Correlation between lung infection severity and clinical laboratory indicators in patients with COVID-19: A cross-sectional study based on machine learning

Background: New coronavirus disease (COVID-19) has caused a global pandemic that has raised worldwide concern. This study aims to investigate the correlation between the extent of lung infection and relevant clinical laboratory testing indicators in COVID-19 and to analyse its underlying mechanism. Methods: : Chest high-resolution computer tomography (CT) images and laboratory examination data of 31 patients with COVID-19 were extracted, and the lesion areas in CT images were quantitatively segmented and calculated using the deep learning (DL) system. A cross-sectional study method was used to explore the differences among the proportions of lung lobe infection and to correlate the percentage of infection (POI) of the whole lung in all patients with clinical laboratory examination values. Results: : No significant difference in the proportion of infection was noted among various lung lobes ( P > 0.05). The POI of total lung infection was negatively correlated with the peripheral blood lymphocyte percentage (L%) ( r = -0.633, P < 0.0001) and lymphocyte count (LY) ( r = -0.555, P = 0.001) but positively correlated with the neutrophil percentage (G%) ( r = 0.565, P = 0.001). Otherwise, the POI was not significantly correlated with the peripheral blood leukocyte count (WBC), monocyte percentage (M%) or haemoglobin content (HGB). In some patients, the G% increased continuously and was accompanied by a progressive decrease in the L% and LY. Conclusions: : No significant difference in infection propensity was noted among the lung lobes in COVID-19 patients. The peripheral blood lymphocyte and neutrophil levels are significantly correlated with the extent of lung lesions, and related indicator abnormalities serve as a warning, thus guiding the implications of clinical interventions in patients.