Association between glucose-to-lymphocyte ratio and in-hospital mortality in acute myocardial infarction patients

BackgroundInflammation is involved in the development and progression of atherosclerosis. Recent studies indicated that glucose-to-lymphocyte ratio (GLR) level were significantly associated with the risk of mortality from inflammatory diseases, and showed a specific prognostic value. Herein, this study intended to explore the association between GLR level and in-hospital mortality in patients with acute myocardial infarction (AMI), and evaluate the predictive value of GLR on AMI prognosis.MethodsData of patients with AMI were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database in 2012-2019 in this retrospective cohort study. Univariate COX proportional hazard model was used to screen covariates. The associations between GLR and in-hospital mortality were evaluated using univariate and multivariate COX proportional hazard models. Subgroup analysis of age, gender, vasopressor use, SOFA scores, renal replacement therapy, coronary artery bypass graft, and beta blockers use were performed. The evaluated index was hazard ratios (HRs) and 95% confidence intervals (CIs). In addition, the predictive performance of GLR, glucose, and lymphocytes on in-hospital mortality was assessed respectively.ResultsAmong eligible patients, 248 (13.74%) died in the hospital. After adjusting for covariates, we found that a higher GLR level was associated with an increased risk of in-hospital mortality [HR = 1.70, 95%CI: (1.24-2.34)]. This relationship was also found in patients who were male, aged >= 65 years old, did not have renal replacement therapy, coronary artery bypass graft, or beta blockers, used vasopressor or not, and whatever the SOFA scores (all P<0.05). Moreover, the predictive performance of GLR on in-hospital mortality seemed superior to that of glucose or lymphocytes.ConclusionGLR may be a potential predictor for AMI prognosis, which provided some references for identifying and managing high-risk populations early in clinical.