维持性血液透析患者重症新型冠状病毒感染发病风险感知与客观估算风险模型的构建  

Construction of Risk Perception and Objective Risk Estimation Model for Severe Corona Virus Disease 2019 in Maintenance Hemodialysis Patients

作　　者：邱琳蕊 陈梅梅 QIU Linrui;CHEN Meimei(Nephrology Department of Longyan People’s Hospital in Fujian Province,Longyan City,Fujian Province 364000)

机构地区：[1]福建省龙岩人民医院肾病学科,福建省龙岩市364000

出　　处：《医学理论与实践》2023年第23期3968-3971,共4页The Journal of Medical Theory and Practice

基　　金：龙岩市科技计划项目(2022LYF17017)。

摘　　要：目的:分析维持性血液透析患者(MHD)发生重症新型冠状病毒感染(COVID-19)的危险因素,并基于危险因素构建客观估算风险预测模型。方法:将258例MHD确诊COVID-19患者分为重症组和非重症组。分析所选研究对象的临床资料,通过单因素和二元Logistic回归分析筛选出MHD发生重症COVID-19的独立危险因素,采用R软件构建客观估算风险预测模型。结果:258例MHD确诊COVID-19患者重症检出率为20.54%(53/258);BMI增高、空腹血糖增高、血小板计数减少、血C反应蛋白增高、淋巴细胞百分比下降、谷草转氨酶增高、肌酸激酶同工酶增高是MHD患者发生重症COVID-19的独立危险因素(P<0.05);列线图模型验证结果显示C-index为0.983,H-L拟合优度检验为χ^(2)=12.436,P=0.078,校正曲线趋近于理想曲线,ROC曲线下面积为0.857。结论:本文构建的列线图预测模型准确性较高,这使得医护人员能够快速发现和识别可能存在的高危患者,有助于推动个体化医疗发展。Objective:To analyze the risk factors for severe corona virus disease 2019 in maintenance hemodialysis patients,and to construct an objective estimation risk prediction model based on the risk factors.Methods:258 MHD confirmed COVID-19 patients were divided into severe group and non-severe group.The clinical data of the selected subjects were analyzed,and the independent risk factors for severe COVID-19 in MHD were screened out through univariate and binary Logistic regression analysis,and R software was used to construct an objective estimation risk prediction model.Results:The severe detection rate of 258 MHD confirmed COVID-19 patients was 20.54%(53/258);increased BMI,increased fasting blood sugar,decreased platelet count,increased blood C-reactive protein,decreased lymphocyte percentage,increased aspartate aminotransferase,and creatine kinase increased isoenzyme were independent risk factors for severe COVID-19 in MHD patients(P<0.05);the nomogram model validation results showed that the C-index was 0.983,and the H-L goodness-of-fit test wasχ^(2)=12.436,P=0.078.The calibration curve approaches the ideal curve,and the area under the ROC curve is 0.857.Conclusion:The nomogram prediction model constructed in this article has high accuracy,which allows medical staff to quickly discover and identify possible high-risk patients,helping to promote the development of personalized medicine.

关 键 词：维持性血液透析 新型冠状病毒感染 重症 客观估算风险模型 列线图 

分 类 号：R563.1[医药卫生—呼吸系统]