Abstract
INTRODUCTION: There are few accurate prognostic indications of the illness's development and severity for COVID-19, despite certain biomarkers having been investigated. The unexpected nature of COVID-19's course, which can quickly progress from asymptomatic to life-threatening symptoms, lies at the heart of the disease's intricacy. Predicting SARS-CoV-2 pathogenicity through laboratory biomarkers and as such, identifying the patients' illness severity at the time of their initial admission would be crucial in improving patient care. In this study, we sought to evaluate the potential of hematological, biochemical, and inflammatory biomarkers in predicting the course of COVID-19 at a tertiary hospital in western Kenya. METHODS: This cross-sectional study involved 48 COVID-19 patients (16 asymptomatic; 16 moderate symptomatic; and 16 severe symptomatic) and 48 age-sex-matched COVID-19-negative clients attending the Moi Teaching and Referral Hospital, Kenya. Demographic information, self-reported chronic illnesses, symptoms, and laboratory results were collected at recruitment. RESULTS: Significantly, the severity of COVID-19 was associated with; hemoglobin (p < 0.0001), white blood cells (p = 0.0022), hematocrit (p < 0.0001), blood urea nitrogen (p = 0.01), blood sodium (p = 0.0002), potassium (p = 0.0483), C-reactive protein (p = 0.0002), and Lactate Dehydrogenase (p < 0.0001). Regression analysis of CRP revealed a strong positive correlation (p = 0.0006) whereas LDH revealed a weak positive correlation (p < 0.0001) with COVID-19 disease severity. Discriminative accuracy was highest when asymptomatic was compared to severe COVID-19 for CRP and LDH (AUC: 0.8867, 95% CI: 0.7532-1.000) and (AUC: 1.000, 95% CI: 1.000-1.000) respectively. CONCLUSION: The hematological indices, inflammatory and biochemical biomarkers studied have the potential to predict the course of COVID-19. These parameters may be useful in helping design appropriate care for COVID-19 patients.