Objective: To determine the association between serum 25-hydroxyvitamin D (25(OH)D) and measures of glycemic control, hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG), in adult patients with diabetes mellitus. Methodology: This is an analytical cross-sectional study of 270 patients with diabetes admitted to a tertiary hospital. Serum 25(OH)D levels were categorized as follows: sufficient (>30 ng/mL), insufficient (20 to 30 ng/mL), and deficient (<20 ng/mL). The correlation of HbA1c and FPG with serum 25(OH)D and other variables was determined using Spearman’s rho (ρ) coefficient. The risk factors associated with HbA1c ≥7% and FPG ≥126 mg/dL were determined using logistic regression analysis to generate crude and adjusted odds ratios. The null hypothesis was rejected at 0.05 α-level of significance. Results: The median serum 25(OH)D was 18.92 (range 3.56–56.3) ng/mL. Ninety percent (245 patients) had vitamin D levels below 30 ng/mL. This study showed that vitamin D level is significantly but weakly correlated with patient’s age (ρ=0.339) and duration of diabetes (ρ=0.147), whereas it had inverse correlations with BMI (ρ=-0.134), HbA1c (ρ=-0.261), and FPG (ρ=-0.198). Conclusion In this study, we found a possible association between vitamin D levels and measures of glycemic control among this group of adult Filipino patients with diabetes mellitus, but further investigations in other cohorts of individuals with diabetes are needed.
Vitamin D ; diabetes mellitus ; glycemic control

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.
Diabetes Mellitus, Type 2 ; COVID-19