在线动态列线图可视化分析脓毒症患者发生急性肾损伤的预测模型:开发与验证应用研究  

Visualization analysis of predictive model of acute kidney injury in patients with sepsis by online dynamic nomogram:research on development and validation of application

作　　者：李静[1] 孟润祺 郭鲁恒 谷琳琳[1] 郝翠萍 师猛[1] Li Jing;Meng Runqi;Guo Luheng;Gu Linlin;Hao Cuiping;Shi Meng(Department of Emergency,the Affiliated Hospital of Jining Medical University,Jining 272100,Shandong,China;Department of Emergency,Jinan Central Hospital,Jinan 250000,Shandong,China;Department of Critical Care Medicine,the Affiliated Hospital of Jining Medical University,Jining 272100,Shandong,China)

机构地区：[1]济宁医学院附属医院急诊科,山东济宁272100 [2]济南市中心医院急诊科,山东济南250000 [3]济宁医学院附属医院重症医学科,山东济宁272100

出　　处：《中华危重病急救医学》2024年第10期1069-1074,共6页Chinese Critical Care Medicine

基　　金：山东省济宁市重点研发计划项目(2021JNZC016)。

摘　　要：目的分析脓毒症患者发生脓毒性急性肾损伤(sAKI)的危险影响,构建sAKI预测模型并验证模型预测价值,开发动态列线图,帮助临床医生及早且更容易识别sAKI高风险患者。方法采用横断面研究方法,选择2013年5月至2023年11月济宁医学院附属医院重症监护病房(ICU)收治的245例脓毒症患者作为研究对象。根据患者ICU住院期间是否发生sAKI分为sAKI组和非sAKI组,比较两组患者人口统计学、临床和实验室数据;将两组间不均衡变量纳入Logistic逐步回归分析,并建立sAKI预测模型。通过5折交叉验证、校准曲线和决策曲线分析(DCA)评价sAKI预测模型的预测价值,并开发模型的在线动态列线图。结果245例患者均纳入最终分析,其中110例(44.9%)在ICU住院期间发生sAKI,135例(55.1%)未发生sAKI。与非sAKI组比较,sAKI组患者女性、高血压、有创机械通气(IMV)、肾脏替代治疗(RRT)、使用血管加压药比例及中性粒细胞计数(NEU)、天冬氨酸转氨酶(AST)、血尿素氮(BUN)、血肌酐(SCr)、尿酸(UA)、Na+、K+、降钙素原(PCT)、急性生理学与慢性健康状况评分Ⅱ(APACHEⅡ)、序贯器官衰竭评分(SOFA)更高;多因素Logistic逐步回归分析显示,女性〔优势比(OR)=2.208,95%可信区间(95%CI)为1.073~4.323,P=0.020〕、高血压(OR=2.422,95%CI为1.255~5.073,P=0.012)、使用血管加压药(OR=2.888,95%CI为1.380~6.679,P=0.002)和SCr(OR=1.015,95%CI为1.009~1.024,P<0.001)是脓毒症患者发生sAKI的独立危险因素,并构建sAKI预测模型:ln〔P/(1+P)〕=-4.665+0.792×女性+0.885×高血压+1.060×使用血管加压药+0.015×SCr。5折交叉验证显示,每次验证集受试者工作特征曲线下面积(AUC)的平均值为0.860,说明sAKI预测模型的效能较好;校准曲线分析显示,sAKI预测模型的校准度较好;DCA显示,sAKI预测模型的净收益较高。分别制作sAKI预测模型的静态列线图和在线动态列线图;与静态列线图相比,动态列线图可手动选�Objective To explore the risk factors of septic acute kidney injury(sAKI)in patients with sepsis,construct a predictive model for sAKI,verify the predictive value of the model,and develop a dynamic nomogram to help clinical doctors identify patients with high-risk sAKI earlier and more easily.Methods A cross-sectional study was conducted.A total of 245 patients with sepsis admitted to intensive care unit(ICU)of the Affiliated Hospital of Jining Medical University from May 2013 to November 2023 were enrolled as the research subjects.The patients were divided into sAKI group and non-sAKI group based on whether they suffered from sAKI during ICU hospitalization.The differences of the demographic,clinical and laboratory indicators of patients between the two groups were compared.Logistic ordinal regression analysis was performed to analyze the imbalanced variables between the two groups,and to construct a sAKI predictive model.The predictive value of the sAKI predictive model was evaluated through 5-fold cross validation,calibration curve,and decision curve analysis(DCA),and to develop an online dynamic nomogram for the predictive model.Results A total of 245 patients were enrolled in the final analysis.110(44.9%)patients developed sAKI during ICU hospitalization and 135(55.1%)patients did not develop sAKI.Compared with the non-sAKI group,the patients in the sAKI group had higher ratios of female,hypertension,invasive mechanical ventilation(IMV),renal replacement therapy(RRT),vasopressin usage,and neutrophil count(NEU),aspartate aminotransferase(AST),blood urea nitrogen(BUN),serum creatinine(SCr),uric acid(UA),Na+,K+,procalcitonin(PCT),acute physiology and chronic health evaluationⅡ(APACHEⅡ)score,and sequential organ failure assessment(SOFA)score.Multivariate Logistic ordinal regression analysis showed that female[odd ratio(OR)=2.208,95%confidence interval(95%CI)was 1.073-4.323,P=0.020],hypertension(OR=2.422,95%CI was 1.255-5.073,P=0.012),vasopressin usage(OR=2.888,95%CI was 1.380-6.679,P=0.002),and SCr(OR=1.015,

关 键 词：在线动态列线图 可视化分析 脓毒症 急性肾损伤 预测模型 

分 类 号：R459.7[医药卫生—急诊医学] R692[医药卫生—治疗学]