Uric acid to albumin ratio is a novel predictive marker for all-cause and cardiovascular death in diabetic patients: a prospective cohort study - Chen, Shengnan; Zhang, Ming; Hu, Shouye; Shao, Xiaolong; Liu, Lin; Yang, Zhi; Nan, Kai (Frontiers in Endocrinology, 2025)
BackgroundDiabetes is one of the leading causes of death with an increasing prevalence worldwide. Diabetes-related premature mortality is largely preventable and reversible if identified and managed early. Accordingly, we intend to investigate the predictive value of uric acid to albumin ratio (UAR) for all-cause and cardiovascular death in diabetic patients.MethodsUnivariate and multivariate Cox regression analyses were performed to identify risk factors for all-cause death of diabetic patients. The receiver operating characteristic (ROC) curves and nomogram model were used to evaluate the predictive ability of variables. Kaplan-Meier survival analysis was used to display the progression risks of diabetic patients.ResultsA total of 804 diabetic patients were enrolled in the study. During the 5-year follow-up, all-cause death was found in 80 participants (9.95%) and cardiovascular death was found in 24 participants (2.99%). Age, UAR, and hsCRP were independent risk factors for all-cause death in diabetic patients after adjusting for potential confounding factors. Age and UAR had good predictive value for 1-, 3-, and 5-year all-cause death in diabetic patients, and the combination of UAR and age had the highest predictive value. An easy and intuitive prognostic nomogram model with good predictive accuracy was constructed based on age and UAR. Patients in higher quantiles of age and UAR had more rapid progression to all-cause death and higher mortality risk than patients in the lower quantiles. UAR also had good predictive value for cardiovascular death in diabetic patients.ConclusionsUAR may be a simple, cost-effective, and reliable predictive marker for all-cause and cardiovascular death in U.S. diabetic patients. The clinical utility of UAR and nomogram based on age and UAR can help physicians identify individuals at higher risk and therefore promote prevention strategies.