Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
School of Information Science and Technology, ShanghaiTech University, Shanghai, China.
Respir Res. 2022 Apr 29;23(1):105. doi: 10.1186/s12931-022-02025-6.
Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19) and for monitoring its progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19.
Between February 7 and February 17, 2020, 72 patients with severe COVID-19 were retrospectively enrolled. All 300 chest CT scans from these patients were collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3-7 days); Stage 3 (8-14 days); Stage 4 (15-21 days); and Stage 5 (22-31 days). QCT was performed using a threshold-based quantitative analysis to segment the lung according to different Hounsfield unit (HU) intervals. The primary outcomes were changes in percentage of compromised lung volume (%CL, - 500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders.
Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (- 3.27% [95% CI, - 5.86 to - 0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P < 0.01). Steroid therapy was associated with decrease in %CL after stage 3 (all P < 0.05), but not at stage 2. Similarly, steroid therapy was associated with a more significant decrease in %CL in the high CL group (P < 0.05), but not in the low CL group.
Steroid administration was independently associated with a decrease in %CL, with interaction by duration or disease severity in a longitudinal cohort. The quantitative CT parameters, particularly compromised lung volume, may provide a useful tool to monitor COVID-19 progression during the treatment process. Trial registration Clinicaltrials.gov, NCT04953247. Registered July 7, 2021, https://clinicaltrials.gov/ct2/show/NCT04953247.
定量计算机断层扫描(QCT)分析可作为评估 2019 年冠状病毒病(COVID-19)严重程度和监测其进展的工具。本研究旨在评估 COVID-19 纵向队列中类固醇治疗与定量 CT 参数之间的关系。
2020 年 2 月 7 日至 2 月 17 日,回顾性纳入 72 例重症 COVID-19 患者。收集所有 300 例胸部 CT 扫描,根据住院至随访 CT 扫描的时间间隔将其分为五个阶段:阶段 1(入院时);阶段 2(3-7 天);阶段 3(8-14 天);阶段 4(15-21 天);阶段 5(22-31 天)。使用基于阈值的定量分析对肺进行分段,根据不同的 Hounsfield 单位(HU)间隔。主要结局是不同阶段时受累肺容积百分比(%CL,-500 至 100 HU)的变化。调整潜在混杂因素后,采用多变量广义估计方程进行分析。
72 例患者中,31 例(43.1%)接受了类固醇治疗。调整持续时间和基线%CL 后,类固醇治疗与%CL 下降(-3.27%[95%CI,-5.86 至 -0.68,P=0.01])相关。类固醇治疗与%CL 变化之间的关系在不同阶段或基线%CL 之间存在差异(所有交互作用,P<0.01)。类固醇治疗与第 3 阶段后%CL 下降相关(所有 P<0.05),但在第 2 阶段无相关性。同样,类固醇治疗与高 CL 组中%CL 的显著下降相关(P<0.05),但与低 CL 组无相关性。
在纵向队列中,类固醇治疗与%CL 下降独立相关,且与治疗持续时间或疾病严重程度存在交互作用。定量 CT 参数,特别是受累肺容积,可能为监测 COVID-19 治疗过程中的进展提供有用的工具。
Clinicaltrials.gov,NCT04953247。2021 年 7 月 7 日注册,https://clinicaltrials.gov/ct2/show/NCT04953247。