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

Abstract

IntroductionChest 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 methodsAltogether 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.ResultsThe 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.ConclusionCTSS 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.

Cohort Comparative Study of Covid-19 Vaccinated and Non-Vaccinated Patients Depending on Ct Chest Findings Between Iraqi and Jordanian Population

“…This is similar to other studies [42,47]. Finally, CT score positively correlated with age, WBC and platelet counts, CRP, PCT, LDH, D-dimer, ferritin, IL-6, urea, and the A-DROP score, while negatively correlated with total lymphocyte count, PaO2 and SaO2 [39].…”

“…However, when comparing non-vaccinated patients from both nations, we revealed that most of the cases lie at mid-score and above with no significant difference (p=0.639). In Szabo et al, the mean score was moderate (14.6) while in the study of Francone et al, the mean score was 18 which was associated with a high mortality rate [39,42].…”

“…Awareness of these features might assist radiologists encountering these COVID- 19 cases in daily practice. Szabo et al concluded that a CT scan score may be suitable to assess the severity of COVID-19 [39]. CT score and chest CT patterns may predict the required ventilation, as well as mortality in COVID-19, which help the staff to guide management strategies in COVID-19, as well as other infections.…”

CT semi-quantitative score used as risk factor for hyponatremia in patients with COVID-19: a cross-sectional study

“…Miklos Szabo et al. found that the chest CT scoring system (CCTS) and specific chest CT patterns can predict ventilation requirements and mortality in COVID-19 ( 32 ). In this study, we used the TSS semi-quantitative method to assess the severity of lung lesions in patients with COVID-19 and then correlate it with hyponatremia.…”