Cardiac adipose tissue volume assessed by computed tomography is a specific and independent predictor of early mortality and critical illness in COVID-19 in type 2-diabetic patients

Beyond body mass index: exploring the role of visceral adipose tissue in intensive care unit outcomes

Obesity is a worldwide health crisis and poses significant challenges in critical care. Many studies suggest an 'obesity paradox', in which obesity, defined by body mass index (BMI), is associated with better outcomes. However, the inability of BMI to discriminate between fat and muscle or between visceral adipose tissue and subcutaneous adipose tissue, limits its prediction of metabolic ill health. We suggest that the 'obesity paradox' may be more reflective of the limitations of BMI than the protective effect of obesity. We explore the biological processes leading to visceral fat accumulation, and the evidence linking it to outcomes in critical illness. In the 'spillover' hypothesis of adipose tissue expansion, caloric excess and impaired expansion of storage capacity in the subcutaneous adipose tissue lead to accumulation of visceral adipose tissue. This is associated with a chronic inflammatory state, which is integral to the link between visceral adiposity, type 2 diabetes mellitus, and ischaemic heart disease. We review the current evidence on visceral adiposity and critical illness outcomes. In COVID-19, increased visceral adipose tissue, irrespective of BMI, is associated with more severe disease. This is mirrored in acute pancreatitis, suggesting visceral adiposity is linked to poorer outcomes in some hyperinflammatory conditions. We suggest that visceral adiposity's chronic inflammatory state may potentiate acute inflammation in conditions such as COVID-19 and acute pancreatitis. Further work is required to investigate other critical illnesses, especially sepsis and acute respiratory distress syndrome, in which current evidence is scarce. This may give further insights into pathophysiology and inform tailored treatment and nutrition strategies based on body fat distribution.

Association between visceral adipose tissue and total testosterone among the United States male adults: a cross-sectional study

Visceral adipose tissue (VAT) is regarded as an important risk factor for obesity-related diseases. The results of the association between VAT and total testosterone (TT) are controversial and whether this association is nonlinear is still unknown. 3971 male participants who were aged 20-59 years from the National Health and Nutrition Examination Surveys 2011-2016 were included. VAT area was measured by dual-energy x-ray absorptiometry. TT in serum was assessed utilizing the isotope dilution liquid chromatography-tandem mass spectrometry technique. Linear regression models assessed the associations between VAT area and TT. A restricted cubic spline model was employed to investigate nonlinear relationships. A two-piecewise linear regression model was applied to determine the threshold effect. Subgroup analyses were conducted. The weighted methods were utilized in all analyses. VAT area was inversely associated with TT in the crude and adjusted models. In the fully adjusted model, VAT area was associated with TT (β = -0.59, 95% confidence interval [CI] = -0.74, -0.43) and compared to the first tertile of VAT area, the second and the third tertile had a lower TT level, the β and 95% CI = -65.49 (-83.72, -47.25) and -97.57 (-121.86, -73.27) respectively. We found these inverse associations were nonlinear. The cutoff point of the VAT area was 126 cm2. When the VAT area was <126 cm2, VAT area was significantly associated with a lower TT level (β = -1.55, 95% CI = -1.93 to -1.17, p < 0.0001). However, when the VAT area was ≥126 cm2, this association was less apparent (β = -0.26, 95% CI = -0.52 to 0.01, p = 0.06). No significant interactions among different ages (<50 or ≥50 years), marital, and physical activity status were found. These findings underscore the potential for VAT area as a modifiable indicator for improving testosterone deficiency.

Subcutaneous adipose tissue measured by computed tomography could be an independent predictor for early outcomes of patients with severe COVID-19

Background

Patients with severe Coronavirus Disease 2019 (COVID-19) can experience protein loss due to the inflammatory response and energy consumption, impairing immune function. The presence of excessive visceral and heart fat leads to chronic long-term inflammation that can adversely affect immune function and, thus, outcomes for these patients. We aimed to explore the roles of prognostic nutrition index (PNI) and quantitative fat assessment based on computed tomography (CT) scans in predicting the outcomes of patients with severe COVID-19.

Methods

A total of 130 patients with severe COVID-19 who were treated between December 1, 2022, and February 28, 2023, were retrospectively enrolled. The patients were divided into survival and death groups. Data on chest CT examinations following admission were collected to measure cardiac adipose tissue (CAT), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) and to analyze the CT score of pulmonary lesions. Clinical information and laboratory examination data were collected. Univariate and multivariate logistic regression analyses were used to explore the risk factors associated with death, and several multivariate logistic regression models were established.

Results

Of the 130 patients included in the study (median age, 80.5 years; males, 32%), 68 patients died and 62 patients survived. PNI showed a strong association with the outcome of severe COVID-19 (p < 0.001). Among each part of the fat volume obtained based on a CT scan, SAT showed a significant association with the mortality of severe COVID-19 patients (p = 0.007). However, VAT and CAT were not significantly correlated with the death of patients. In the multivariate models, SAT had a higher predictive value than PNI; the area under the curve (AUC) of SAT was 0.844, which was higher than that of PNI (AUC = 0.833), but in the model of the combination of the two indexes, the prediction did not improve (AUC = 0.830), and SAT lost its significance (p = 0.069).

Conclusion

Subcutaneous adipose tissue measured by computed tomography and PNI were found to be independent predictors of death in patients with severe COVID-19.

The epicardial adipose tissue confined in the atrioventricular groove can be used to assess atrial adipose tissue and atrial dysfunction in cardiac magnetic resonance imaging

Aims

The growing interest in epicardial adipose tissue (EAT) as a biomarker of atrial fibrillation is limited by the difficulties in isolating EAT from other paracardial adipose tissues. We tested the feasibility and value of measuring the pure EAT contained in the atrioventricular groove (GEAT) using cardiovascular magnetic resonance (CMR) imaging in patients with distinct metabolic disorders.

Methods and results

CMR was performed on 100 patients from the MetaCardis cohort: obese (n = 18), metabolic syndrome (MSD) (n = 25), type-2 diabetes (T2D) (n = 42), and age- and gender-matched healthy controls (n = 15). GEAT volume measured from long-axis views was obtained in all patients with a strong correlation between GEAT and atrial EAT (r = 0.95; P < 0.0001). GEAT volume was higher in the three groups of patients with metabolic disorders and highest in the MSD group compared with controls. GEAT volume, as well as body mass and body fat, allowed obese, T2D, and MSD patients to be distinguished from controls. GEAT T1 relaxation and peak longitudinal left atrial (LA) strain in CMR were decreased in T2D patients. Logistic regression and random forest machine learning methods were used to create an algorithm combining GEAT volume, GEAT T1, and peak LA strain to identify T2D patients from other groups with an area under curve (AUC) of 0.81 (Se: 77%, Spe: 80%; 95% confidence interval 0.72-0.91, P < 0.0001).

Conclusion

Atrioventricular groove adipose tissue characteristics measured during routine CMR can be used as a proxy of atrial EAT and integrated in a multi-parametric CMR biomarker for early identification of atrial cardiomyopathy.

Role of Cardiovascular Imaging in Risk Assessment: Recent Advances, Gaps in Evidence, and Future Directions

Optimal risk assessment for primary prevention remains highly challenging. Recent registries have highlighted major discrepancies between guidelines and daily practice. Although guidelines have improved over time and provide updated risk scores, they still fail to identify a significant proportion of at-risk individuals, who then miss out on effective prevention measures until their initial ischemic events. Cardiovascular imaging is progressively assuming an increasingly pivotal role, playing a crucial part in enhancing the meticulous categorization of individuals according to their risk profiles, thus enabling the customization of precise therapeutic strategies for patients with increased cardiovascular risks. For the most part, the current approach to patients with atherosclerotic cardiovascular disease (ASCVD) is homogeneous. However, data from registries (e.g., REACH, CORONOR) and randomized clinical trials (e.g., COMPASS, FOURIER, and ODYSSEY outcomes) highlight heterogeneity in the risks of recurrent ischemic events, which are especially higher in patients with poly-vascular disease and/or multivessel coronary disease. This indicates the need for a more individualized strategy and further research to improve definitions of individual residual risk, with a view of intensifying treatments in the subgroups with very high residual risk. In this narrative review, we discuss advances in cardiovascular imaging, its current place in the guidelines, the gaps in evidence, and perspectives for primary and secondary prevention to improve risk assessment and therapeutic strategies using cardiovascular imaging.

Cyclophilins modify their profile depending on the organ or tissue in a murine inflammatory model

Inflammation is the leading subjacent cause of many chronic diseases. Despite several studies in the last decades, the molecular mechanism involving its pathophysiology is not fully known. Recently, the implication of cyclophilins in inflammatory-based diseases has been demonstrated. However, the main role of cyclophilins in these processes remains elusive. Hence, a mouse model of systemic inflammation was used to better understand the relationship between cyclophilins and their tissue distribution. To induce inflammation, mice were fed with high-fat diet for 10 weeks. In these conditions, serum levels of interleukins 2 and 6, tumour necrosis factor-α, interferon-ϒ, and the monocyte chemoattractant protein 1 were elevated, evidencing a systemic inflammatory state. Then, in this inflammatory model, cyclophilins and CD147 profiles in the aorta, liver, and kidney were studied. The results demonstrate that, upon inflammatory conditions, cyclophilins A and C expression levels were increased in the aorta. Cyclophilins A and D were augmented in the liver, meanwhile, cyclophilins B and C were diminished. In the kidney, cyclophilins B and C levels were elevated. Furthermore, CD147 receptor was also increased in the aorta, liver, and kidney. In addition, when cyclophilin A was modulated, serum levels of inflammatory mediators were decreased, indicating a reduction in systemic inflammation. Besides, the expression levels of cyclophilin A and CD147 were also reduced in the aorta and liver, when cyclophilin A was modulated. Therefore, these results suggest that each cyclophilin has a different profile depending on the tissue, under inflammatory conditions.