Title Research on predictors of disease severity and clinical outcomes in hospitalised COVID-19 patients
Translation of Title Hospitalizuotų pacientų sunkios COVID-19 ligos ir jos baigčių prognostinių veiksnių tyrimas.
Authors Kubiliūtė, Ieva
DOI 10.15388/vu.thesis.969
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Pages 194
Keywords [eng] COVID-19 ; predictors ; cell-free DNA ; cfDNA
Abstract [eng] This doctoral dissertation aimed to identify demographic, clinical, and laboratory factors predicting severe COVID-19 disease, defined by the need for oxygen therapy, and lethal outcomes in hospitalised COVID-19 patients. It comprised three observational cohort studies conducted at Vilnius University Hospital Santaros Klinikos. The first included 2,794 hospitalised adults and assessed predictors of in-hospital mortality, including troponin I and hyperglycaemia. The second included 495 patients and evaluated clinical characteristics and predictors of severe COVID-19 disease. The third assessed serum cell-free nucleic acids (cfDNA and SARS-CoV-2 RNA) in 108 patients with COVID-19 and 24 controls. Older age, obesity, lymphopenia, and higher CRP and LDH levels on admission were independently associated with severe COVID-19 disease, while age, congestive heart failure, obesity, COPD, prior stroke, and elevated urea, LDH, CRP, IL-6, troponin I levels, and AST-to-ALT ratio on admission were associated with in-hospital mortality. Troponin I and hyperglycaemia provided additional prognostic information for in-hospital mortality. Higher serum cfDNA levels were independently associated with disease severity, intensive care admission, advanced respiratory support, and in-hospital mortality, whereas serum SARS-CoV-2 RNAemia was associated with advanced respiratory support. These findings support cfDNA as a promising biomarker for early risk stratification and outcome prediction in hospitalised COVID-19 patients, although further standardisation and external validation are required before clinical implementation.
Dissertation Institution Vilniaus universitetas.
Type Doctoral thesis
Language English
Publication date 2026