Clinical Profile, Outcomes and Severity Predictor Model in COVID 19 Patients: An Early Indian Experience
Abstract
Background: SARS COV-2 infection or COVID 19 originated in Wuhan, China. It has now spread to entire world and WHO has
declared it as pandemic.
Methods: We studied clinical profile, comorbidities, laboratory parameters, their association to disease severity and developed a
severity prediction model based on them.
Results: 36/53(68%) patients had Mild Disease (MD), whereas 17/53(32%) were classified to be having Moderate/Severe Disease
(MSD). Compared MSD group with MD group, the value of white blood cell count (Δ(MSD-MD)=2639/mm3; 95% CI, 1094.94 to 4183.04/
mm3; p=0.001), Neutrophil Lymphocyte Ratio(N/L ratio) (Δ(MSD-MD)=5.21; 95% CI, 3.30 to 7.12; p=0.0001), CRP (Δ(MSD-MD)=79.31; 95%
CI, 45.28 to 113.34 pg/ml; p=0.0001) and ferritin (Δ(MSD-MD)=293.42; 95% CI, 123.35 to 463.48; p=0.001) were significantly elevated. The
optimal cut-off established by ROC curve for N/L ratio-3.13 (Sn=100.0% and Sp=86.4%), CRP-16.0 (Sn=92.3% and Sp=90.9%). The
CRP (OR=272, 95% CI: 23 to 3225, p=0.0001) and N/L Ratio (OR=176, 95% CI: 17 to 1828, p=0.0001) had highest power of predicting
disease severity. Based on N/L ratio and CRP, block model probability of progression to MSD was calculated for each patient and the
model correctly classified 94.3% of patients.
Conclusion: Severity Prediction model using baseline N/L ratio and CRP correctly predicted progression to MSD in majority of cases.
