Department of Radiology, The First College of Clinical Medical Science, China Three Gorges University, Yichang Central People's Hospital, Yichang, China.
Department of Radiology, Yichang Second People's Hospital, Yichang, China.
Int J Med Sci. 2021 Jan 1;18(1):270-275. doi: 10.7150/ijms.48281. eCollection 2021.
To identify whether the initial chest computed tomography (CT) findings of patients with coronavirus disease 2019 (COVID-19) are helpful for predicting the clinical outcome. A total of 224 patients with laboratory-confirmed COVID-19 who underwent chest CT examination within the first day of admission were enrolled. CT findings, including the pattern and distribution of opacities, the number of lung lobes involved and the chest CT scores of lung involvement, were assessed. Independent predictors of adverse clinical outcomes were determined by multivariate regression analysis. Adverse outcome were defined as the need for mechanical ventilation or death. Of 224 patients, 74 (33%) had adverse outcomes and 150 (67%) had good outcomes. There were higher frequencies of more than four lung zones involved (73% vs 32%), both central and peripheral distribution (57% vs 42%), consolidation (27% vs 17%), and air bronchogram (24% vs 13%) and higher initial chest CT scores (8.6±3.4 vs 5.4±2.1) ( < 0.05 for all) in the patients with poor outcomes. Multivariate analysis demonstrated that more than four lung zones (odds ratio [OR] 3.93; 95% confidence interval [CI]: 1.44 to 12.89), age above 65 (OR 3.65; 95% CI: 1.11 to 10.59), the presence of comorbidity (OR 5.21; 95% CI: 1.64 to 19.22) and dyspnea on admission (OR 3.19; 95% CI: 1.35 to 8.46) were independent predictors of poor outcome. Involvement of more than four lung zones and a higher CT score on the initial chest CT were significantly associated with adverse clinical outcome. Initial chest CT findings may be helpful for predicting clinical outcome in patients with COVID-19.
为了确定 2019 年冠状病毒病（COVID-19）患者的初始胸部计算机断层扫描（CT）结果是否有助于预测临床转归。共纳入 224 例在入院第一天内接受胸部 CT 检查的实验室确诊 COVID-19 患者。评估 CT 结果，包括不透明度的模式和分布、受累肺叶的数量以及肺受累的 CT 评分。通过多变量回归分析确定不良临床结局的独立预测因素。不良结局定义为需要机械通气或死亡。224 例患者中，74 例（33%）发生不良结局，150 例（67%）结局良好。更多的肺区受累（73%对 32%）、中央和外周分布（57%对 42%）、实变（27%对 17%）和空气支气管征（24%对 13%）以及更高的初始胸部 CT 评分（8.6±3.4 对 5.4±2.1）（均<0.05）的患者更频繁出现。多变量分析表明，超过四个肺区（比值比[OR]3.93；95%置信区间[CI]：1.44 至 12.89）、年龄大于 65 岁（OR 3.65；95% CI：1.11 至 10.59）、合并症（OR 5.21；95% CI：1.64 至 19.22）和入院时呼吸困难（OR 3.19；95% CI：1.35 至 8.46）是不良结局的独立预测因素。初始胸部 CT 显示超过四个肺区受累和更高的 CT 评分与不良临床结局显著相关。初始胸部 CT 结果可能有助于预测 COVID-19 患者的临床结局。
