Lightowler Maria S, Sander Julia Verena, García de Casasola Sánchez Gonzalo, Mateos González Maria, Güerri-Fernández Robert, Lorenzo Navarro Maria Dolores, Nackers Fabienne, Stratta Erin, Lanusse Candelaria, Huerga Helena
Epicentre, 75019 Paris, France.
Médecins Sans Frontières, 08005 Barcelona, Spain.
J Clin Med. 2024 Jun 2;13(11):3282. doi: 10.3390/jcm13113282.
: During the COVID-19 pandemic and the burden on hospital resources, the rapid categorization of high-risk COVID-19 patients became essential, and lung ultrasound (LUS) emerged as an alternative to chest computed tomography, offering speed, non-ionizing, repeatable, and bedside assessments. Various LUS score systems have been used, yet there is no consensus on an optimal severity cut-off. We assessed the performance of a 12-zone LUS score to identify adult COVID-19 patients with severe lung involvement using oxygen saturation (SpO)/fractional inspired oxygen (FiO) ratio as a reference standard to define the best cut-off for predicting adverse outcomes. : We conducted a single-centre prospective study (August 2020-April 2021) at Hospital del Mar, Barcelona, Spain. Upon admission to the general ward or intensive care unit (ICU), clinicians performed LUS in adult patients with confirmed COVID-19 pneumonia. Severe lung involvement was defined as a SpO/FiO ratio <315. The LUS score ranged from 0 to 36 based on the aeration patterns. : 248 patients were included. The admission LUS score showed moderate performance in identifying a SpO/FiO ratio <315 (area under the ROC curve: 0.71; 95%CI 0.64-0.77). After adjustment for COVID-19 risk factors, an admission LUS score ≥17 was associated with an increased risk of in-hospital death (OR 5.31; 95%CI: 1.38-20.4), ICU admission (OR 3.50; 95%CI: 1.37-8.94) and need for IMV (OR 3.31; 95%CI: 1.19-9.13). : Although the admission LUS score had limited performance in identifying severe lung involvement, a cut-off ≥17 score was associated with an increased risk of adverse outcomes. and could play a role in the rapid categorization of COVID-19 pneumonia patients, anticipating the need for advanced care.
在新冠疫情期间，鉴于医院资源所承受的压力，对高危新冠患者进行快速分类变得至关重要，而肺部超声（LUS）作为胸部计算机断层扫描的替代方法应运而生，它具有快速、非电离、可重复以及能在床边进行评估的特点。人们使用了各种LUS评分系统，但对于最佳严重程度临界值尚未达成共识。我们评估了一种12区LUS评分在识别有严重肺部受累的成年新冠患者方面的表现，以氧饱和度（SpO）/吸入氧分数（FiO）比值作为参考标准来确定预测不良结局的最佳临界值。
我们在西班牙巴塞罗那的德尔马医院进行了一项单中心前瞻性研究（2020年8月至2021年4月）。成年确诊新冠肺炎患者入住普通病房或重症监护病房（ICU）时，临床医生对其进行LUS检查。严重肺部受累定义为SpO/FiO比值<315。根据通气模式，LUS评分范围为0至36分。
共纳入248例患者。入院时的LUS评分在识别SpO/FiO比值<315方面表现中等（ROC曲线下面积：0.71；95%置信区间0.64 - 0.77）。在对新冠危险因素进行调整后，入院时LUS评分≥17与院内死亡风险增加相关（比值比5.31；95%置信区间：1.38 - 20.4）、入住ICU风险增加相关（比值比3.50；95%置信区间：1.37 - 8.94）以及需要机械通气风险增加相关（比值比3.31；95%置信区间：1.19 - 9.13）。
尽管入院时的LUS评分在识别严重肺部受累方面表现有限，但临界值≥17分与不良结局风险增加相关，并且可以在新冠肺炎患者的快速分类中发挥作用，预判对高级护理的需求。
