The association of lung ultrasound images with COVID-19 infection in an emergency room cohort - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Anaesthesia Année : 2020

The association of lung ultrasound images with COVID-19 infection in an emergency room cohort

(1, 2) , , (1, 2, 3) , (4) , , , (5) , (6) , (1)
1
2
3
4
5
6

Résumé

Lung ultrasound could facilitate the triage of patients with suspected COVID-19 infection admitted to the emergency room. We developed a predictive model for COVID-19 diagnosis based on lung ultrasound and clinical features. We used ultrasound to image the lung bilaterally at two anterior sites, one and two hands below each clavicle, and a posterolateral site that was the posterior transverse continuation from the lower anterior site. We studied 100 patients, 31 of whom had a COVID-19 positive reverse transcriptase polymerase chain reaction. A positive test was independently associated with: quick sequential organ failure assessment score >= 1; >= 3 B-lines at the upper site; consolidation and thickened pleura at the lower site; and thickened pleura line at the posterolateral site. The model discrimination was an area (95%CI) under the receiver operating characteristic curve of 0.82 (0.75-0.90). The characteristics (95%CI) of the model's diagnostic threshold, applied to the population from which it was derived, were: sensitivity, 97% (83-100%); specificity, 62% (50-74%); positive predictive value, 54% (41-98%); and negative predictive value, 98% (88-99%). This model may facilitate triage of patients with suspected COVID-19 infection admitted to the emergency room.

Dates et versions

hal-03576421 , version 1 (16-02-2022)

Identifiants

Citer

Stéphane Bar, A. Lecourtois, Hervé Dupont, M. Diouf, E. Goldberg, et al.. The association of lung ultrasound images with COVID-19 infection in an emergency room cohort. Anaesthesia, 2020, 75 (12), pp.1620-1625. ⟨10.1111/anae.15175⟩. ⟨hal-03576421⟩
18 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook Twitter LinkedIn More