Blood glucose and epicardial adipose tissue at the hospital admission as possible predictors for COVID-19 severity.

PURPOSE: To study the possible association of CT-derived quantitative epicardial adipose tissue (EAT) and glycemia at the admission, with severe outcomes in patients with COVID-19. METHODS: Two hundred and twenty-nine patients consecutively hospitalized for COVID-19 from March 1st to June 30th 2020 were studied. Non contrast chest CT scans, to confirm diagnosis of pneumonia, were performed. EAT volume (cm3) and attenuation (Hounsfield units) were measured using a CT post-processing software. The primary outcome was acute respiratory distress syndrome (ARDS) or in-hospital death. RESULTS: The primary outcome occurred in 56.8% patients. Fasting blood glucose was significantly higher in the group ARDS/death than in the group with better prognosis [114 (98-144) vs. 101 (91-118) mg/dl, p = 0.001]. EAT volume was higher in patients with vs without the primary outcome [103 (69.25; 129.75) vs. 78.95 (50.7; 100.25) cm3, p < 0.001] and it was positively correlated with glycemia, PCR, fibrinogen, P/F ratio. In the multivariable logistic regression analysis, age and EAT volume were independently associated with ARDS/death. Glycemia and EAT attenuation would appear to be factors involved in ARDS/death with a trend of statistical significance. CONCLUSIONS: Our findings suggest that both blood glucose and EAT, easily measurable and modifiable targets, could be important predisposing factors for severe Covid-19 complications.

Radiographers and COVID-19 pneumonia: Diagnostic performance using CO-RADS.

INTRODUCTION: A more structured role of radiographers is advisable to speed up the management of patients with suspected COVID-19. The purpose of our study was to evaluate the diagnostic performance of radiographers in the detection of COVID-19 pneumonia on chest CT using CO-RADS descriptors. METHODS: CT images of patients who underwent RT-PCR and chest CT due to COVID-19 suspicion between March and July 2020 were analysed retrospectively. Six readers, including two radiologists, two highly experienced radiographers and two less experienced radiographers, independently scored each CT using the CO-RADS lexicon. ROC curves were used to investigate diagnostic accuracy, and Fleiss'κ statistics to evaluate inter-rater agreement. RESULTS: 714 patients (419 men; 295 women; mean age: 64 years ±19SD) were evaluated. CO-RADS> 3 was identified as optimal diagnostic threshold. Highly experienced radiographers achieved an average sensitivity of 58.7% (95%CI: 52.5-64.7), an average specificity of 81.8% (95%CI: 77.9-85.2), and a mean AUC of 0.72 (95%CI: 0.68-0.75). Among less experienced radiographers, an average sensitivity of 56.3% (95%CI: 50.1-62.2) and an average specificity of 81.5% (95%CI: 77.6-84.9) were observed, with a mean AUC of 0.71 (95%CI: 0.68-0.74). Consultant radiologists achieved an average sensitivity of 60.0% (95%CI: 53.7-65.8), an average specificity of 81.7% (95%CI: 77.8-85.1), and a mean AUC of 0.73 (95%CI: 0.70-0.77). CONCLUSION: Radiographers can adequately recognise the classic appearances of COVID-19 on CT, as described by the CO-RADS assessment scheme, in a way comparable to expert radiologists. IMPLICATIONS FOR PRACTICE: Radiographers, as the first healthcare professionals to evaluate CT images in patients with suspected SARS-CoV-2 infection, could diagnose COVID-19 pneumonia by means of a categorical reporting scheme at CT in a reliable way, hence playing a primary role in the early management of these patients.