加速康复外科模式下食管癌根治术后患者出院准备度影响因素分析及预测模型构建

Analysis of influencing factors and predictive model construction of discharge readiness of patients after radical resection of esophageal cancer under enhanced recovery after surgery mode

目的探讨加速康复外科(ERAS)模式下食管癌根治术后患者出院准备度影响因素,并进行预测模型探索。方法采用便利抽样方法,于2019年1月—2020年4月选取河南省某医院胸外科收治的195例食管癌患者为研究对象。在患者出院时,采用一般情况和疾病相关资料收集表、出院准备度量表、安德森癌症消化道症状调查量表(MDASI-GI)、衰弱问卷式评分、起立行走计时试验(TUGT)及洼田饮水试验进行调查。采用多因素非条件Logistic回归分析进行影响因素分析。本研究共发放问卷195份,回收有效问卷189份。结果血浆白蛋白水平、24 h进食量、MDASI-GI和TUGT是食管癌根治术后患者出院准备度的独立预测因素(P<0.05)。最终得到患者术后出院准备度预测模型为:Y=-3×X1+1×X2+5×X3-4×X4-1×X5(Y=出院准备度;X1=疼痛评分,X2=血浆白蛋白,X3=24 h进食量,X4=MDASI,X5=TUGT)。结论ERAS模式下食管癌患者术后出院准备度受多种因素影响,出院评估预测模型效能较好,可为临床出院决策提供参考。

Objective To explore the influencing factors of discharge readiness of patients after radical resection of esophageal cancer under enhanced recovery after surgery(ERAS)model and to explore the prediction model.Methods Using the convenient sampling method,a total of 195 patients with esophageal cancer who were admitted to the department of thoracic surgery in a hospital in Henan Province from January 2019 to April 2020 were selected as the research objects.At discharge,the general and disease-related data collection form,Readiness for Hospital Discharge Scale,M.D.Anderson Symptom Inventory Gastrointestinal(MDAS-GI),Frail Scale,Time Up and Go Test(TUGT)and Water Swallow Test were used to investigate.Multivariate unconditional Logistic regression analysis was used to analyze influencing factors.A total of 195 questionnaires were distributed in this study,and 189 valid questionnaires were collected.Results Plasma albumin level,24-hour food intake,MDASI-GI and TUGT were independent predictors of the readiness for discharge of patients after radical resection of esophageal cancer(P<0.05).Finally,the prediction model of postoperative discharge readiness for patients was Y=-3×X1+1×X2+5×X3-4×X4-1×X5(Y=discharge readiness;X1=pain score,X2=plasma albumin,X3=24 h food intake,X4=MDASI,X5=TUGT).Conclusions The readiness for discharge of patients with esophageal cancer under the ERAS mode is affected by many factors,and the prediction model of discharge assessment is effective,which can provide reference for clinical discharge decision-making.