Indian Journal of Endocrinology and Metabolism (Jan 2022)
A study of the profile and the impact of diabetes, steroid and stress hyperglycaemia on COVID-19 outcomes
Abstract
Background: Diabetes Mellitus (DM) and hyperglycaemia (HG) have been identified as risk factors for morbidity and mortality in coronavirus disease 19 (COVID-19) infection. However, a detailed study of various categories of HG and the impacts and characteristics of each of these on COVID-19 was considered important to address this metabolic disorder in COVID-19. Aims: This study aimed to describe the patterns of HG and its impact on the clinical outcomes in hospitalised patients with COVID-19 infection. Methodology: Data on 1000 consecutive patients with COVID-19 were analysed using Statistical Package for Social Sciences (SPSS) version 20.0 software (SPSS Inc., Chicago, IL, USA). Results: A total of 1000 patients were included for analysis The overall mean age of the study group was 52.77 + 19.71 with 636 (63.6%) male patients; 261 had mild, 317 moderate, and 422 severe infections; and 601 had HG (New-onset DM 66, known DM 386, steroid-induced HG 133 and stress HG 16). The HG group has significantly higher levels of inflammatory markers and worse outcomes. Blood glucose levels were higher in patients with known DM. The ROC cut-off of total steroids to predict mortality in the HG group was 84 mg versus 60 mg in the normoglycaemia group. The ROC cut-off of FBS to predict mortality in the overall HG group was 165, with AUC 0.58 (95% CI 0.52, 0.63, P = 0.005), whereas that for pre-existing DM and steroid HG were 232 and 166, which were also significant. There was a wide variation in mean glucose levels against time. Conclusion: HG is an independent predictor of mortality, with the highest significance in the steroid-induced category. COVID-19 morbidity and mortality can be minimised by identifying the blood glucose range for best results and instituting appropriate treatment guidelines.
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