Kulkarni Shruthi, Fernandes Jonita, Selvam Sumithra, Idiculla Jyothi
Department of General Medicine, St Johns Medical College, Bengaluru, Karnataka, India.
Division of Epidemiology, Biostatistics and Population Health, St John's Research Institute, Bengaluru, Karnataka, India.
Indian J Endocrinol Metab. 2022 Nov-Dec;26(6):551-557. doi: 10.4103/ijem.ijem_247_22. Epub 2023 Feb 7.
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.
This study aimed to describe the patterns of HG and its impact on the clinical outcomes in hospitalised patients with COVID-19 infection.
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).
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, = 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.
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.
糖尿病（DM）和高血糖（HG）已被确定为新型冠状病毒肺炎（COVID-19）感染发病和死亡的风险因素。然而，对各类高血糖及其对COVID-19的影响和特征进行详细研究，对于解决COVID-19中的这种代谢紊乱很重要。
本研究旨在描述COVID-19感染住院患者的高血糖模式及其对临床结局的影响。
使用社会科学统计软件包（SPSS）20.0版软件（SPSS公司，美国伊利诺伊州芝加哥）分析1000例连续的COVID-19患者的数据。
共纳入1000例患者进行分析。研究组的总体平均年龄为52.77±19.71岁，男性患者636例（63.6%）；261例为轻度感染，317例为中度感染，422例为重度感染；601例有高血糖（新发糖尿病66例，已知糖尿病386例，类固醇诱导的高血糖133例，应激性高血糖16例）。高血糖组的炎症标志物水平显著更高，结局更差。已知糖尿病患者的血糖水平更高。预测高血糖组死亡率的总类固醇的ROC临界值为84mg，而血糖正常组为60mg。预测总体高血糖组死亡率的空腹血糖（FBS）的ROC临界值为165，曲线下面积（AUC）为0.58（95%置信区间0.52，0.63，P=0.005），而既往糖尿病和类固醇性高血糖的临界值分别为232和166，也具有显著性。平均血糖水平随时间有很大差异。
高血糖是死亡率的独立预测因素，在类固醇诱导的类别中意义最大。通过确定最佳结果的血糖范围并制定适当的治疗指南，可以将COVID-19的发病率和死亡率降至最低。
