Ability of Laboratory Findings upon Admission to Predict Lung Involvement and Its Severity in COVID-19 Patients Requiring Hospitalization

Background: The struggle of humanity with Coronavirus disease 2019 (COVID-19) infection, which affected the whole world and caused severe social and health crises, continues without deceleration. Objectives: This study aimed to determine the relationship between the abnormal laboratory parameters upon admission and the intensity of lung involvement using chest computerized tomography severity score (CT-SS). Methods: This single-center study evaluated a total of 242 patients who were admitted to our hospital due to COVID-19 with positive polymerase chain reaction (PCR) test results. The patients were divided into three groups of no involvement on thorax CT images, mild involvement, and moderate-severe involvement. Results: The mean ages of groups 1 (n=42), 2 (n=123), and 3 (n=77) were 38 +/- 10.6, 56.3 +/- 16, and 61 +/- 15.6 years, respectively (P<0.001). The three groups showed significant differences in terms of hypertension, diabetes mellitus, heart rate, oxygen saturation, lymphocyte count, platelet-lymphocyte ratio (PLR), systemic immune inflammation index (SII), ferritin, troponin-I, erythrocyte sedimentation rate (ESR), and c-reactive protein (CRP) values (P<0.001). The CRP (R=0.545, P<0.001), ferritin (R=0.481, P<0.001), and SII (R=0.473, P<0.001) were moderately and positively correlated with CT-SS, while neutrophil-lymphocyte ratio (R=0.404, P<0.001), PLR (R=0.371, P<0.001), and ESR (R=0.327, P<0.001) were mildly and positively correlated with CT-SS. Conclusion: The results of the present study showed that elevation in CRP, as well as ferritin and SII values upon admission to the hospital was significantly correlated with CT-SS. The results also revealed that the presence of lung parenchyma involvement might be predicted in PCR positive COVID-19 patients without the need for thorax CT. Furthermore, it is believed that this information will provide great convenience to the clinicians who first welcome the patient in terms of predicting COVID-19 lung involvement.