抽象的
In COVID-19 the right lung has higher degree of opacification on plain radiograph than the left lung. Right lung opacificiation is a stronger predictor for critical care admission and death.https://bit.ly/36dig2n
To the Editor:
全球对2019年冠状病毒疾病的反应(Covid-19)导致了大量研究。通过电子健康记录(EHR)获得数据的应计促进了数据集的有效询问。的确,已经以这种方式探讨了许多与COVID-19的相关问题,这是种族或血管紧张素转化酶对结果的影响,仅举两个[1,2]。
Large teaching hospitals in the capital were at the forefront of the COVID-19 outbreak in the UK, with over 1000 patients admitted in under 1 month. Research teams mobilised quickly to understand this new and unprecedented disease. We extracted data from our EHR to build a risk score that predicted critical care admission or death. The model included demographics, laboratory data and chest radiographic (CXR) severity [3]。
The extent of CXR abnormality was scored using an adapted radiographic assessment of lung oedema for COVID-19, as proposed by Wonget al.[4]。The severity score attributes a number between 0 and 4 to each lung depending on extent of consolidation or ground glass opacification as follows: a score of 0 corresponding to no disease; 1 corresponding to <25% extent; 2 to 25–49%; 3 to 50–75%; and a score of 4 corresponding to >75% extent.
评估了1389例COVID-19的连续患者的入院CXR。前200个X光片由两个独立的得分手评估:评估者间一致性很高(90.5%)。随后对肺部评分之间的回顾表明中等一致(r = 0.72;κ= 0.52)。
比较通过肺部不透明程度的多choric相关性显示出显着差异(p <0.0001)。惊人的差异是最严重的类别。右肺更有可能被分配4:11%的最高范围得分versus左肺中有6%。此外,右肺的不透明是接受重症监护或死亡的更强有力的预测指标(图1)。这一发现尚未报道,也没有以其他成像方式报道。我们承认工作中的重要局限性。我们没有考虑投影图像质量(e.g.anterior or posterior views). The scoring was done by acute physicians rather than radiologists.
The explanation for the apparent differential lung involvement in COVID-19 is unclear. If the finding is confirmed, it may offer insights into the pathobiology of COVID-19 in the lungs. The explanation may lie in anatomy: the right lung is anatomically larger than the left, with a larger main bronchus diameter and more segmental bronchi, possibly increasing viral delivery to respiratory epithelial surfaces. Conversely, it is also possible that the lung scoring is subject to perception bias with the cardiac silhouette distracting from left lung abnormalities. To our knowledge asymmetrical radiographic involvement in interstitial lung disease has not been previously reported.
作为一个对机器学习兴趣的研究小组,反思人类观察的力量很有趣。我们期待使用其他工具(例如体积计算机断层扫描)在其他人群中探索这种模式。
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脚注
Conflict of interest: D. Nagra has nothing to disclose.
Conflict of interest: M. Russell has nothing to disclose.
利益冲突:M。Yates没有什么可披露的。
Conflict of interest: J. Galloway has nothing to disclose.
Conflict of interest: R. Barker has nothing to disclose.
Conflict of interest: S.R. Desai has nothing to disclose.
利益冲突:S。Norton没有什么可披露的。
- 已收到2020年6月15日。
- Accepted2020年9月2日。
- 复制right ©ERS 2020
This version is distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0.