Association of dynamic change of triglyceride-glucose index during hospital stay with all-cause mortality in critically ill patients: a retrospective cohort study from MIMIC IV2.0

作者全名："Cheng, Long; Zhang, Feng; Xue, Wenjing; Yu, Peng; Wang, Xiaoyan; Wang, Hairong; Wang, Jun; Hu, Tianyang; Gong, Hui; Lin, Li"

作者地址："[Cheng, Long; Zhang, Feng; Xue, Wenjing; Gong, Hui] Fudan Univ, Dept Cardiol, Jinshan Hosp, Shanghai, Peoples R China; [Yu, Peng] Shanghai Punan Hosp Pudong New Dist, Punan Branch Renji Hosp, Dept Urol, 279 Linyi Rd, Shanghai 200000, Peoples R China; [Wang, Xiaoyan] Shanghai Jiao Tong Univ, Ruijin Hosp, Inst Cardiovasc Dis, Sch Med, Shanghai, Peoples R China; [Wang, Hairong] Shanghai Pudong New Area Gongli Hosp, Dept Cardiovasc Med, Shanghai 200000, Peoples R China; [Wang, Jun] First Peoples Hosp Yancheng, Dept Neurol, Yulong Western Rd, Yancheng 224006, Jiangsu, Peoples R China; [Hu, Tianyang] Chongqing Med Univ, Affiliated Hosp 2, Precis Med Ctr, Chongqing, Peoples R China; [Lin, Li] Tongji Univ, Shanghai East Hosp, Sch Med, Dept Cardiovasc Med, Jimo Rd 150, Shanghai 200120, Peoples R China"

通信作者："Lin, L (通讯作者)，Tongji Univ, Shanghai East Hosp, Sch Med, Dept Cardiovasc Med, Jimo Rd 150, Shanghai 200120, Peoples R China."

来源：CARDIOVASCULAR DIABETOLOGY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001007227000001

JCR分区：Q1

影响因子：8.5

年份：2023

卷号：22

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Triglyceride-glucose index; Intensive care unit; All-cause mortality; MIMIC-IV database

摘要："BackgroundBiomarker of insulin resistance, namely triglyceride-glucose index, is potentially useful in identifying critically ill patients at high risk of hospital death. However, the TyG index might have variations over time during ICU stay. Hence, the purpose of the current research was to verify the associations between the dynamic change of the TyG index during the hospital stay and all-cause mortality.MethodsThe present retrospective cohort study was conducted using the Medical Information Mart for Intensive Care IV 2.0 (MIMIC-IV) critical care dataset, which included data from 8835 patients with 13,674 TyG measurements. The primary endpoint was 1-year all-cause mortality. Secondary outcomes included in-hospital all-cause mortality, the need for mechanical ventilation during hospitalization, length of stay in the hospital. Cumulative curves were calculated using the Kaplan-Meier method. Propensity score matching was performed to reduce any potential baseline bias. Restricted cubic spline analysis was also employed to assess any potential non-linear associations. Cox proportional hazards analyses were performed to examine the association between the dynamic change of TyG index and mortality.ResultsThe follow-up period identified a total of 3010 all-cause deaths (35.87%), of which 2477 (29.52%) occurred within the first year. The cumulative incidence of all-cause death increased with a higher quartile of the TyGVR, while there were no differences in the TyG index. Restricted cubic spline analysis revealed a nearly linear association between TyGVR and the risk of in-hospital all-cause mortality (P for non-linear = 0.449, P for overall = 0.004) as well as 1-year all-cause mortality (P for non-linear = 0.909, P for overall = 0.019). The area under the curve of all-cause mortality by various conventional severity of illness scores significantly improved with the addition of the TyG index and TyGVR. The results were basically consistent in subgroup analysis.ConclusionsDynamic change of TyG during hospital stay is associated with in-hospital and 1-year all-cause mortality, and may be superior to the effect of baseline TyG index."

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