Zhanna Davidovna Kobalava, Fuad Safarova Ayten, Cabello Montoya Flora Elisa, Vatsik-Gorodetskaya Maria Vasilevna, Yulia Leonidovna Karaulova, Olga Tairovna Zorya, Olga Valeryevna Arutina, Rajan Rajesh, Al Jarallah Mohammed, Brady Peter A, Al-Zakwani Ibrahim
Department of Internal Medicine with the subspecialty of cardiology and functional diagnostics named after V.S. Moiseev, Institute of Medicine, Peoples' Friendship University of Russia (RUDN University), Moscow, Russia.
Clinical Hospital named after V.V. Vinogradov Moscow, Moscow, Russia.
Multidiscip Respir Med. 2021 Jul 21;16(1):766. doi: 10.4081/mrm.2021.766. eCollection 2021 Jan 15.
Lung ultrasound (LUS) is a bedside imaging tool that has proven useful in identifying and assessing the severity of pulmonary pathology. The aim of this study was to determine LUS patterns, their clinical significance, and how they compare to CT findings in hospitalized patients with coronavirus infection.
This observational study included 62 patients (33 men, age 59.3±15.9 years), hospitalized with pneumonia due to COVID-19, who underwent chest CT and bedside LUS on the day of admission. The CT images were analyzed by chest radiographers who calculated a CT visual score based on the expansion and distribution of ground-glass opacities and consolidations. The LUS score was calculated according to the presence, distribution, and severity of anomalies.
All patients had CT findings suggestive of bilateral COVID-19 pneumonia, with an average visual scoring of 8.1±2.9%. LUS identified 4 different abnormalities, with bilateral distribution (mean LUS score: 26.4±6.7), focal areas of non-confluent B lines, diffuse confluent B lines, small sub-pleural micro consolidations with pleural line irregularities, and large parenchymal consolidations with air bronchograms. LUS score was significantly correlated with CT visual scoring (rho = 0.70; p<0.001). Correlation analysis of the CT and LUS severity scores showed good interclass correlation (ICC) (ICC =0.71; 95% confidence interval (CI): 0.52-0.83; p<0.001). Logistic regression was used to determine the cut-off value of ≥27 (area under the curve: 0.97; 95% CI: 90-99; sensitivity 88.5% and specificity 97%) of the LUS severity score that represented severe and critical pulmonary involvement on chest CT (CT: 3-4).
When combined with clinical data, LUS can provide a potent diagnostic aid in patients with suspected COVID-19 pneumonia, reflecting CT findings.
肺部超声(LUS)是一种床旁成像工具,已被证明在识别和评估肺部病变的严重程度方面很有用。本研究的目的是确定住院的冠状病毒感染患者的LUS模式、其临床意义以及与CT结果的比较情况。
这项观察性研究纳入了62例因COVID-19肺炎住院的患者(33名男性,年龄59.3±15.9岁),他们在入院当天接受了胸部CT和床旁LUS检查。胸部放射技师分析CT图像,并根据磨玻璃影和实变的范围及分布计算CT视觉评分。LUS评分根据异常的存在、分布和严重程度进行计算。
所有患者的CT结果均提示双侧COVID-19肺炎,平均视觉评分为8.1±2.9%。LUS识别出4种不同异常,呈双侧分布(平均LUS评分:26.4±6.7),包括非融合性B线的局灶区域、弥漫性融合性B线、伴有胸膜线不规则的小的胸膜下微实变以及伴有空气支气管征的大的实质实变。LUS评分与CT视觉评分显著相关(rho = 0.70;p<0.001)。CT和LUS严重程度评分的相关性分析显示组内相关性良好(ICC)(ICC = 0.71;95%置信区间(CI):0.52 - 0.83;p<0.001)。采用逻辑回归确定LUS严重程度评分≥27(曲线下面积:0.97;95%CI:90 - 99;敏感性88.5%,特异性97%)的截断值,该值代表胸部CT上严重和危重型肺部受累(CT:3 - 4)。
结合临床数据时,LUS可为疑似COVID-19肺炎患者提供有力的诊断辅助,反映CT结果。