Szabó Miklós, Kardos Zsófia, Kostyál László, Tamáska Péter, Oláh Csaba, Csánky Eszter, Szekanecz Zoltán
Department of Pulmonology, Borsod Academic County Hospital, Miskolc, Hungary.
Department of Rheumatology, Borsod Academic County Hospital, Miskolc, Hungary.
Front Med (Lausanne). 2023 May 17;10:1125530. doi: 10.3389/fmed.2023.1125530. eCollection 2023.
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.
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.
The mean CTSS-Pan in the 227 COVID-19 patients was 14.6 ± 6.7. The need for ICU admission ( < 0.001) and death ( < 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 ( = 0.026) and CTSS>19.5 was the cutoff for increased mortality ( < 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.
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.
胸部计算机断层扫描（CT）适用于评估肺部的形态变化。胸部CT评分系统（CCTS）已被开发并用于量化COVID-19患者肺部受累的严重程度。CCTS也与临床结局相关。在此，我们希望使用一种经过验证的、相对简单的CT评分系统来评估胸部CT模式，并将CT评分系统与COVID-19的临床结局相关联。
总共227例COVID-19患者使用128层螺旋CT扫描仪（德国西门子医疗的SOMATOM Go Top）进行了胸部CT扫描。评估了磨玻璃影（GGO）、铺路石样改变、实变、纤维化、胸膜下线、胸腔积液、淋巴结肿大和肺栓塞等特定病理特征。应用了Pan等人开发的CT评分系统（CTSS-Pan）。CTSS和特定病理与人口统计学、临床和实验室数据、A-DROP评分以及结局指标相关。我们将CTSS-Pan与其他两种CT评分系统进行了比较。
227例COVID-19患者的平均CTSS-Pan为14.6±6.7。入住重症监护病房（ICU）的需求（<0.001）和死亡（<0.001）与较高的CTSS显著相关。关于胸部CT模式，铺路石样改变与入住ICU显著相关。胸膜下线与入住ICU和机械通气呈显著负相关。淋巴结肿大与所有三个结局参数相关。肺栓塞导致入住ICU。在ROC分析中，CTSS>18.5显著预测入住ICU（=0.026），CTSS>19.5是死亡率增加的临界值（<0.001）。CTSS-Pan和其他两种CT评分系统表现相似。就临床结局而言，CTSS-Pan可能表现最佳。
CTSS可能适用于评估COVID-19相关肺炎的严重程度和预后。CTSS和特定的胸部CT模式可以预测COVID-19患者的机械通气需求和死亡率。这有助于医生指导COVID-19以及其他肺部感染的治疗策略。
