Shin Hyun Joo, Kim Min Hyung, Son Nak-Hoon, Han Kyunghwa, Kim Eun-Kyung, Kim Yong Chan, Park Yoon Soo, Lee Eun Hye, Kyong Taeyoung
Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si 16995, Republic of Korea.
Center for Digital Health, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si 16995, Republic of Korea.
Diagnostics (Basel). 2023 Jun 16;13(12):2090. doi: 10.3390/diagnostics13122090.
This study aimed to investigate the clinical implications and prognostic value of artificial intelligence (AI)-based results for chest radiographs (CXR) in coronavirus disease 2019 (COVID-19) patients. Patients who were admitted due to COVID-19 from September 2021 to March 2022 were retrospectively included. A commercial AI-based software was used to assess CXR data for consolidation and pleural effusion scores. Clinical data, including laboratory results, were analyzed for possible prognostic factors. Total O supply period, the last SpO result, and deterioration were evaluated as prognostic indicators of treatment outcome. Generalized linear mixed model and regression tests were used to examine the prognostic value of CXR results. Among a total of 228 patients (mean 59.9 ± 18.8 years old), consolidation scores had a significant association with erythrocyte sedimentation rate and C-reactive protein changes, and initial consolidation scores were associated with the last SpO result (estimate -0.018, = 0.024). All consolidation scores during admission showed significant association with the total O supply period and the last SpO result. Early changing degree of consolidation score showed an association with deterioration (odds ratio 1.017, 95% confidence interval 1.005-1.03). In conclusion, AI-based CXR results for consolidation have potential prognostic value for predicting treatment outcomes in COVID-19 patients.
本研究旨在探讨基于人工智能（AI）的2019冠状病毒病（COVID-19）患者胸部X线片（CXR）结果的临床意义及预后价值。回顾性纳入了2021年9月至2022年3月因COVID-19入院的患者。使用一款基于AI的商业软件评估CXR数据的实变和胸腔积液评分。分析包括实验室检查结果在内的临床数据，以寻找可能的预后因素。将总氧供应期、末次血氧饱和度（SpO）结果及病情恶化情况作为治疗结局的预后指标。采用广义线性混合模型和回归检验来研究CXR结果的预后价值。在总共228例患者（平均年龄59.9±18.8岁）中，实变评分与红细胞沉降率及C反应蛋白变化显著相关，初始实变评分与末次SpO结果相关（估计值-0.018，P = 0.024）。入院期间所有实变评分均与总氧供应期和末次SpO结果显著相关。实变评分的早期变化程度与病情恶化相关（比值比1.017，95%置信区间1.005-1.03）。总之，基于AI的CXR实变结果对预测COVID-19患者的治疗结局具有潜在的预后价值。
