The association between stress hyperglycemia ratio with mortality in critically ill patients with acute heart failure

Background: It's recognized that stress hyperglycemia ratio (SHR) is considered a significant indicator of poor prognosis in many diseases. However, its role in critically ill patients with acute heart failure (acute HF) remains underexplored.

Methods: We conducted a retrospective cohort study on patients with acute HF included in the Medical Information Mart for Intensive Care IV (MIMIC-IV) version 2.2 database. A restricted cubic spline (RCS) regression analysis was used to explore the relationship between SHR and the risk of all-cause mortality in these patients. Subsequently, a Cox regression model was used to evaluate the relationship between SHR and mortality in acute HF patients.

Results: A total of 1,644 acute HF patients were included in the study and divided into two groups: the low SHR group (SHR < 1.06, N = 823) and the high SHR group (SHR ≥ 1.06, N = 821). In our study, the 30-day, 90-day, 180-day, and 365-day mortality rates for acute HF were 7.0%, 12%, 15%, and 19%, respectively, with higher mortality rates observed in the high SHR group compared to the low SHR group. SHR levels showed a linear relationship with all-cause mortality. Furthermore, SHR as a continuous variable shows a significant positive correlation with 30-day (HR = 2.31, 95% CI: 1.58-3.39), 90-day (HR = 1.81, 95% CI: 1.31-2.52), 180-day (HR = 1.57, 95% CI: 1.16-2.12), and 365-day (HR = 1.41, 95% CI: 1.07-1.85) all-cause mortality. After categorization, high SHR remains associated with increased 30-day (HR = 2.4, 95% CI: 1.59-3.61), 90-day (HR = 1.76, 95% CI: 1.31-2.36), 180-day (HR = 1.51, 95% CI: 1.16-1.95), and 365-day (HR = 1.38, 95% CI: 1.09-1.73) all-cause mortality.

Conclusion: Our findings indicate that high SHR is an independent predictor of poor short- and long-term prognosis in acute HF patients. Understanding the impact of SHR on mortality in acute HF is crucial as it can assist clinicians in identifying high-risk patients and adjusting treatment strategies accordingly.