重症监护病房脓毒症患者预后模型构建与评估  

Development and validation of a prognostic model for patients with sepsis in intensive care unit

作　　者：蒋子鸣 王洪亮 王素梅[2] 关纯[2] 曲彦[2] Jiang Ziming;Wang Hongliang;Wang Sumei;Guan Chun;Qu Yan(Dalian Medical University,Dalian 116000,Liaoning,China;Department of Critical Care Medicine,Qingdao Municipal Hospital,Qingdao 266000,Shandong,China)

机构地区：[1]大连医科大学,辽宁大连116000 [2]青岛市市立医院重症医学科,山东青岛266000

出　　处：《中华危重病急救医学》2023年第8期800-806,共7页Chinese Critical Care Medicine

基　　金：国家自然科学基金(81971873)。

摘　　要：目的:分析重症监护病房(ICU)脓毒症患者预后危险因素,构建列线图模型,并进行预测效能验证。方法:使用美国重症监护医学信息数据库Ⅳ〔MIMIC-Ⅳ(version 2.0)〕中的数据进行回顾性队列研究。收集符合Sepsis-3诊断标准的6 500例脓毒症患者的信息,包括人口学特征、合并症、入ICU 24 h内实验室指标、最终随访结局等资料。采用简单随机抽样法,按照7∶3的比例将患者分为训练集和验证集。采用限制性立方样条(RCS)分析各项变量与预后是否存在线性关系,将非线性关系的变量截断转换为分类变量;将所有变量使用LASSO回归进行筛选,并纳入多因素Cox回归模型,分析ICU脓毒症患者死亡危险因素,并构建列线图模型;采用一致性指数、校准曲线和受试者工作特征曲线(ROC曲线)评估列线图模型的预测效能;采用决策曲线分析(DCA)验证模型的临床价值及其对实际决策的影响。结果:6?500例脓毒症患者中,训练集4?551例,验证集1?949例。训练集28 d、90 d、1年病死率分别为27.73%(1?262/4?551)、34.76%(1?582/4?551)、42.98%(1?956/4?551),验证集分别为27.24%(531/1?949)、33.91%(661/1?949)、42.23%(823/1?949)。无论在训练集还是验证集,与最终存活患者比较,死亡患者年龄更大,序贯器官衰竭评分(SOFA)及简化急性生理学评分Ⅱ(SAPSⅡ)更高,合并症更多,尿量更少,使用血管活性药物、肾脏替代治疗及机械通气更多。经RCS分析将与脓毒症患者预后风险存在潜在非线性关联的变量转换为分类变量;将经过LASSO回归筛选后的变量纳入多因素Cox回归模型,结果显示,年龄〔风险比( HR)=1.021,95%可信区间(95% CI)为1.018~1.024〕、SOFA评分( HR=1.020,95% CI为1.000~1.040)、SAPSⅡ评分>44分( HR=1.480,95% CI为1.340~1.634)、平均动脉压(MAP)≤75 mmHg(1 mmHg≈0.133 kPa;HR=1.120,95% CI为1.026~1.222)、呼吸频率(RR;HR=1.044,95% CI为1.034~1.055)、脑血管病( HR=1.620,95% CI为1.443~1.818)、Objective To analyze the risk factors related to the prognosis of patients with sepsis in intensive care unit(ICU),construct a nomogram model,and verify its predictive efficacy.Methods A retrospective cohort study was conducted using data from Medical Information Mart for Intensive Care-Ⅳ0.4[MIMIC-Ⅳ(version 2.0)].The information of 6500 patients with sepsis who meet the diagnostic criteria of Sepsis-3 were collected,including demography characteristics,complications,laboratory indicators within 24 hours after ICU admission,and final outcome.Using a simple random sampling method,the patients were divided into a training set and a validation set at a ratio of 7∶3.The restricted cubic spline(RCS)was used to explore whether there was a linear relationship between each variable and the prognosis,and the nonlinear variables were truncated into categorical variables.All variables were screened by LASSO regression and included in multivariate Cox regression analysis to analyze the death risk factors in ICU patients with sepsis,and construct a nomograph.The consistency index,calibration curve and receiver operator characteristic curve(ROC curve)were used to evaluate the prediction efficiency of nomogram model.The decision curve analysis(DCA)was used to validate the clinical value of the model and its impact on actual decision-making.Results Among 6500 patients with sepsis,4551 were in the training set and 1949 were in the validation set.The 28-day,90-day and 1-year mortality in the training set were 27.73%(1262/4551),34.76%(1582/4551),and 42.98%(1956/4551),respectively,those in the validation set were 27.24%(531/1949),33.91%(661/1949),and 42.23%(823/1949),respectively.Both in training set and the validation set,compared with the final survival patients,the death patients were older,and had higher sequential organ failure assessment(SOFA)score and simplified acute physiology scoreⅡ(SAPSⅡ),more comorbidities,less urine output,and more use of vasoactive drugs,kidney replacement therapy,and mechanical ventilation.By

关 键 词：脓毒症 MIMIC-Ⅳ数据库 预后模型 LASSO回归 COX回归 

分 类 号：R459.7[医药卫生—急诊医学]