预测脓毒症合并冠状动脉疾病患者28天死亡率的列线图:基于MIMIC-III数据库的回顾性研究
A nomogram to predict 28-day mortality in patients with sepsis combined coronary artery disease: retrospective study based on the MIMIC-III database.
作者信息
Gu Quankuan, Huang Ping, Yang Qiuyue, Meng Xianglin, Zhao Mingyan
机构信息
Department of Critical Care Medicine, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang Province, China.
Heilongjiang Provincial Key Laboratory of Critical Care Medicine, Harbin, Heilongjiang Province, China.
出版信息
Front Med (Lausanne). 2024 Sep 4;11:1433809. doi: 10.3389/fmed.2024.1433809. eCollection 2024.
OBJECT
Establish a clinical prognosis model of coronary heart disease (CHD) to predict 28-day mortality in patients with sepsis.
METHOD
The data were collected retrospectively from septic patients with a previous history of coronary heart disease (CHD) from the Medical Information Mart for Intensive Care (MIMIC)-III database. The included patients were randomly divided into the training cohorts and validation cohorts. The variables were selected using the backward stepwise selection method of Cox regression, and a nomogram was subsequently constructed. The nomogram was compared to the Sequential Organ Failure Assessment (SOFA) model using the C-index, area under the receiver operating characteristic curve (AUC) over time, Net reclassification index (NRI), Integrated discrimination improvement index (IDI), calibration map, and decision curve analysis (DCA).
RESULT
A total of 800 patients were included in the study. We developed a nomogram based on age, diastolic blood pressure (DBP), pH, lactate, red blood cell distribution width (RDW), anion gap, valvular heart disease, peripheral vascular disease, and acute kidney injury (AKI) stage. The nomogram was evaluated using C-index, AUC, NRI, IDI, calibration plot, and DCA. Our findings revealed that this nomogram outperformed the SOFA score in predicting 28-day mortality in sepsis patients.
目的
建立冠心病(CHD)临床预后模型,以预测脓毒症患者的28天死亡率。
方法
回顾性收集医学重症监护信息数据库(MIMIC)-III中既往有冠心病病史的脓毒症患者的数据。将纳入的患者随机分为训练队列和验证队列。采用Cox回归的向后逐步选择法选择变量,随后构建列线图。使用C指数、随时间变化的受试者操作特征曲线下面积(AUC)、净重新分类指数(NRI)、综合判别改善指数(IDI)、校准图和决策曲线分析(DCA)将列线图与序贯器官衰竭评估(SOFA)模型进行比较。
结果
本研究共纳入800例患者。我们基于年龄、舒张压(DBP)、pH值、乳酸、红细胞分布宽度(RDW)、阴离子间隙、瓣膜性心脏病、外周血管疾病和急性肾损伤(AKI)分期建立了列线图。使用C指数、AUC、NRI、IDI、校准图和DCA对列线图进行评估。我们的研究结果表明,该列线图在预测脓毒症患者的28天死亡率方面优于SOFA评分。