Lung ultrasound based prediction of CT-scan Severity Score in COVID-19

IF 0.8 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Ultrasound Pub Date : 2023-09-09 DOI:10.1183/13993003.congress-2023.pa1819
Panaiotis Finamore, Emanuele Gilardi, Moises Muley, Tommaso Grandi, Silvia Navarin, Michela Orrù, Chiara Bucci, Simone Scarlata, Francesco Travaglino, Federica Sambuco
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Abstract

Background: CT-scan Severity Score (CT-SS) is the gold standard for the quantification of COVID-19 pneumonia, however CT-scan is not always available. Aims and objectives: Lung ultrasound (LU) is able to identify lung abnormalities, hence we hypothesize that can be used to predict CT-SS. Objectives are to determine whether it is possible to predict CT-SS from the LU score, and whether the change in LU score associates with a change in CT-SS during hospitalization. Methods: This is a retrospective observational study. Hospitalized patients with COVID-19 pneumonia who performed LU within 6 hours from CT-scan were included. Two LU scores, the LU-Mean, calculated by diving the sum of scores of explored chest areas for the total number of areas, and the LU-Sum, calculated as the sum of chest areas with a score ≥ 2, were derived and used to predict CT-SS using linear regression models. The agreement between fitted values and CT-SS was assessed using Bland-Altman plot. The correlation between the change in CT-SS and LU scores was reported using the Pearson correlation index. Results: The median CT-SS was 11 (IQR:6). LU-Mean and LU-Sum were linearly correlated with CT-SS (rLU-Mean=0.78 and rLU-Sum=0.79), with a Beta of 7.34 (P-value<0.001) and 0.94 (P-value<0.001), respectively. Two predictive models, based on LU scores and type of respiratory support, were developed, with an adjusted R-squared of 0.64 and 0.67, respectively. The correlation between the change of CT-SS and LU scores was 0.86 (P-value<0.001) for LU-Mean and 0.87 (P-value<0.001) for LU-Sum. Conclusions: CT-SS can be predicted from LU scores, and its change correlates with that of LU score. LU score can be used to predict CT-SS when CT-scan is not available.
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基于肺部超声预测COVID-19 ct扫描严重程度评分
背景:ct扫描严重程度评分(CT-SS)是量化COVID-19肺炎的金标准,但ct扫描并不总是可用。目的和目的:肺超声(LU)能够识别肺部异常,因此我们假设可以用于预测CT-SS。目的是确定是否可以通过LU评分预测CT-SS,以及LU评分的变化是否与住院期间CT-SS的变化相关。方法:回顾性观察性研究。纳入ct扫描后6小时内行LU的住院COVID-19肺炎患者。得出两个LU评分,即通过对总区域数的探索胸部区域评分之和计算的LU- mean和通过得分≥2的胸部区域之和计算的LU- sum,并使用线性回归模型预测CT-SS。使用Bland-Altman图评估拟合值与CT-SS之间的一致性。使用Pearson相关指数报告CT-SS变化与LU评分之间的相关性。结果:CT-SS中位值为11 (IQR:6)。LU-Mean和LU-Sum与CT-SS呈线性相关(rLU-Mean=0.78, rLU-Sum=0.79),贝塔系数分别为7.34 (p值<0.001)和0.94 (p值<0.001)。建立了两个基于LU评分和呼吸支持类型的预测模型,调整后的r平方分别为0.64和0.67。CT-SS变化与LU评分的相关性LU- mean为0.86 (p值<0.001), LU- sum为0.87 (p值<0.001)。结论:CT-SS可由LU评分预测,其变化与LU评分相关。当ct扫描不可用时,LU评分可用于预测CT-SS。
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来源期刊
Ultrasound
Ultrasound RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
1.70
自引率
0.00%
发文量
55
期刊介绍: Ultrasound is the official journal of the British Medical Ultrasound Society (BMUS), a multidisciplinary, charitable society comprising radiologists, obstetricians, sonographers, physicists and veterinarians amongst others.
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