Predictors of disease severity, clinical course, and therapeutic outcome in COVID-19 patients: Our experience with 1700 patients (preprint)

ABSTRACT

Objective: To investigate the impacts of demographic, hematological, and biochemical factors on the clinical course and the prognostic outcome in adult COVID-19 patients. Methods: This retrospective study was performed in the internal medicine departments of 2 hospitals and data were extracted from the medical files of 1700 adult COVID-19 patients (836 females, 49.2%; 864 males, 50.8%) with an average age of 48.23 ± 16.68 (range 18-93). Clinical data included baseline descriptives, prior medical history, admission date, treatment, and hematological and biochemical blood test results. The relationship between the survival, length of hospitalization, hematological, and biochemical parameters was investigated. Results: Advanced age (p<0.001), presence of at least 1 comorbid disease (p=0.045), increased length of hospitalization (p=0.006), elevated white blood cell (p=0.001) and neutrophil (p=0.002) counts, increased serum levels of glucose (p=0.027), blood urea nitrogen (p<0.001), AST (p=0.006), LDH (p<0.001), CRP (p>0.001), and D-dimer (p=0.001). In contrast, diminution of serum levels of albumin (p<0.001), ALT (p=0.028), calcium (p=0.022), and platelet count (p=0.010) were associated with increased mortality. There was a positive and weak relationship between serum D-dimer levels and length of hospitalization. Conclusion: Our data imply that identification and validation of indicators that predict COVID-19 disease progression to improve health outcomes are crucial. Age, comorbidities, immunological response, radiographic abnormalities, laboratory markers, and signs of organ dysfunction may all predict poor outcomes individually or collectively. It is critical to identify characteristics that predict COVID-19 problems to guide clinical management, improve patient outcomes, and allocation of limited resources. Keywords SARS-Cov-2, COVID-19; severity; prognosis; outcome: