Shiro Otake, Yusuke Shiraishi, Shotaro Chubachi, Naoya Tanabe, Tomoki Maetani, Takanori Asakura, Ho Namkoong, Takashi Shimada, Shuhei Azekawa, Kensuke Nakagawara, Hiromu Tanaka, Takahiro Fukushima, Mayuko Watase, Hideki Terai, Mamoru Sasaki, Soichiro Ueda, Yukari Kato, Norihiro Harada, Shoji Suzuki, Shuichi Yoshida, Hiroki Tateno, Yoshitake Yamada, Masahiro Jinzaki, Toyohiro Hirai, Yukinori Okada, Ryuji Koike, Makoto Ishii, Naoki Hasegawa, Akinori Kimura, Seiya Imoto, Satoru Miyano, Seishi Ogawa, Takanori Kanai, Koichi Fukunaga
OBJECTIVE: This study aimed to investigate the utility of CT quantification of lung volume for predicting critical outcomes in COVID-19 patients. METHODS: This retrospective cohort study included 1200 hospitalised patients with COVID-19 from 4 hospitals. Lung fields were extracted using artificial intelligence-based segmentation, and the percentage of the predicted (%pred) total lung volume (TLC (%pred)) was calculated. The incidence of critical outcomes and posthospitalisation complications was compared between patients with low and high CT lung volumes classified based on the median percentage of predicted TLCct (n=600 for each)...
April 24, 2024: BMJ Open Respiratory Research