Background
Lower muscle mass is a known predictor of unfavorable outcome, but its prognostic impact on COVID-19 patients is unknown.
Purpose
To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in COVID-19 patients.
Materials and Methods
Clinical/laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed COVID-19, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. Extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation of paravertebral muscles were measured on axial CT images at T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation odds ratios (OR) with 95% confidence intervals (CIs), were used to build four models to predict ICU admission and death, tested and compared using receiver operating characteristic curve (ROC) analysis.
Results
A total 552 patients (364 men; median age 65 years, interquartile range 54–75) were included. In a CT-based model, lower-than-median T5 paravertebral muscle area showed the highest ORs for ICU admission (OR 4.8, 95% CI 2.7–8.5;
P
<.001) and death (OR 2.3, 95% CI 1.0–2.9;
P
=.027). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle area still showed the highest ORs both for ICU admission (OR 4.3; 95% CI 2.5–7.7;
P
<.001) and death (OR 2.3, 95% CI 1.3–3.7;
P
=.001). At ROC analysis, the CT-based model and the model including clinical variables showed the same area under the curve (AUC) for ICU admission prediction (AUC 0.83,
P
=.380) and were not different in predicting death (AUC 0.86 versus AUC 0.87, respectively,
P
=.282).
Conclusion
In hospitalized patients with COVID-19, lower muscle mass on CT was independently associated with ICU admission and hospital mortality.
The aortic arch classification is associated with a consistent geometric pattern of the aortic arch map, which identifies specific proximal landing zones with suboptimal angulation for stent graft deployment. Arches II and III also appear to have progressively less favorable anatomy for thoracic endovascular aortic repair compared with arch I.
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Epicardial adipose tissue (EAT) is a metabolically activated beige adipose tissue, non-homogeneously surrounding the myocardium. Physiologically, EAT regulates toxic fatty acids, protects the coronary arteries against mechanical strain, regulates proinflammatory cytokines, stimulates the production of nitric oxide, reduces oxidative stress, and works as a thermogenic source against hypothermia. Conversely, EAT has pathologic paracrine interactions with the surrounded vessels, and might favour the onset of atrial fibrillation. In addition, initial atherosclerotic lesions can promote inflammation and trigger the EAT production of cytokines increasing vascular inflammation, which, in turn, may help the development of collateral vessels but also of self-stimulating, dysregulated inflammatory process, increasing coronary artery disease severity. Variations in EAT were also linked to metabolic syndrome. Echocardiography first estimated EAT measuring its thickness on the free wall of the right ventricle but does not allow accurate volumetric EAT estimates. Cardiac CT (CCT) and cardiac MR (CMR) allow for three-dimensional EAT estimates, the former showing higher spatial resolution and reproducibility but being limited by radiation exposure and long segmentation times, the latter being radiation-free but limited by lower spatial resolution and reproducibility, higher cost, and difficulties for obese patients. EAT radiodensity at CCT could to be related to underlying metabolic processes. The correlation between EAT and response to certain pharmacological therapies has also been investigated, showing promising results. In the future, semi-automatic or fully automatic techniques, machine/deep-learning methods, if validated, will facilitate research for various EAT measures and may find a place in CCT/CMR reporting.
A significant reduction of high-attenuation artifacts can be achieved by use of higher monoenergetic energy levels with cardiac DECT. However, image noise in anatomic structures affected by artifacts is lowest at 80 keV, which suggests an evaluation approach that makes use of multiple energy levels for a complete diagnosis.
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