Role of CT-based body composition parameters in the course of COVID-19.

BACKGROUND/AIM: A significant correlation is observed between the course of coronavirus disease 2019 (COVID-19) and body composition parameters including visceral fat quantification, muscle mass, and hepatic attenuation. The aim of the study was to investigate the correlation between the extent of lung involvement and various computed tomography (CT) parameters, as well as laboratory findings in COVID-19 patients.

MATERIALS AND METHODS

A retrospective analysis was conducted on 72 adult patients with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection who underwent two consecutive thorax CT scans at least 2 weeks apart. The patients were divided into two groups, as progressive and nonprogressive, based on the presence of two consecutive CT scans. Skeletal muscle area (SMA), subcutaneous fat area (SFA), visceral fat area (VFA), total fat area (TFA), liver-to-spleen (L/S) density ratio, and laboratory findings were compared between the groups. The correlation between the extent of lung involvement and CT parameters, as well as the laboratory findings were assessed.

RESULTS

A total of 72 patients were included in the study, with 34 (47.2%) females and 38 (52.8%) males. Hemoglobin levels were significantly lower in the progressive group compared to the nonprogressive group. C-reactive protein (CRP) values were higher in the progressive group at follow-up. The nonprogressive group exhibited decreases in the SFA, VFA, and TFA, while liver density increased. The progressive group showed a decrease in the twelfth thoracic vertebra (T12) paravertebral muscle area and muscle index.

CONCLUSION

In the comparison of the laboratory and radiological data in the course of COVID-19, white blood cell (WBC) and neutrophil counts increased, SMA T12, and the skeletal muscle index (SMI) decreased in the lung progressive group. Hemoglobin and CRP levels at admission may indicate disease progression. Future studies are warranted to increase the reliability with larger series.