Wang Youquan, Li Yanhua, Zhang Yuhan, Wang Huimei, Li Yuting, Zhang Liying, Zhang Chaoyang, Gao Meng, Li Hongxiang, Zhang Dong
Department of Critical Care Medicine, The First Hospital of Jilin University, Changchun, China.
Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China.
Front Nutr. 2024 Oct 10;11:1469870. doi: 10.3389/fnut.2024.1469870. eCollection 2024.
Developing and validating a clinical prediction nomogram of 28-day mortality in critically ill patients with acute gastrointestinal injury (AGI).
Firstly, the construction of a clinical prediction model was developed using data obtained from a prospective observational study from May 2023 to April 2024. Then, data from a prospective multicenter observational study conducted in the intensive care units of 12 teaching hospitals in 2014 were utilized to independently and externally validate the clinical prediction model developed in the first part. We first screened the covariates of the development cohort by univariate cox regression, and then carried out cox regression analysis on the development cohort by backward stepwise regression to determine the optimal fitting model. Subsequently, a nomogram was derived from this model.
A total of 1102 and 379 patients, 28-day mortality occurred in 20.3% and 15.8% of patients respectively, were included in the development and validation cohort, respectively. We developed a nomogram in critically ill patients with AGI and the AGI grade, APACHE II score, Mechanical ventilation (MV), Feeding intolerance (FI) and daily calorie intake (DCI) in 72 h, were independent predictors of 28-day mortality, with the OR of the AGI grade was 1.910 (95% , 1.588-2.298; < 0.001), the of APACHE II score was 1.099 (95% , 1.069-1.130; < 0.001), the of MV was 1.880 (95% , 1.215-2.911; = 0.005), the of FI was 3.453 (95% , 2.414-4.939; < 0.001) and the DCI > 0.7 or < 0.5 of calorie target is associated with increased 28-day mortality, with of 1.566 (95% , 1.024-2.395; = 0.039) and 1.769 (95% , 1.170-2.674; = 0.007), respectively. Independent external validation of the prediction model was performed. This model has good discrimination and calibration. The DCA and CIC also validated the good clinical utility of the nomogram.
The prediction of 28-day mortality can be conveniently facilitated by the nomogram that integrates AGI grade, APACHE II score, MV, FI and DCI in 72 h in critically ill patients with AGI.
建立并验证急性胃肠损伤(AGI)危重症患者28天死亡率的临床预测列线图。
首先,利用2023年5月至2024年4月前瞻性观察性研究获得的数据构建临床预测模型。然后,利用2014年在12家教学医院重症监护病房进行的前瞻性多中心观察性研究数据,对第一部分建立的临床预测模型进行独立外部验证。我们首先通过单因素cox回归筛选开发队列的协变量,然后对开发队列进行向后逐步回归的cox回归分析,以确定最佳拟合模型。随后,从该模型导出列线图。
开发队列和验证队列分别纳入1102例和379例患者,28天死亡率分别为20.3%和15.8%。我们在AGI危重症患者中建立了一个列线图,AGI分级、急性生理与慢性健康状况评分系统II(APACHE II)评分、机械通气(MV)、喂养不耐受(FI)和72小时每日卡路里摄入量(DCI)是28天死亡率的独立预测因素,AGI分级的比值比(OR)为1.910(95%,1.588 - 2.298;P < 0.001),APACHE II评分的OR为1.099(95%,1.069 - 1.130;P < 0.001),MV的OR为1.880(95%,1.215 - 2.911;P = 0.005),FI的OR为3.453(95%,2.414 - 4.939;P < 0.001),DCI > 0.7或 < 0.5卡路里目标与28天死亡率增加相关,OR分别为1.566(95%,1.024 - 2.395;P = 0.039)和1.769(95%,1.170 - 2.674;P = 0.007)。对预测模型进行了独立外部验证。该模型具有良好的区分度和校准度。决策曲线分析(DCA)和一致性指数(CIC)也验证了列线图良好的临床实用性。
整合AGI分级、APACHE II评分、MV、FI和72小时DCI的列线图可方便地预测AGI危重症患者的28天死亡率。