Coronary artery calcification on low-dose chest CT is an early predictor of severe progression of COVID-19-A multi-center, multi-vendor study.

PURPOSE: Cardiovascular comorbidity anticipates severe progression of COVID-19 and becomes evident by coronary artery calcification (CAC) on low-dose chest computed tomography (LDCT). The purpose of this study was to predict a patient's obligation of intensive care treatment by evaluating the coronary calcium burden on the initial diagnostic LDCT. METHODS: Eighty-nine consecutive patients with parallel LDCT and positive RT-PCR for SARS-CoV-2 were included from three centers. The primary endpoint was admission to ICU, tracheal intubation, or death in the 22-day follow-up period. CAC burden was represented by the Agatston score. Multivariate logistic regression was modeled for prediction of the primary endpoint by the independent variables "Agatston score > 0", as well as the CT lung involvement score, patient sex, age, clinical predictors of severe COVID-19 progression (history of hypertension, diabetes, prior cardiovascular event, active smoking, or hyperlipidemia), and laboratory parameters (creatinine, C-reactive protein, leucocyte, as well as thrombocyte counts, relative lymphocyte count, d-dimer, and lactate dehydrogenase levels). RESULTS: After excluding multicollinearity, "Agatston score >0" was an independent regressor within multivariate analysis for prediction of the primary endpoint (p<0.01). Further independent regressors were creatinine (p = 0.02) and leucocyte count (p = 0.04). The Agatston score was significantly higher for COVID-19 cases which completed the primary endpoint (64.2 [interquartile range 1.7-409.4] vs. 0 [interquartile range 0-0]). CONCLUSION: CAC scoring on LDCT might help to predict future obligation of intensive care treatment at the day of patient admission to the hospital.

Calcification of the thoracic aorta on low-dose chest CT predicts severe COVID-19.

BACKGROUND: Cardiovascular comorbidity anticipates poor prognosis of SARS-CoV-2 disease (COVID-19) and correlates with the systemic atherosclerotic transformation of the arterial vessels. The amount of aortic wall calcification (AWC) can be estimated on low-dose chest CT. We suggest quantification of AWC on the low-dose chest CT, which is initially performed for the diagnosis of COVID-19, to screen for patients at risk of severe COVID-19. METHODS: Seventy consecutive patients (46 in center 1, 24 in center 2) with parallel low-dose chest CT and positive RT-PCR for SARS-CoV-2 were included in our multi-center, multi-vendor study. The outcome was rated moderate (no hospitalization, hospitalization) and severe (ICU, tracheal intubation, death), the latter implying a requirement for intensive care treatment. The amount of AWC was quantified with the CT vendor's software. RESULTS: Of 70 included patients, 38 developed a moderate, and 32 a severe COVID-19. The average volume of AWC was significantly higher throughout the subgroup with severe COVID-19, when compared to moderate cases (771.7 mm3 (Q1 = 49.8 mm3, Q3 = 3065.5 mm3) vs. 0 mm3 (Q1 = 0 mm3, Q3 = 57.3 mm3)). Within multivariate regression analysis, including AWC, patient age and sex, as well as a cardiovascular comorbidity score, the volume of AWC was the only significant regressor for severe COVID-19 (p = 0.004). For AWC > 3000 mm3, the logistic regression predicts risk for a severe progression of 0.78. If there are no visually detectable AWC risk for severe progression is 0.13, only. CONCLUSION: AWC seems to be an independent biomarker for the prediction of severe progression and intensive care treatment of COVID-19 already at the time of patient admission to the hospital; verification in a larger multi-center, multi-vendor study is desired.

Early extrapulmonary prognostic features in chest computed tomography in COVID-19 pneumonia: Bone mineral density is a relevant predictor for the clinical outcome - A multicenter feasibility study.

BACKGROUND: Besides throat-nose swab polymerase chain reaction (PCR), unenhanced chest computed tomography (CT) is a recommended diagnostic tool for early detection and quantification of pulmonary changes in COVID-19 pneumonia caused by the novel corona virus. Demographic factors, especially age and comorbidities, are major determinants of the outcome in COVID-19 infection. This study examines the extra pulmonary parameter of bone mineral density (BMD) from an initial chest computed tomography as an associated variable of pre-existing comorbidities like chronic lung disease or demographic factors to determine the later patient's outcome, in particular whether treatment on an intensive care unit (ICU) was necessary in infected patients. METHODS: We analyzed 58 PCR-confirmed COVID-19 infections that received an unenhanced CT at admission at one of the included centers. In addition to the extent of pulmonary involvement, we performed a phantomless assessment of bone mineral density of thoracic vertebra 9-12. RESULTS: In a univariate regression analysis BMD was found to be a significant predictor of the necessity for intensive care unit treatment of COVID-19 patients. In the subgroup requiring intensive care treatment within the follow-up period a significantly lower BMD was found. In a multivariate logistic regression model considering gender, age and CT measurements of bone mineral density, BMD was eliminated from the regression analysis as a significant predictor. CONCLUSION: Phantomless assessed BMD provides prognostic information on the necessity for ICU treatment in course of COVID-19 pneumonia. We recommend using the measurement of BMD in an initial CT image to facilitate a potentially better prediction of severe patient outcomes within the 22 days after an initial CT scan. Consequently, in the present sample, additional bone density analysis did not result in a prognostic advantage over simply considering age. Significantly larger patient cohorts with a more homogenous patient age should be performed in the future to illustrate potential effects. CLINICAL RELEVANCE: While clinical capacities such as ICU beds and ventilators are more crucial than ever to help manage the current global corona pandemic, this work introduces an approach that can be used in a cost-effective way to help determine the amount of these rare clinical resources required in the near future.