Glycemic gap as a predictor of adverse outcomes in patients with Type 2 Diabetes Diagnosed with COVID-19 in a tertiary hospital in Metro Manila: A retrospective cohort study

ABSTRACT

Background@#Although elevated glucose levels are associated with adverse outcomes in the critically ill, HbA1c-based adjusted glycemic variables have not been extensively utilized as a tool to evaluate patients in the acute critical condition.@*Objective@#This study aims to determine whether glycemic gap can predict adverse outcomes in patients with type 2 diabetes diagnosed with COVID-19.@*Methodology@# A single center and retrospective study of adult patients with type 2 diabetes diagnosed with COVID- 19. Glycemic gap was calculated as the difference between the admission blood glucose and A1c‐derived average glucose. Logistic regression was used to determine association of glycemic gap and several adverse clinical outcomes. A decision curve analysis was used to determine the clinical utility of a clinical decision model based on this cut-off.@*Results@#A total of 150 diabetic patients with COVID-19 were analyzed. Median baseline HbA1c was 7.5% (range 4.79–18.42), while median admitting blood glucose was 196 (range 71–506) mg/dL. From these, computed glycemic gaps ranged from -180.5 to 312.8 mg/dL, with a median of 13.75 mg/dL. On univariate analysis, for every unit increase in glycemic gap, odds of developing ARDS increased five times (cOR 4.798, 95% CI 2.08 to 11.09); odds of developing shock increased four times (cOR 4.48, 95% CI 1.48 to 13.44). No single cut-off value for glycemic gap was able to discriminate patients with favorable outcome from those with adverse outcome. The decision curve analysis graphically shows that glycemic gap has a positive net benefit for threshold risk of 50% or higher.@*Conclusion@#Higher glycemic gaps were significantly associated with increased risk for poor outcomes in diabetic patients with COVID-19. Glycemic gap should be correlated with clinical status and other laboratory parameters to make it a more powerful discriminant among COVID-19 infected patients.