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.

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...

Our aim was to determine the effect of the initial pattern of fracture and the displacement of fragments on the outcome of proximal humeral fractures treated conservatively. We followed 93 consecutive patients prospectively for one year. Final movement and strength were compared with those of the contralateral side. The final American Shoulder and Elbow Society score and the Disabilities of Arm, Shoulder and Hand and Short-Form 36 questionnaires were compared with those provided by the patient on the day of the injury. Radiographs and CT scans with three-dimensional reconstruction were obtained in all patients. The pattern of the fracture and the displacement of individual fragments were analysed and correlated with the final outcome. There were two cases of nonunion and six of avascular necrosis. The majority of the fractures (84 patients; 90%) followed one of the following four patterns: posteromedial (varus) impaction in 50 patients (54%), lateral (valgus) impaction in 13 (14%), isolated greater tuberosity in 15 (16%), and anteromedial impaction fracture in six (6%). Head orientation, impaction of the surgical neck and displacement of the tuberosity correlated strongly with the outcome. In fractures with posteromedial impaction, a poor outcome was noted as the articular surface displaced inferiorly increasing its distance from the acromion. A poorer outcome was noted as a fractured greater tuberosity displaced medially overlapping with the posterior articular surface. Lateral impaction fractures had a worse outcome than other patterns of fracture.

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The aim of this study was to determine the radiologic findings associated with admission to the intensive care unit (ICU) and the development of acute respiratory distress syndrome (ARDS) in patients with pH1N1 infection. One hundred and four patients (15-96 years) with laboratory-confirmed pH1N1 infection seen at the Emergency Department from July to December 2009 who underwent chest radiographs were studied. Radiographs were evaluated for consolidation, ground-glass opacities, interstitial patterns, distribution, and extent of findings. Eighty-seven (83.7%) of the patients were managed in the ward, and 17 (16.3%) patients eventually required admission to the ICU. All patients admitted to the ICU showed abnormalities on the initial radiograph. The presence of consolidation, multifocal, diffuse, and bilateral involvement on the initial radiograph was associated with a statistically higher risk of requiring ICU admission (p<0.001). There were no significant differences regarding age, sex, and presence of underlying comorbidities. Evolution to ARDS was found in eight cases that necessitated ICU care. All of them had on the initial radiograph patchy multifocal consolidations (p<0.001) with bilateral lesions in six cases. A higher number of lung zones involved and consolidation on the initial chest radiograph as well as a rapid progression of the radiological abnormalities were identified in patients requiring ICU admission and development of ARDS. Initial chest radiographs show acute abnormalities in all patients with severe disease. The findings of a multifocal patchy consolidation pattern with bilateral or diffuse lung involvement on admission should alert of the impending severity of disease and the risk of necessitating ICU admission.

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INTRODUCTION: There is growing evidence regarding the imaging findings of Coronavirus Disease 2019 (COVID-19), in chest X-ray and Computed Tomography scan (CT). At this moment, the role of Lung Ultrasonography (LUS) has yet to be explored. OBJECTIVES: The main purpose of this study is to evaluate the correlation between LUS findings and chest CT in confirmed (positive RT-PCR) or clinically highly suspicious (dyspnea, fever, myasthenia, gastrointestinal symptoms, dry cough, ageusia or anosmia) of COVID-19 patients. METHODS: Prospective study carried out in the emergency department (ED) of confirmed or clinically highly suspicious COVID-19 patients who were subjected to a chest CT and concurrent LUS exam. An experienced ED 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). Compatible LUS exam was considered a bilateral pattern of B-lines, irregular pleural line and subpleural consolidations. RESULTS: Between March and April 2020, fifty-one 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%). Radiological signs compatible with COVID-19 were present in thirty-seven patients (72.5%) on CT scan and forty patients (78.4%) on LUS exam. The presence of LUS findings was correlated with a positive CT scan suggestive of COVID-19 (OR: 13.3, 95%CI: 4.5-39.6, p<0.001) with a sensitivity of 100.0% and a specificity of 78.6%, positive predictive value of 92.5% and negative of 100.0%. There was no missed diagnosis of COVID-19 with LUS compared to CT in our cohort. The LUS Score had a good correlation with CT total severity score (ICC 0.803, 95% CI 0.60-0.90, p<0.001). CONCLUSION: LUS presents similar accuracy compared to chest CT to detect lung abnormalities in COVID-19 patients.

Background In the past months, several lung ultrasonography (LUS) protocols have been proposed, mainly on previously validated schemes independent of coronavirus disease 2019 . Objectives The main purpose of this study was to determine the impact and accuracy of different LUS protocols proposed in COVID-19. Methods Patients were evaluated with a standard sequence of LUS scans in 72 intercostal spaces along 14 anatomic lines in the chest. A scoring system of LUS findings was reported and then analyzed separately according to each proposed LUS protocol zones. This score was then correlated to a validated Pulmonary Inflammation Index (PII) on chest Computed Tomography (CT). Results Thirty-two patients were enrolled. The most frequent pattern was ground-glass opacities in the chest X-ray (53.1%), chest CT (59.1%) and subpleural or lobar consolidations (40.8%) in the posteroinferior areas (p < 0.001) on LUS. The Interclass Correlation Coefficient (ICC) was significantly correlated with almost every protocol analyzed except the 8-zone (p = 0.119) and the 10-zone protocol that only included one posterior point (p = 0.052). The highest ICC was obtained with a 12-zone protocol (ICC 0.500; p = 0.027) and decreased as more points were included. Conclusions In conclusion, our study results suggest that performing an ultrasound protocol with 12-zone scanning, including the superior and inferior areas of the anterior, lateral and posterior regions of the chest was consistent with higher ICC and higher degree of concordance with CT. We emphasize the need of a more standardization technique to further implement and develop this imaging modality in COVID-19. KeywordsPoint-of-care ultrasonography (POCUS) • Lung ultrasonography (LUS) • Coronavirus disease 2019 (COVID-19) • Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) * Yale Tung-Chen