Point-of-care lung ultrasound assessment for risk stratification and therapy guiding in COVID-19 patients. A prospective non-interventional study

Rubio-Gracia, Jorge; Giménez-López, Ignacio; Garcés-Horna, Vanesa; López-Delgado, Daniel; Sierra-Monzón, Jose Luis; Martínez-Lostao, Luis; Josa-Laorden, Claudia; Ruiz-Laiglesia, Fernando; Pérez-Calvo, Juan Ignacio; Crespo-Aznarez, Silvia; García-Lafuente, Javier; Peña Fresneda, Natasha; Amores Arriaga, Beatriz; Gracia-Tello, Borja; Sánchez-Marteles, Marta

BACKGROUND: Lung ultrasound (LUS) is feasible for assessing lung injury caused by COVID-19. However, the prognostic meaning and time-line changes of lung injury assessed by LUS in COVID-19 hospitalised patients, is unknown. METHODS: Prospective cohort study designed to analyse prognostic value of LUS in COVID-19 patients by using a quantitative scale (LUZ-score) during the first 72 h after admission. Primary endpoint was in-hospital death and/or admission to the intensive care unit. Total length of hospital stay, increase of oxygen flow or escalate medical treatment during the first 72 h, were secondary endpoints. RESULTS: 130 patients were included in the final analysis; mean age was 56.7±13.5 years. Time since the beginning of symptoms until admission was 6 days (4–9). Lung injury assessed by LUZ-score did not differ during the first 72 h (21 points [16–26] at admission versus 20 points [16–27] at 72 h; p=0.183). In univariable logistic regression analysis estimated PaO2/FiO2 (HR 0.99 [0.98–0.99]; p=0.027) and LUZ-score>22 points (5.45 (1.42–20.90); p=0.013) were predictors for the primary endpoint. CONCLUSIONS: LUZ-score is an easy, simple and fast point of care ultrasound tool to identify patients with severe lung injury due to COVID-19, upon admission. Baseline score is predictive of severity along the whole period of hospitalisation. The score facilitates early implementation or intensification of treatment for COVID-19 infection. LUZ-score may be combined with clinical variables (as estimated PAFI) to further refine risk stratification.