The importance of chest CT severity score and lung CT patterns in risk assessment in COVID-19-associated pneumonia: a comparative study

Miklós Szabó; Zsófia Kardos; László Kostyál; Péter Tamáska; Csaba Oláh; Eszter Csánky; Zoltán Szekanecz

doi:10.3389/fmed.2023.1125530

The importance of chest CT severity score and lung CT patterns in risk assessment in COVID-19-associated pneumonia: a comparative study

Front Med (Lausanne). 2023 May 17:10:1125530. doi: 10.3389/fmed.2023.1125530. eCollection 2023.

Authors

Miklós Szabó¹, Zsófia Kardos^{2

3}, László Kostyál⁴, Péter Tamáska⁴, Csaba Oláh⁴, Eszter Csánky¹, Zoltán Szekanecz⁵

Affiliations

¹ Department of Pulmonology, Borsod Academic County Hospital, Miskolc, Hungary.
² Department of Rheumatology, Borsod Academic County Hospital, Miskolc, Hungary.
³ Faculty of Health Sciences, University of Miskolc, Miskolc, Hungary.
⁴ Department of Radiology, Borsod Academic County Hospital, Miskolc, Hungary.
⁵ Department of Rheumatology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.

Abstract

Introduction: Chest computed tomography (CT) is suitable to assess morphological changes in the lungs. Chest CT scoring systems (CCTS) have been developed and use in order to quantify the severity of pulmonary involvement in COVID-19. CCTS has also been correlated with clinical outcomes. Here we wished to use a validated, relatively simple CTSS to assess chest CT patterns and to correlate CTSS with clinical outcomes in COVID-19.

Patients and methods: Altogether 227 COVID-19 cases underwent chest CT scanning using a 128 multi-detector CT scanner (SOMATOM Go Top, Siemens Healthineers, Germany). Specific pathological features, such as ground-glass opacity (GGO), crazy-paving pattern, consolidation, fibrosis, subpleural lines, pleural effusion, lymphadenopathy and pulmonary embolism were evaluated. CTSS developed by Pan et al. (CTSS-Pan) was applied. CTSS and specific pathologies were correlated with demographic, clinical and laboratory data, A-DROP scores, as well as outcome measures. We compared CTSS-Pan to two other CT scoring systems.

Results: The mean CTSS-Pan in the 227 COVID-19 patients was 14.6 ± 6.7. The need for ICU admission (p < 0.001) and death (p < 0.001) were significantly associated with higher CTSS. With respect to chest CT patterns, crazy-paving pattern was significantly associated with ICU admission. Subpleural lines exerted significant inverse associations with ICU admission and ventilation. Lymphadenopathy was associated with all three outcome parameters. Pulmonary embolism led to ICU admission. In the ROC analysis, CTSS>18.5 significantly predicted admission to ICU (p = 0.026) and CTSS>19.5 was the cutoff for increased mortality (p < 0.001). CTSS-Pan and the two other CTSS systems exerted similar performance. With respect to clinical outcomes, CTSS-Pan might have the best performance.

Conclusion: CTSS may be suitable to assess severity and prognosis of COVID-19-associated pneumonia. CTSS and specific chest CT patterns may predict the need for ventilation, as well as mortality in COVID-19. This can help the physician to guide treatment strategies in COVID-19, as well as other pulmonary infections.

Keywords: COVID-19; chest CT severity score; ground-glass opacity; intensive care unit; survival.