There is growing evidence regarding chest X-ray and computed tomography (CT) findings for coronavirus disease 2019 (COVID-19). At present, the role of lung ultrasonography (LUS) has yet to be explored. The main purpose of this study was to evaluate the correlation between LUS findings and chest CT in patients confirmed to have (positive reverse transcription polymerase chain reaction [RT-PCR]) or clinically highly suspected of having (dyspnea, fever, myasthenia, gastrointestinal symptoms, dry cough, ageusia or anosmia) COVID-19. This prospective study was carried out in the emergency department, where patients confirmed of having or clinically highly suspected of having COVID-19 were recruited and underwent chest CT and concurrent LUS exam. An experienced emergency department physician performed the LUS exam blind to the clinical history and results of the CT scan, which were reviewed by two radiologists in consensus for signs compatible with COVID-19 (bilateral ground-glass opacities in peripheral distribution). A compatible LUS exam was considered a bilateral pattern of B-lines, irregular pleural line and subpleural consolidations. Between March and April 2020, 51 patients were consecutively enrolled. The indication for CT was a negative or indeterminate RT-PCR test (49.0%) followed by suspicion of pulmonary embolism (41.2%). Radiologic signs compatible with COVID-19 were present in 37 patients (72.5%) on CT scan and 40 patients (78.4%) on LUS exam. The presence of LUS findings was correlated with a positive CT scan suggestive of COVID-19 (odds ratio: 13.3, 95% confidence interval: 4.5–39.6, p < 0.001) with a sensitivity of 100.0%, specificity of 78.6%, positive predictive value of 92.5% and negative predictive value of 100.0%. There was no missed diagnosis of COVID-19 with LUS compared with CT in our cohort. The correlation between LUS score and CT total severity score was good (intraclass correlation coefficient: 0.803, 95% confidence interval: 0.60–0.90, p < 0.001). LUS exhibited similar accuracy compared with chest CT in the detection of lung abnormalities in COVID-19 patients.

COVID-19 has caused great devastation in the past year. Multi-organ point-of-care ultrasound (PoCUS) including lung ultrasound (LUS) and focused cardiac ultrasound (FoCUS) as a clinical adjunct has played a significant role in triaging, diagnosis and medical management of COVID-19 patients. The expert panel from 27 countries and 6 continents with considerable experience of direct application of PoCUS on COVID-19 patients presents evidence-based consensus using GRADE methodology for the quality of evidence and an expedited, modified-Delphi process for the strength of expert consensus. The use of ultrasound is suggested in many clinical situations related to respiratory, cardiovascular and thromboembolic aspects of COVID-19, comparing well with other imaging modalities. The limitations due to insufficient data are highlighted as opportunities for future research.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

IntroductionCoronavirus disease 2019 (COVID-19) is a highly contagious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pneumonia and acute respiratory distress syndrome (ARDS) are the most common severe complications. There is growing evidence regarding the imaging findings of COVID-19 in chest X-rays and computed tomography (CT) scans; however, their availability to clinical staff in this pandemic outbreak might be compromised. At this moment, the role of lung ultrasound (LUS) has yet to be explored. The purpose of this case report is to describe the natural course of the disease in mild infection managed at home. Case reportWe report a 35-year-old man with recently diagnosed COVID-19 infection. Clinical examination was unremarkable. The diagnosis of mild disease was made clinically which was later reaffirmed by LUS after identifying a bilateral small pleural effusion and a thickened pleural line. During follow up, subpleural consolidations appeared before symptoms slightly aggravated (cough, tiredness and fever). The patient's condition improved after adjustment of therapy at home. ConclusionLUS is an excellent tool in the characterisation of COVID-19 infection and is more available than CT or X-ray. We emphasise the utility and the opportunity that LUS presents in some clinical scenarios, like this COVID-19 pandemic, and how it may serve as a monitoring and therapy guide.