Prediction Accuracy of Serial Lung Ultrasound in COVID-19 Hospitalized Patients (Pred-Echovid Study).
Juan Torres-MachoMarcos Sánchez-FernándezIrene Arnanz-GonzálezYashdeep Singh PathaniaAna Isabel Franco-MorenoMercedes Duffort-FalcóLuis Beltrán-RomeroSantiago Rodríguez-SuarézMáximo Bernabeu-WittelElena UrbanoManuel Méndez-BailonFernando Roque-RojasElena García-GuijarroGonzalo García De Casasola-SánchezPublished in: Journal of clinical medicine (2021)
The value of serial lung ultrasound (LUS) in patients with COVID-19 is not well defined. In this multicenter prospective observational study, we aimed to assess the prognostic accuracy of serial LUS in patients admitted to hospital due to COVID-19. The serial LUS protocol included two examinations (0-48 h and 72-96 h after admission) using a 10-zones sequence, and a 0 to 5 severity score. Primary combined endpoint was death or the need for invasive mechanical ventilation. Calibration (Hosmer-Lemeshow test and calibration curves), and discrimination power (area under the ROC curve) of both ultrasound exams (SCORE1 and 2), and their difference (DIFFERENTIAL-SCORE) were performed. A total of 469 patients (54.2% women, median age 60 years) were included. The primary endpoint occurred in 51 patients (10.9%). Probability risk tertiles of SCORE1 and SCORE2 (0-11 points, 12-24 points, and ≥25 points) obtained a high calibration. SCORE-2 showed a higher discrimination power than SCORE-1 (AUC 0.72 (0.58-0.85) vs. 0.61 (0.52-0.7)). The DIFFERENTIAL-SCORE showed a higher discrimination power than SCORE-1 and SCORE-2 (AUC 0.78 (0.66-0.9)). An algorithm for clinical decision-making is proposed. Serial lung ultrasound performing two examinations during the first days of hospitalization is an accurate strategy for predicting clinical deterioration of patients with COVID-19.
Keyphrases
- magnetic resonance imaging
- mechanical ventilation
- coronavirus disease
- sars cov
- end stage renal disease
- ejection fraction
- randomized controlled trial
- emergency department
- type diabetes
- decision making
- metabolic syndrome
- chronic kidney disease
- machine learning
- computed tomography
- prognostic factors
- peritoneal dialysis
- pregnant women
- acute respiratory distress syndrome
- insulin resistance
- skeletal muscle
- adipose tissue