Evaluation of an Established Semi-Quantitative Chest CT Scoring System for Assessing the Severity of COVID-19 Pneumonia: What is Its Diagnostic Value Regarding Patient Outcomes?

Background/Objectives: Investigation of whether visual and AI-based assessments of the severity of COVID-19 pneumonia using an established semi-quantitative chest CT scoring system (Pan score) correlate with laboratory parameters as well as pulmonary function, and of the score’s diagnostic value in predicting the patients’ clinical outcome. Methods: This retrospective analysis comprises patients with PCR-confirmed COVID-19, who received a chest CT scan (not more than three days prior to or after the positive PCR test) between March 21, 2020, and December 27, 2021. Each of the five lung lobes was assessed separately using a scoring system ranging from 0 (no pulmonary involvement) to 5 (> 75% pulmonary involvement) by a radiology specialist, an experienced resident physician, a medical student, and a dedicated AI-based chest CT software tool. In addition, pulmonary function and laboratory parameters, the duration of ICU stays and of any required mechanical ventilation, as well as the clinical outcome (discharge vs. death) were recorded, and their correlation with the obtained CT score was analysed. Statistical analyses comprised descriptive baseline comparisons using non-parametric tests, bivariate correlation matrices, and ROC curves to assess diagnostic accuracy. Furthermore, multivariable logistic, ordinal, and age-adjusted spline regression models were constructed to calculate odds ratios and estimate predicted probabilities for cumulative ICU and mechanical ventilation duration thresholds. Results: In total, 351 consecutive patients with confirmed COVID-19 (223 males [63.5%], 128 females [36.5%]; mean age 67.0 years) were included, all of whom underwent at least one chest CT scan. Compared with patients who were discharged, deceased patients had a significantly (p < 0.05) higher mean Pan score (11.7 ± 6.0 vs. 8.8 ± 5.0), higher rates of mechanical ventilation (56.0 vs. 32.1 %), and both a higher incidence (42.7 vs. 25.4 %) and longer duration (10.5 [6.0–20.0] vs. 6.0 [3.0–10.0] days) of ICU stays. The Pan score showed a strong and consistent association with the requirement for mechanical ventilation (r = 0.54; p < 0.01) and the duration of the ICU stay (r = 0.39; p < 0.01). Conclusions: The investigated semi-quantitative CT score is a simple, reliable tool for assessing the extent of COVID-19 pneumonia and can be evaluated both by radiologists and fully automated AI software. While its predictive value for all-cause mortality was only moderate, it showed good performance in predicting the need for and duration of mechanical ventilation, as well as intensive care requirement.