Pulmonary fibrosis in critical ill patients recovered from COVID-19 pneumonia: Preliminary experience

新冠肺炎康复重症患者的肺纤维化:初步经验

阅读:1

Abstract

OBJECTIVE: To investigate chest computed tomography (CT) findings associated with severe COVID-19 pneumonia in the early recovery period. METHODS: We retrospectively analyzed the cases of patients diagnosed with severe COVID-19 pneumonia at a single center between January 12, 2020, and March 16, 2020. The twelve ICU patients studied had been diagnosed SARS-CoV-2 (COVID-19) nucleic acid positive. Patient clinical symptoms were relieved or disappeared, and basic clinical information and laboratory test results were collected. The study focused on the most recent CT imaging characteristics. RESULTS: The average age of the 12 patients was 58.8 ± 16.2 years. The most prevalent symptoms were fever (100%), dyspnea (100%), and cough (83.3%). All patients experienced acute respiratory distress syndrome (ARDS), of which 9 were moderate to severe. Six patients used noninvasive ventilators, and 4 patients used mechanical ventilation. One patient was treated with extracorporeal membrane oxygenation (ECMO). The lymphocyte count decreased to 0.67 ± 0.3 (× 10 (9)/L). The average day from illness onset to the last follow-up CT was 56.1 ± 7.7 d. The CT results showed a decrease in ground glass opacities (GGO), whereas fibrosis gradually increased. The common CT features included GGO (10/12, 83.3%), subpleural line (10/12, 83.3%), fibrous stripes (12/12, 100%), and traction bronchiectasis (10/12, 83.3%). Eight patients (66.7%) showed predominant reticulation and interlobular thickening. Four patients (33.3%) showed predominant GGO. Lung segments involved were 174/216 (80.6%). CONCLUSIONS: Fibrous stripes and GGO are common CT signs in critically ill patients with COVID-19 pneumonia in the early recovery period. Signs of pulmonary fibrosis in survivors should be carefully monitored.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。