Baseline and early changes in laboratory parameters predict disease severity and fatal outcomes in COVID-19 patients

Coronavirus disease 2019 (COVID-19) has become the worst catastrophe of the twenty-first century and has led to the death of more than 6.9 million individuals across the globe. Despite the growing knowledge of the clinicopathological features of COVID-19, the correlation between baseline and early changes in the laboratory parameters and the clinical outcomes of patients is not entirely understood.

Here, we conducted a time series cross-sectional study aimed at assessing different measured parameters and socio-demographic factors that are associated with disease severity and the outcome of the disease in 268 PCR-confirmed COVID-19 Patients.

We found COVID-19 patients who died had a median age of 61 years (IQR, 50 y - 70 y), which is significantly higher (p < 0.05) compared to those who survived and had a median age of 54 years (IQR, 42y - 65y). The median RBC count of COVID-19 survivors was 4.9 × 10⁶/μL (IQR 4.3 × 10⁶/μL - 5.2 × 10⁶/μL) which is higher (p < 0.05) compared to those who died 4.4 × 10⁶/μL (3.82 × 10⁶/μL - 5.02 × 10⁶/μL). Similarly, COVID-19 survivors had significantly (p < 0.05) higher lymphocyte and monocyte percentages compared to those who died. One important result we found was that COVID-19 patients who presented with severe/critical cases at the time of first admission but managed to survive had a lower percentage of neutrophil, neutrophil to lymphocyte ratio, higher lymphocyte and monocyte percentages, and RBC count compared to those who died.

To conclude here, we showed that simple laboratory parameters can be used to predict severity and outcome in COVID-19 patients. As these parameters are simple, inexpensive, and radially available in most resource-limited countries, they can be extrapolated to future viral epidemics or pandemics to allocate resources to particular patients.