.601),intravenous general anesthesia(OR=3.892,95%CI:1.369~11.069),opioid analgesics(OR=4.267,95%CI:1.501~12.136),and postoperative hypoxemia(OR=3.655,95%CI:1.285~10.393)were identified as risk factors for prolonged anesthesia recovery time in patients undergoing laparoscopic radical resection for colorectal cancer(P<0.05).The receiver operating characteristic(ROC)curve analysis showed that the sensitivity of the Logistic regression model in predicting prolonged recovery time was 0.783(95%CI:0.701~0.843),specificity was 0.800(95%CI:0.716~0.881),and the area under the curve was 0.821(95%CI:0.729~0.903).The sensitivity of the Logistic regression model in predicting prolonged recovery time with inflammatory markers was 0.773(95%CI:0.702~0.839),specificity was 0.794(95%CI:0.709~0.861),and the area under the curve was 0.806(95%CI:0.721~0.906).Conclusion Age,comorbid chronic obstructive pulmonary disease,intravenous general anesthesia,opioid analgesics,and postoperative hypoxemia are associated with prolonged anesthesia recovery time in patients undergoing laparoscopic radical resection for colorectal cancer.The construction of a risk prediction model can help in the early screening of patients at risk of prolonged anesthesia recovery time after surgery.
作者
黄伶慧
鲍金凤
张婷婷
吴向群
王昕
何文胜
HUANG Ling-hui;BAO Jin-feng;ZHANG Ting-ting;WU Xiang-qun;WANG Xin;HE Wensheng(Department of Anesthesiology,Hefei Hospital Affiliated to Anhui Medical University(The 2nd Hospital of Hefei),Hefei 230012,China)
出处
《哈尔滨医科大学学报》
CAS
2024年第4期435-440,共6页
Journal of Harbin Medical University
基金
安徽省自然科学基金资助项目(2308085MH296)
2020年度安徽医科大学科研基金(2020xkj246)。
关键词
结直肠癌
腹腔镜手术
麻醉
术后恢复
影响因素
预测模型
colorectal cancer
laparoscopic surgery
anesthesia
postoperative recovery
influencing factors
prediction model