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McKeown食管癌术后呼吸衰竭的危险因素分析及预测模型建立 被引量:2

Risk factors and predictive model ofpostoperative respiratory failure after McKeown esophagectomy
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摘要 目的探讨McKeown食管癌术后呼吸衰竭发生的危险因素,建立临床预测模型,为早期临床干预提供依据。方法回顾性分析2020年1~12月在安徽省肿瘤医院胸外科行McKeown食管癌手术的261例患者的临床资料,其中男性患者203例,女性患者58例。结果261例患者中有13.00%(34/261)的患者发生术后呼吸衰竭。logistic回归分析显示,年龄(OR=1.078,P=0.015)、术中补液量(OR=1.001,P=0.032)、术后低蛋白血症(OR=4.501,P=0.001)、吻合口瘘(OR=7.101,P<0.001)、胸腔广泛粘连(OR=2.785,P=0.031)是McKeown食管癌术后呼吸衰竭发生的独立危险因素。并建立Nomogram预测模型。受试者工作特征曲线下面积为0.848(95%CI:0.772~0.925,P<0.001)。结论对于McKeown食管癌手术的患者,年龄越大、术中补液量越多、胸腔广泛粘连、伴有术后低蛋白血症及吻合口瘘,术后发生呼吸功能衰竭的风险越高。 Objective To investigate the risk factors andestablish a risk predictive model for postoperative respiratory failure after McKeown esophagectomyfor early clinical intervention.Methods We retrospectively reviewed 261 patients including 203 males and 58 females,who underwent McKeown esophagectomyintheDepartment of Thoracic Surgeryof Anhui Cancer Hospital from January 2020 to December 2020.Results Postoperative respiratory failure occurred in 13.00%of 261 patients(34/261).Logistic analysis revealed that age(OR=1.078,P=0.015),intraoperative fluid replenishment(OR=1.001,P=0.032),postoperative hypoproteinemia(OR=4.501,P=0.001),anastomostomy fistula(OR=7.101,P<0.001)and extensive pleural adhesion(OR=2.785,P=0.031)were independent risk factors for respiratory failure afterMcKeownesophagectomy.A predictive Nomogram model was established based on these factors.The area under the receiver operating characteristic curve was0.848(95%CI:0.772~0.925,P<0.001).Conclusions The patients with elder age,the more intraoperative fluid replenishment,extensive pleural adhesion,postoperative hypoproteinemia and anastomostomy fistula are prone to respiratory failure after McKeown esophagectomy.
作者 王开旺 张荣新 WANG Kaiwang;ZHANG Rongxin(Department of Thoracic Surgery,Anhui Cancer Hospital(the First Affiliated Hospital of University of Science and Technology of China),Hefei 230031,China)
出处 《安徽医学》 2022年第8期918-922,共5页 Anhui Medical Journal
关键词 食管癌 呼吸衰竭 危险因素 预测模型 Esophageal cancer Respiratory failure Risk factors Predictive model
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