Predictors of New-Onset Diabetes in Hospitalized Patients with SARS-CoV-2 Infection

Int J Environ Res Public Health. 2022 Oct 14;19(20):13230. doi: 10.3390/ijerph192013230.

Abstract

The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the world's most disruptive health crises. The presence of diabetes plays an important role in the severity of the infection, and a rise in newly diagnosed diabetes cases has been identified. The aim of this retrospective study was to determine the incidence of new-onset diabetes (NOD) and predictive factors with their cut-off values for patients hospitalized with COVID-19. All patients (n = 219) hospitalized for COVID-19 during three consecutive months were included. NOD was diagnosed in 26.48% of patients. The severity of the infection, hospital admission values for fasting plasma glucose, lactate dehydrogenase (LDH), PaO2/FiO2 ratio, the peak values for leucocytes, neutrophils, C-reactive protein, triglycerides, and the need for care in the intensive care unit were predictors for the occurrence of NOD in univariate analysis, while only LDH level remained a significant predictor in the multivariable analysis. In conclusion, the results of the study showed a high incidence of NOD in patients hospitalized with COVID-19 and identified LDH levels at hospital admission as a significant predictor of NOD during SARS-CoV-2 infection. However, the persistence of NOD after the COVID-19 infection is not known, therefore, the results must be interpreted with caution.

Keywords: COVID-19; cut-off value; new-onset diabetes mellitus; predictors.

MeSH terms

  • Blood Glucose
  • C-Reactive Protein / metabolism
  • COVID-19* / epidemiology
  • Diabetes Mellitus* / epidemiology
  • Humans
  • L-Lactate Dehydrogenase
  • Retrospective Studies
  • SARS-CoV-2
  • Triglycerides

Substances

  • C-Reactive Protein
  • Blood Glucose
  • L-Lactate Dehydrogenase
  • Triglycerides

Grants and funding

This research received no external funding.