Abstract TP032: Association Between Stroke-Associated Pneumonia and Glycemic Variability in Acute Ischemic Stroke Patients

Introduction: Stroke-associated pneumonia (SAP) is the most common infectious complication following acute ischemic stroke (AIS). During the acute phase of stroke, patients often experience stress-induced hyperglycemia, resulting in elevated and fluctuating blood glucose (BG) levels. This study aimed to investigate the association between SAP and various glycemic parameters, including both BG levels and glycemic variability, in patients with AIS. Methods: We retrospectively analyzed consecutive AIS patients admitted between 2017 and 2018 who had their BG levels measured at least four times per day during the first five days of hospitalization. SAP was defined based on modified Centers for Disease Control and Prevention criteria. Glycemic metrics analyzed included mean BG, standard deviation (SD), coefficient of variation (CV), hyperglycemia ratio (BG >180 mg/dL), and mean amplitude of glycemic excursion (MAGE). Results: A total of 297 AIS patients were included. In multivariable logistic regression analysis, higher mean BG was independently associated with increased risk of SAP (adjusted odds ratio [aOR] = 1.02; 95% confidence interval [CI]: 1.01–1.04). Other independent predictors of SAP included older age, dysphagia, higher initial NIHSS score, elevated white blood cell count, and lower serum albumin levels. Among glycemic variability parameters, higher BG SD (aOR = 1.03; 95% CI: 1.01–1.05), increased hyperglycemia ratio (aOR = 1.03; 95% CI: 1.01–1.05), and elevated MAGE (aOR = 1.02; 95% CI: 1.00–1.03) were also significantly associated with SAP after adjustment for confounders. Conclusions: Our findings suggest that not only elevated mean BG but also greater glycemic variability are independently associated with the development of SAP in AIS patients. These results underscore the importance of close glucose monitoring and stringent glycemic control during the acute phase of stroke to potentially reduce the risk of SAP.