Ontology highlight
ABSTRACT: Aims
To create and compare survival models from admission laboratory indices in people hospitalized with coronavirus disease 2019 (COVID-19) with and without diabetes.Methods
Retrospective observational study of patients with COVID-19 with or without diabetes admitted to Sheffield Teaching Hospitals from 29 February to 01 May 2020. Predictive variables for in-hospital mortality from COVID-19 were explored using Cox proportional hazard models.Results
Out of 505 patients, 156 (30.8%) had diabetes mellitus (DM) of which 143 (91.7%) had type 2 diabetes. There were significantly higher in-hospital COVID-19 deaths in those with DM [DM COVID-19 deaths 54 (34.6%) vs. non-DM COVID-19 deaths 88 (25.2%): P < 0.05]. Activated partial thromboplastin time (APPT) > 24 s without anticoagulants (HR 6.38, 95% CI: 1.07-37.87: P = 0.04), APTT > 24 s with anticoagulants (HR 24.01, 95% CI: 3.63-159.01: P < 0.001), neutrophil-lymphocyte ratio > 8 (HR 6.18, 95% CI: 2.36-16.16: P < 0.001), and sodium > 136 mmol/L (HR 3.27, 95% CI: 1.12-9.56: P = 0.03) at admission, were only associated with in-hospital COVID-19 mortality for those with diabetes.Conclusions
At admission, elevated APTT with or without anticoagulants, neutrophil-lymphocyte ratio and serum sodium are unique factors that predict in-hospital COVID-19 mortality in patients with diabetes compared to those without. This novel finding may lead to research into haematological and biochemical mechanisms to understand why those with diabetes are more susceptible to poor outcomes when infected with Covid-19, and contribute to identification of those most at risk when admitted to hospital.
SUBMITTER: Iqbal A
PROVIDER: S-EPMC8278840 | biostudies-literature |
REPOSITORIES: biostudies-literature