Predicting the impact of stress-induced hyperglycemia on in-hospital mortality in patients with chronic kidney disease and acute coronary syndrome: A retrospective study.

BACKGROUND

Stress hyperglycemia is prevalent in critical illnesses and has been associated with adverse short- and long-term outcomes in individuals with acute coronary syndrome (ACS). However, there is limited evidence for the predictive value of stress hyperglycemia and hospitalization mortality in patients with chronic kidney disease (CKD) and ACS. This study aimed to explore the association between hospitalized mortality, stress hyperglycemia ratio (SHR), and admission blood glucose (ABG) in patients with CKD and ACS.

METHODS

This study included 655 hospitalized patients who were diagnosed with ACS and CKD. Patients with incomplete data were excluded, resulting in the analysis of 550 patients. The primary outcome measured was in-hospital mortality.

RESULTS

The median age of the cohort included in the analysis was 71 years, with a male proportion of 66.2 %, and a mean estimated glomerular filtration rate (eGFR) of 27.8 mL/min/1.73 m. Patients classified as having stage 3, stage 4, and stage 5 chronic kidney disease (CKD) comprised 46.9 %, 17.1 %, and 36.0 % of the population, respectively. The overall in-hospital mortality rate was 10.7 % (n = 59). Both SHR (OR = 2.67; 95 % CI 1.51-4.74; p < 0.001) and ABG (OR = 1.09; 95 % CI 1.04-1.14; p < 0.001) were significantly associated with in-hospital mortality in CKD and ACS patients. SHR and ABG showed a linear relationship with in-hospital mortality, with SHR demonstrating superior reclassification ability over ABG. The inclusion of SHR or ABG, irrespective of diabetes mellitus status, substantially enhanced the predictive performance of the Global Registry of Acute Coronary Events (GRACE) score model.

CONCLUSIONS

In patients with ACS and CKD, a robust correlation was observed between SHR, ABG, and in-hospital mortality. Both SHR and ABG improved the predictive accuracy of the GRACE score in forecasting inpatient mortality in this population.