Association between glycemic variability and mortality in critically ill patients with heart failure - Pengcheng Liu; Ziqi Li; Shanshan Tang; Weiguang Dou; Yuanyuan Liu (Scientific Reports)
Abstract Heart failure is a significant global health challenge with high mortality rates. This study examines the association between glycemic variability and short-term mortality in critically ill heart failure patients. Data from the eICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care (MIMIC-IV) database were analyzed, including 23,744 heart failure patients. Glycemic variability, measured by the coefficient of variation of glucose levels during ICU stay, was categorized into quartiles. Multivariable logistic regression and Cox proportional hazards models were used to assess associations with in-hospital and 30-day mortality. Linear regression models were employed to evaluate the association with ICU length of stay. Dose-response relationships were explored using restricted cubic splines. The in-hospital and 30-day mortality rates were 15.0% and 17.6%, respectively. The median ICU length of stay was 3.1 days (IQR: 1.9–5.4). Patients in the highest glycemic variability quartile had a significantly higher risk of in-hospital mortality (OR: 1.77, 95% CI: 1.54–2.04) and 30-day mortality (HR: 1.37, 95% CI: 1.23–1.53) compared to the lowest quartile. Additionally, higher glycemic variability was associated with prolonged ICU stays, with each unit increase resulting in a 2.57-day extension (95% CI: 2.03–3.10, P < 0.001) after adjustment for covariates. A U-shaped association was observed for in-hospital mortality, while a linear relationship was seen for 30-day mortality. Sensitivity and subgroup analyses confirmed the robustness of these findings. Elevated glycemic variability is independently associated with increased short-term mortality and prolonged ICU stays in critically ill heart failure patients, highlighting the importance of managing blood glucose fluctuations to improve outcomes and reduce healthcare resource utilization.