Biochemical and Hematological Profile of Covid-19 Patients on Mechanical Ventilation

Beakground: The prevalence of cardiovascular diseases in COVID-19 patients, such as hypertension, diabetes mellitus, and chronic obstructive pulmonary disease, which are the most common comorbid conditions in COVID-19 patients, is considered a risk factor for premature mortality in the population. The aim of the study is to compare the standard biochemical and hematological markers of COVID-19 patients on mechanical ventilation and those who have recovered, and to identify differences by gender and comorbidities, as well as the dominant marker in comorbidities that frequently shows statistical significance, in order to investigate its prognostic value in further research.

The study is a retrospective study of patients with RT-PCR confirmed presence of the Sars-CoV-2 virus who were hospitalized at the Zenica Cantonal Hospital. The study lasted from February to April 2021.

The results of the study, which included a sample of 302 participants, indicate that men were more represented in both the mechanical ventilation group and the recovered group, with 59.6% compared to women with 40.4%. Among the investigated biochemical and hematological parameters, there was a significantly higher number of leukocytes, urea, creatinine, LDH, and troponin in patients on mechanical ventilation, while the number of platelets was significantly higher in recovered patients. The most common comorbidity was hypertension in both groups of patients, with 24.5%. In patients on mechanical ventilation with cardiovascular disease, there was a significantly higher number of leukocytes, urea, creatinine, LDH, and troponin. In the same patients with three comorbidities, there was a significantly higher number of leukocytes, troponin, and LDH, while recovered patients without comorbidities had a significantly higher number of platelets.

The male gender and comorbidities remain a vicious circle in COVID-19 infection, while biochemical and hematological markers can help in forecasting and improve the clinical treatment of these high-risk patients.