The Influence of COVID-19 in Glycemic Control: Predictive Value of Inflammation and Metabolic Parameters

Background/Objectives: Predicting post-COVID-19 diabetes is crucial for enhancing patient care and public health. This study investigates the role of metabolic factors in predicting the glycemic outcomes in patients recovering from moderate to severe COVID-19. Methods: We conducted a retrospective analysis of 135 patients without pre-existing diabetes, selected from a cohort of 1980 individuals hospitalized between January 2020 and December 2022. Metabolic parameters, including blood glucose, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), Triglyceride/Glucose (TyG) index, and high-sensitivity C-reactive protein (hs-CRP), were assessed at discharge and followed up after 4 months (T4) and 12 months (T12). Results: Statistical analysis revealed significant correlations of initial glycemia, HOMA-IR, and hs-CRP with the subsequent glycemic levels at T4 and T12. Multiple regression analysis confirmed that initial glycemia, HOMA-IR, and hs-CRP were strong predictors of elevated glycemia, while the TyG index did not show a significant predictive value. Conventional diabetes risk factors, including body mass index (BMI) and lipid profiles, showed low predictive power for post-COVID-19 glycemia. Conclusions: This research highlights the critical role of metabolic and inflammatory pathways in managing glycemic control in COVID-19 patients. Markers like blood glucose, HOMA-IR, and hs-CRP are significant predictors of blood glucose levels, while the TyG index appears less helpful in this context. Early, targeted interventions based on these markers can improve patient outcomes and reduce the risk of post-COVID-19 complications like diabetes.