Perigenual anterior cingulate cortex and its structural covariance as predictors for future body fat gain in young adults.

OBJECTIVE: This study aimed to examine whether baseline gray matter (GM) volume and structural covariance patterns could predict body fat gain over 1 to 2 years in a relatively large sample. METHODS: Voxel-based morphometry (VBM) analysis was applied to examine the association between baseline GM volume and body fat gain in 502 participants over 1 to 2 years. Furthermore, this study tested whether the structural covariances between the regions identified as seeds from VBM analysis and the rest of the brain were associated with future body fat gain. RESULTS: A significant positive association was observed between baseline GM volume in the perigenual anterior cingulate cortex (pgACC) and body fat gain over 1 to 2 years. Furthermore, relative to those with lower future body fat gain, pgACC covaried more extensively with the middle frontal gyrus, middle temporal gyrus, inferior temporal gyrus, and cerebellum in participants with higher future body fat gain. CONCLUSIONS: Using VBM and structural covariance network analysis, the current study revealed that higher GM volume of pgACC and its increased structural covariances with specific brain regions were associated with future weight gain, which may guide the development of more effective prevention and treatment interventions for obesity.

Visceral to subcutaneous fat ratio predicts short-term mortality in patients with Covid 19. A multicenter study.

OBJECTIVE: To evaluate the association of body composition parameters with outcomes in Covid-19. METHODS: 173 patients hospitalized for Covid-19 infection in 6 European centers were included in this retrospective study. Measurements were performed at L3-level and comprised skeletal muscle index (SMI), muscle density (MD), and adipose tissue measurements [visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), visceral-to-subcutaneous-adipose-tissue-area-ratio (VSR)]. The association with mortality, the need for intubation (MV), and the need for admission to ICU within 30 days were evaluated. RESULTS: Higher SAT density was associated with a greater risk of MV (OR = 1.071, 95%CI=(1.034;1.110), p < 0.001). Higher VAT density was associated with admission to ICU (OR = 1.068, 95%CI=(1.029;1.109), p < 0.001). Higher MD was a protective factor for MV and ICU admission (OR = 0.914, 95%CI=(0.870;0.960), p < 0.001; OR = 0.882, 95%CI=(0.832;0.934), p = 0.028). Higher VSR was associated with mortality (OR = 2.147, 95%CI=(1.022;4.512), p = 0.044). Male sex showed the strongest influence on the risk of ICU admission and MV. SMI was not associated with either parameter. CONCLUSION: In patients hospitalized for Covid-19 infection, higher VSR seems to be a strong prognostic factor of short-term mortality. Weak associations with clinical course were found for MD and adipose tissue measurements. Male sex was the strongest prognostic factor of adverse clinical course. ADVANCES IN KNOWLEDGE: VSR is a prognostic biomarker for 30-day mortality in patients hospitalized for Covid-19 disease.

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.

BACKGROUND: Patients with type 2-diabetes mellitus (T2D), are characterized by visceral and ectopic adipose tissue expansion, leading to systemic chronic low-grade inflammation. As visceral adiposity is associated with severe COVID-19 irrespective of obesity, we aimed to evaluate and compare the predictive value for early intensive care or death of three fat depots (cardiac, visceral and subcutaneous) using computed tomography (CT) at admission for COVID-19 in consecutive patients with and without T2D. METHODS: Two hundred and two patients admitted for COVID-19 were retrospectively included between February and June 2020 and distributed in two groups: T2D or non-diabetic controls. Chest CT with cardiac (CATi), visceral (VATi) and subcutaneous adipose tissue (SATi) volume measurements were performed at admission. The primary endpoint was a composite outcome criteria including death or ICU admission at day 21 after admission. Threshold values of adipose tissue components predicting adverse outcome were determined. RESULTS: One hundred and eight controls [median age: 76(IQR:59-83), 61% male, median BMI: 24(22-27)] and ninety-four T2D patients [median age: 70(IQR:61-77), 70% male, median BMI: 27(24-31)], were enrolled in this study. At day 21 after admission, 42 patients (21%) had died from COVID-19, 48 (24%) required intensive care and 112 (55%) were admitted to a conventional care unit (CMU). In T2D, CATi was associated with early death or ICU independently from age, sex, BMI, dyslipidemia, CRP and coronary calcium (CAC). (p = 0.005). Concerning T2D patients, the cut-point for CATi was > 100 mL/m2 with a sensitivity of 0.83 and a specificity of 0.50 (AUC = 0.67, p = 0.004) and an OR of 4.71 for early ICU admission or mortality (p = 0.002) in the fully adjusted model. Other adipose tissues SATi or VATi were not significantly associated with early adverse outcomes. In control patients, age and male sex (OR = 1.03, p = 0.04) were the only predictors of ICU or death. CONCLUSIONS: Cardiac adipose tissue volume measured in CT at admission was independently predictive of early intensive care or death in T2D patients with COVID-19 but not in non-diabetics. Such automated CT measurement could be used in routine in diabetic patients presenting with moderate to severe COVID-19 illness to optimize individual management and prevent critical evolution.

Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity.

The complex process of manual biomarker extraction from body composition analysis (BCA) has far restricted the analysis of SARS-CoV-2 outcomes to small patient cohorts and a limited number of tissue types. We investigate the association of two BCA-based biomarkers with the development of severe SARS-CoV-2 infections for 918 patients (354 female, 564 male) regarding disease severity and mortality (186 deceased). Multiple tissues, such as muscle, bone, or adipose tissue are used and acquired with a deep-learning-based, fully-automated BCA from computed tomography images of the chest. The BCA features and markers were univariately analyzed with a Shapiro-Wilk and two-sided Mann-Whitney-U test. In a multivariate approach, obtained markers were adjusted by a defined set of laboratory parameters promoted by other studies. Subsequently, the relationship between the markers and two endpoints, namely severity and mortality, was investigated with regard to statistical significance. The univariate approach showed that the muscle volume was significant for female (pseverity ≤ 0.001, pmortality ≤ 0.0001) and male patients (pseverity = 0.018, pmortality ≤ 0.0001) regarding the severity and mortality endpoints. For male patients, the intra- and intermuscular adipose tissue (IMAT) (p ≤ 0.0001), epicardial adipose tissue (EAT) (p ≤ 0.001) and pericardial adipose tissue (PAT) (p ≤ 0.0001) were significant regarding the severity outcome. With the mortality outcome, muscle (p ≤ 0.0001), IMAT (p ≤ 0.001), EAT (p = 0.011) and PAT (p = 0.003) remained significant. For female patients, bone (p ≤ 0.001), IMAT (p = 0.032) and PAT (p = 0.047) were significant in univariate analyses regarding the severity and bone (p = 0.005) regarding the mortality. Furthermore, the defined sarcopenia marker (p ≤ 0.0001, for female and male) was significant for both endpoints. The cardiac marker was significant for severity (pfemale = 0.014, pmale ≤ 0.0001) and for mortality (pfemale ≤ 0.0001, pmale ≤ 0.0001) endpoint for both genders. The multivariate logistic regression showed that the sarcopenia marker was significant (pseverity = 0.006, pmortality = 0.002) for both endpoints (ORseverity = 0.42, 95% CIseverity: 0.23-0.78, ORmortality = 0.34, 95% CImortality: 0.17-0.67). The cardiac marker showed significance (p = 0.018) only for the severity endpoint (OR = 1.42, 95% CI 1.06-1.90). The association between BCA-based sarcopenia and cardiac biomarkers and disease severity and mortality suggests that these biomarkers can contribute to the risk stratification of SARS-CoV-2 patients. Patients with a higher cardiac marker and a lower sarcopenia marker are at risk for a severe course or death. Whether those biomarkers hold similar importance for other pneumonia-related diseases requires further investigation.

Measurement of epicardial adipose tissue using non-contrast routine chest-CT: a consideration of threshold adjustment for fatty attenuation.

BACKGROUND: Epicardial adipose tissue (EAT) is known as an important imaging indicator for cardiovascular risk stratification. The present study aimed to determine whether the EAT volume (EV) and mean EAT attenuation (mEA) measured by non-contrast routine chest CT (RCCT) could be more consistent with those measured by coronary CT angiography (CCTA) by adjusting the threshold of fatty attenuation. METHODS: In total, 83 subjects who simultaneously underwent CCTA and RCCT were enrolled. EV and mEA were quantified by CCTA using a threshold of (N30) (- 190 HU, - 30 HU) as a reference and measured by RCCT using thresholds of N30, N40 (- 190 HU, - 40 HU), and N45 (- 190 HU, - 45 HU). The correlation and agreement of EAT metrics between the two imaging modalities and differences between patients with coronary plaques (plaque ( +)) and without plaques (plaque ( -)) were analyzed. RESULTS: EV obtained from RCCT showed very strong correlation with the reference (r = 0.974, 0.976, 0.972 (N30, N40, N45), P < 0.001), whereas mEA showed a moderate correlation (r = 0.516, 0.500, 0.477 (N30, N40, N45), P < 0.001). Threshold adjustment was able to reduce the bias of EV, while increase the bias of mEA. Data obtained by CCTA and RCCT both demonstrated a significantly larger EV in the plaque ( +) group than in the plaque ( -) group (P < 0.05). A significant difference in mEA was shown only by RCCT using a threshold of N30 (plaque ( +) vs ( -): - 80.0 ± 4.4 HU vs - 78.0 ± 4.0 HU, P = 0.030). The mEA measured on RCCT using threshold of N40 and N45 showed no significant statistical difference between the two groups (P = 0.092 and 0.075), which was consistent with the result obtained on CCTA (P = 0.204). CONCLUSION: Applying more negative threshold, the consistency of EV measurements between the two techniques improves and a consistent result can be obtained when comparing EF measurements between groups, although the bias of mEA increases. Threshold adjustment is necessary when measuring EF with non-contrast RCCT.

Cut-off point of CT-assessed epicardial adipose tissue volume for predicting worse clinical burden of SARS-CoV-2 pneumonia.

OBJECTIVE: To identify a cut-off value of epicardial adipose tissue (EAT) volume quantified by CT associated with a worse clinical outcome in patients with SARS-CoV-2 pneumonia. MATERIALS AND METHODS: In this retrospective study, sixty patients with a diagnosis of laboratory-confirmed COVID-19 pneumonia and a chest CT exam on admission were enrolled. Based on a total severity score (range 0-20), patients were divided into two groups: ordinary group (total severity score < 7) and severe/critical group (total severity score > 7). Clinical results and EAT volume were compared between the two groups. RESULTS: The severe/critical patients, compared to the ordinary ones, were older (66.83 ± 11.72 vs 58.57 ± 16.86 years; p = 0.031), had higher body mass index (27.77 ± 2.11 vs 25.07 ± 2.80 kg/m2; p < 0.001) and higher prevalence of comorbidities. EAT volume was higher in severe/critical group, compared with the ordinary group (151.40 ± 66.22 cm3 vs 92.35 ± 44.46 cm3, p < 0.001). In severe/critical group, 19 (73%) patients were admitted in intensive care unit (ICU), compared with 6 (20%) patients in the ordinary group (p < 0.001). The area under the ROC curve (AUC) is equal to 0.781 (p < 0.001) (95% CI: 0.662-0.900). The cut-off found, in correspondence with the highest value of the Youden Index, is 97 cm3: the sensitivity is equal to 83.3%, while the specificity is equal to 70% for predicting a worse outcome. The risk (odds ratio) of belonging to the severe/critical group in this population due to EAT ≥ 97 cm3 is 11.667 (95% CI: 3.384-40.220; p < 0.001). CONCLUSION: An EAT volume of 97 cm3 has good sensitivity and specificity to predict a greater extent of pulmonary involvement and therefore a worse clinical outcome in patients with SARS-CoV-2 pneumonia.

No Changes in Body Composition in NCAA Division I Collegiate Football Players because of COVID-19 Restrictions.

ABSTRACT: Czeck, MA, Roelofs, EJ, Evanoff, NG, and Dengel, DR. No Changes in body composition in NCAA Division I Collegiate Football Players due to COVID-19 restrictions. J Strength Cond Res 36(6): 1749-1752, 2022-The purpose of this study was to explore the impact of coronavirus disease 2019 (COVID-19) restrictions on body composition, assessed by dual x-ray absorptiometry (DXA), between the 2020 postseason (pre-COVID-19 restrictions) and the 2021 postseason (post-COVID-19 restrictions) in collegiate football players (n = 50). In addition, a subset of athletes (n = 23) was used to explore body composition variables across 4 postseason time points. Body composition variables assessed were total and regional body fat percent, total mass, lean mass, fat mass, bone mineral content, bone mineral density, and visceral adipose tissue mass. Paired t-tests were used to determine differences between the 2020 postseason and the 2021 postseason in body composition variables. Analysis of variance with Tukey HSD post hoc tests assessed significant differences in total and regional body composition across 4 years while adjusting for multiple comparisons. There were no significant differences (p > 0.05) between postseason 2020 and postseason 2021 for all measures of body composition. In a subset of athletes, body composition was analyzed over a 4-year period of time. There were no significant differences between all 4 time points for all measures of body composition. In conclusion, body composition variables in this study's subjects were not affected because of coronavirus disease 2019 restrictions or over 4 years of their collegiate football career.

Association of epicardial adipose tissue with the severity and adverse clinical outcomes of COVID-19: A meta-analysis.

OBJECTIVES: Epicardial adipose tissue (EAT) has been proposed to be an independent predictor of visceral adiposity. EAT measures are associated with coronary artery disease, diabetes, and chronic obstructive pulmonary disease, which are risk factors for COVID-19 poor prognosis. Whether EAT measures are related to COVID-19 severity and prognosis is controversial. METHODS: We searched 6 databases for studies until January 7, 2022. The pooled effects are presented as the standard mean difference (SMD) or weighted mean difference with 95% confidence intervals (CIs). The primary end point was COVID-19 severity. Adverse clinical outcomes were also assessed. RESULTS: A total of 13 studies with 2482 patients with COVID-19 were identified. All patients had positive reverse transcriptase-polymerase chain reaction results. All quantitative EAT measures were based on computed tomography. Patients in the severe group had higher EAT measures compared with the nonsevere group (SMD = 0.74, 95% CI: 0.29-1.18, P = 0.001). Patients with hospitalization requirement, requiring invasive mechanical ventilation, admitted to intensive care unit, or with combined adverse outcomes had higher EAT measures compared to their controls (all P < 0.001). CONCLUSIONS: EAT measures were associated with the severity and adverse clinical outcomes of COVID-19. EAT measures might help in prognostic risk stratification of patients with COVID-19.

Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19.

BACKGROUND: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. METHODS: This monocentric retrospective study included 353 patients: 95 for training, 20 for testing, and 238 for prognosis evaluation. EAT segmentation was obtained after thresholding on a manually segmented pericardial volume. The model was evaluated with Dice coefficient (DSC), inter-and intraobserver reproducibility, and clinical measures. Uni-and multi-variate analyzes were conducted to assess the prognosis value of the EAT volume, EAT extent, and lung lesion extent on clinical outcomes, including hospitalization, oxygen therapy, intensive care unit admission and death. RESULTS: The mean DSC for EAT volumes was 0.85 ± 0.05. For EAT volume, the mean absolute error was 11.7 ± 8.1 cm3 with a non-significant bias of -4.0 ± 13.9 cm3 and a correlation of 0.963 with the manual measures (p < 0.01). The multivariate model providing the higher AUC to predict adverse outcome include both EAT extent and lung lesion extent (AUC = 0.805). CONCLUSIONS: A DL algorithm was developed and evaluated to obtain reproducible and precise EAT segmentation on LDCT. EAT extent in association with lung lesion extent was associated with adverse clinical outcomes with an AUC = 0.805.

Epicardial adipose tissue in contemporary cardiology.

Interest in epicardial adipose tissue (EAT) is growing rapidly, and research in this area appeals to a broad, multidisciplinary audience. EAT is unique in its anatomy and unobstructed proximity to the heart and has a transcriptome and secretome very different from that of other fat depots. EAT has physiological and pathological properties that vary depending on its location. It can be highly protective for the adjacent myocardium through dynamic brown fat-like thermogenic function and harmful via paracrine or vasocrine secretion of pro-inflammatory and profibrotic cytokines. EAT is a modifiable risk factor that can be assessed with traditional and novel imaging techniques. Coronary and left atrial EAT are involved in the pathogenesis of coronary artery disease and atrial fibrillation, respectively, and it also contributes to the development and progression of heart failure. In addition, EAT might have a role in coronavirus disease 2019 (COVID-19)-related cardiac syndrome. EAT is a reliable potential therapeutic target for drugs with cardiovascular benefits such as glucagon-like peptide 1 receptor agonists and sodium-glucose co-transporter 2 inhibitors. This Review provides a comprehensive and up-to-date overview of the role of EAT in cardiovascular disease and highlights the translational nature of EAT research and its applications in contemporary cardiology.

Epicardial adipose tissue thickness is associated with increased COVID-19 severity and mortality.

BACKGROUND: Increased adiposity and visceral obesity have been linked to adverse COVID-19 outcomes. The amount of epicardial adipose tissue (EAT) may have relevant implications given its proximity to the heart and lungs. Here, we explored the role of EAT in increasing the risk for COVID-19 adverse outcomes. METHODS: We included 748 patients with COVID-19 attending a reference center in Mexico City. EAT thickness, sub-thoracic and extra-pericardial fat were measured using thoracic CT scans. We explored the association of each thoracic adipose tissue compartment with COVID-19 mortality and severe COVID-19 (defined as mortality and need for invasive mechanical ventilation), according to the presence or absence of obesity. Mediation analyses evaluated the role of EAT in facilitating the effect of age, body mass index and cardiac troponin levels with COVID-19 outcomes. RESULTS: EAT thickness was associated with increased risk of COVID-19 mortality (HR 1.18, 95% CI 1.01-1.39) independent of age, gender, comorbid conditions and BMI. Increased EAT was associated with lower SpO2 and PaFi index and higher levels of cardiac troponins, D-dimer, fibrinogen, C-reactive protein, and 4 C severity score, independent of obesity. EAT mediated 13.1% (95% CI 3.67-28.0%) and 5.1% (95% CI 0.19-14.0%) of the effect of age and 19.4% (95% CI 4.67-63.0%) and 12.8% (95% CI 0.03-46.0%) of the effect of BMI on requirement for intubation and mortality, respectively. EAT also mediated the effect of increased cardiac troponins on myocardial infarction during COVID-19. CONCLUSION: EAT is an independent risk factor for severe COVID-19 and mortality independent of obesity. EAT partly mediates the effect of age and BMI and increased cardiac troponins on adverse COVID-19 outcomes.

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.

Myocardial injury in COVID-19 patients is associated with the thickness of epicardial adipose tissue.

Aim    High sensitive troponin (hs-TnI) levels may increase secondary to Coronavirus disease-2019 (COVID-19), and this increase is associated with cardiovascular mortality in COVID-19 patients. Epicardial adipose tissue (EAT) is associated with myocardial injury directly as a reservoir tissue for coronavirus, and indirectly through mediators it secretes as an apocrine gland. We aimed to evaluate the relationship between myocardial injury secondary to COVID-19 infection and EAT thickness.Material and methods    Thoracic computed tomography (CT) was performed in 73 consecutive patients diagnosed with COVID-19. EAT thickness and volume were calculated by two radiologists blind to the study data. We formed two groups according to hs-TnI concentrations, patients with myocardial damage (hs-TnI ≥11.6 ng / l) and without myocardial damage (hs-TnI<11.6 ng / dl).Results    A total of 46 patients were women (63.0 %). The mean age was 66.4±12.3 yrs in the myocardial injury group and 55.9±9.7 yrs in the group without myocardial injury (p<0.001). There were 20 hypertensive patients (68.9 %) in the injury group, while there were 12 hypertensive patients (27.3 %) in the group without injury (p=0.001). Glucose, C-reactive protein, D-dimer, white blood cell count, neutrophil, and neutrophil / lymphocyte ratio were higher in the injury group (p<0.05, for all variables). The mean EAT thickness was 5.6±1.6 mm in the injury group, whereas it was 4.8±1.8 mm in the group without injury (p=0.031). EAT thickness of 4.85 mm and above was associated with the myocardial injury with 65 % sensitivity and 39 % specificity (AUC=0.65, 95 % CI: 0.52-078, p=0.031).Conclusion    In patients with COVID-19 infection, higher rates of myocardial injury were observed as the EAT thickness increased. Epicardial adipose tissue, contributes to cytokine-mediated myocardial injury either directly or indirectly by acting as a reservoir for coronavirus. Increased EAT thickness is associated with myocardial injury in COVID-19 patients.

Cardiac adipose tissue volume and IL-6 level at admission are complementary predictors of severity and short-term mortality in COVID-19 diabetic patients.

BACKGROUND: COVID-19 diabetic adults are at increased risk of severe forms irrespective of obesity. In patients with type-II diabetes, fat distribution is characterized by visceral and ectopic adipose tissues expansion, resulting in systemic inflammation, which may play a role in driving the COVID-19 cytokine storm. Our aim was to determine if cardiac adipose tissue, combined to interleukin-6 levels, could predict adverse short-term outcomes, death and ICU requirement, in COVID-19 diabetic patients during the 21 days after admission. METHODS: Eighty one consecutive patients with type-II diabetes admitted for COVID-19 were included. Interleukin-6 measurement and chest computed tomography with total cardiac adipose tissue index (CATi) measurement were performed at admission. The primary outcome was death during the 21 days following admission while intensive care requirement with or without early death (ICU-R) defined the secondary endpoint. Associations of CATi and IL-6 and threshold values to predict the primary and secondary endpoints were determined. RESULTS: Of the enrolled patients (median age 66 years [IQR: 59-74]), 73% male, median body mass index (BMI) 27 kg/m2 [IQR: 24-31]) 20 patients had died from COVID-19, 20 required intensive care and 41 were in conventional care at day 21 after admission. Increased CATi and IL-6 levels were both significantly related to increased early mortality (respectively OR = 6.15, p = 0.002; OR = 18.2, p < 0.0001) and ICU-R (respectively OR = 3.27, p = 0.01; OR = 4.86, p = 0.002). These associations remained significant independently of age, sex, BMI as well as troponin-T level and pulmonary lesion extension in CT. We combined CATi and IL-6 levels as a multiplicative interaction score (CATi*IL-6). The cut-point for this score was ≥ 6386 with a sensitivity of 0.90 and a specificity of 0.87 (AUC = 0.88) and an OR of 59.6 for early mortality (p < 0.0001). CONCLUSIONS: Cardiac adipose tissue index and IL-6 determination at admission could help physicians to better identify diabetic patients with a potentially severe and lethal short term course irrespective of obesity. Diabetic patients with high CATi at admission, a fortiori associated with high IL-6 levels could be a relevant target population to promptly initiate anti-inflammatory therapies.

Epicardial adipose tissue and severe Coronavirus Disease 19.

BACKGROUND: Both visceral adipose tissue and epicardial adipose tissue (EAT) have pro-inflammatory properties. The former is associated with Coronavirus Disease 19 (COVID-19) severity. We aimed to investigate whether an association also exists for EAT. MATERIAL AND METHODS: We retrospectively measured EAT volume using computed tomography (CT) scans (semi-automatic software) of inpatients with COVID-19 and analyzed the correlation between EAT volume and anthropometric characteristics and comorbidities. We then analyzed the clinicobiological and radiological parameters associated with severe COVID-19 (O2 [Formula: see text] 6 l/min), intensive care unit (ICU) admission or death, and 25% or more CT lung involvement, which are three key indicators of COVID-19 severity. RESULTS: We included 100 consecutive patients; 63% were men, mean age was 61.8 ± 16.2 years, 47% were obese, 54% had hypertension, 42% diabetes, and 17.2% a cardiovascular event history. Severe COVID-19 (n = 35, 35%) was associated with EAT volume (132 ± 62 vs 104 ± 40 cm3, p = 0.02), age, ferritinemia, and 25% or more CT lung involvement. ICU admission or death (n = 14, 14%) was associated with EAT volume (153 ± 67 vs 108 ± 45 cm3, p = 0.015), hypertension and 25% or more CT lung involvement. The association between EAT volume and severe COVID-19 remained after adjustment for sex, BMI, ferritinemia and lung involvement, but not after adjustment for age. Instead, the association between EAT volume and ICU admission or death remained after adjustment for all five of these parameters. CONCLUSIONS: Our results suggest that measuring EAT volume on chest CT scans at hospital admission in patients diagnosed with COVID-19 might help to assess the risk of disease aggravation.

Body composition predictors of outcome in patients with COVID-19.

BACKGROUND/OBJECTIVE: Obesity is a strong risk factor for adverse outcomes in patients hospitalized with COVID-19, however, the distribution of fat and the amount of muscle mass are more accurate risk factors than BMI. The objective of this study was to assess body composition measures obtained on opportunistic abdominal CTs as predictors of outcome in patients hospitalized with COVID-19. We hypothesized that elevated visceral and intermuscular adipose tissue would be associated with adverse outcome. SUBJECTS/METHODS: Our retrospective study was IRB-approved and HIPAA-compliant. The study group comprised 124 patients (median age: 68 years, IQR: 56, 77; 59 weeks, 65 months) who were admitted with COVID-19 to a single hospital and who had undergone abdominal CT for clinical purposes. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intermuscular adipose tissue (IMAT), and paraspinal and abdominal muscle cross-sectional areas (CSA) were assessed. Clinical information including prognostic factors, time of admission to the intensive care unit (ICU) and time of death within 28 days were obtained. Multivariate time-to-event competing risk models were fitted to estimate the hazard ratio (HR) for a composite outcome of ICU admission/mortality associated with a one standard deviation increase in each body compositional measure. Each model was adjusted for age, sex, race, BMI, and cardiometabolic comorbidities. RESULTS: There were 50 patients who were admitted to the ICU or deceased over a median time of 1 day [IQR 1, 6] from hospital admission. Higher VAT/SAT ratio (HR of 1.30; 95% CI 1.04-1.62, p = 0.022) and higher IMAT CSA (HR of 1.44; 95% CI 1.10-1.89, p = 0.008) were associated with a reduced time to ICU admission or death in adjusted models. CONCLUSION: VAT/SAT and IMAT are predictors of adverse outcome in patients hospitalized with COVID-19, independent of other established prognostic factors. This suggests that body composition measures may serve as novel biomarkers of outcome in patients with COVID-19.

Incidence of new-onset atrial fibrillation in COVID-19 is associated with increased epicardial adipose tissue.

PURPOSE: Coronary artery calcium (CAC) and epicardial adipose tissue (EAT) can predict AF in the general population. We aimed to determine if CAC and EAT measured by computed tomographic (CT) scanning can predict new-onset AF in patients admitted with COVID-19 disease. METHODS: We performed a retrospective, post hoc analysis of all patients admitted to Montefiore Medical Center with a confirmed COVID-19 diagnosis from March 1st to June 23rd, 2020, who had a non-contrast CT of the chest within 5 years prior to admission. We determined ordinal CAC scores and quantified the EAT volume and examined their relationship with inpatient mortality. RESULTS: A total of 379 patients were analyzed. There were 16 events of new-onset AF (4.22%). Patients who developed AF during the index admission were more likely to be male (75 vs 47%, p < 0.001) and had higher EAT (129.5 [76.3-197.3] vs 91.0 [60.0-129.0] ml, p = 0.049). There were no differences on age (68 [56-71] vs 68 [58-76] years; p = 0.712), BMI (28.5 [25.3-30.8] vs 26.9 [23.1-31.8] kg/m2; p = 0.283), ordinal CAC score (3 [1-6] vs 2 [0-4]; p = 0.482), or prevalence of diabetes (56.3 vs 60.1%; p = 0.761), hypertension (75.0 vs 87.3%, p = 0.153), or coronary artery disease (50.0 vs 39.4%, p = 0.396). Patients with new-onset AF had worse clinical outcomes (death/intubation/vasopressors) (87.5 vs 44.1%; p = 0.001). CONCLUSION: Increased EAT measured by non-contrast chest CT identifies patients hospitalized with COVID-19 at higher risk of developing new-onset AF. Patients with new-onset AF have worse clinical outcomes.

Coronary artery calcification and epicardial adipose tissue as independent predictors of mortality in COVID-19.

Recent epidemiological studies have demonstrated that common cardiovascular risk factors are strongly associated with adverse outcomes in COVID-19. Coronary artery calcium (CAC) and epicardial fat (EAT) have shown to outperform traditional risk factors in predicting cardiovascular events in the general population. We aim to determine if CAC and EAT determined by Computed Tomographic (CT) scanning can predict all-cause mortality in patients admitted with COVID-19 disease. We performed a retrospective, post-hoc analysis of all patients admitted to Montefiore Medical Center with a confirmed COVID-19 diagnosis from March 1st, 2020 to May 2nd, 2020 who had a non-contrast CT of the chest within 5 years prior to admission. We determined ordinal CAC scores and quantified the epicardial (EAT) and thoracic (TAT) fat volume and examined their relationship with inpatient mortality. A total of 493 patients were analyzed. There were 197 deaths (39.95%). Patients who died during the index admission had higher age (72, [64-80] vs 68, [57-76]; p < 0.001), CAC score (3, [0-6] vs 1, [0-4]; p < 0.001) and EAT (107, [70-152] vs 94, [64-129]; p = 0.023). On a competing risk analysis regression model, CAC ≥ 4 and EAT ≥ median (98 ml) were independent predictors of mortality with increased mortality of 63% (p = 0.003) and 43% (p = 0.032), respectively. As a composite, the group with a combination of CAC ≥ 4 and EAT ≥ 98 ml had the highest mortality. CAC and EAT measured from chest CT are strong independent predictors of inpatient mortality from COVID-19 in this high-risk cohort.

Epicardial adipose tissue is associated with extent of pneumonia and adverse outcomes in patients with COVID-19.

AIM: We sought to examine the association of epicardial adipose tissue (EAT) quantified on chest computed tomography (CT) with the extent of pneumonia and adverse outcomes in patients with coronavirus disease 2019 (COVID-19). METHODS: We performed a post-hoc analysis of a prospective international registry comprising 109 consecutive patients (age 64 ±â€¯16 years; 62% male) with laboratory-confirmed COVID-19 and noncontrast chest CT imaging. Using semi-automated software, we quantified the burden (%) of lung abnormalities associated with COVID-19 pneumonia. EAT volume (mL) and attenuation (Hounsfield units) were measured using deep learning software. The primary outcome was clinical deterioration (intensive care unit admission, invasive mechanical ventilation, or vasopressor therapy) or in-hospital death. RESULTS: In multivariable linear regression analysis adjusted for patient comorbidities, the total burden of COVID-19 pneumonia was associated with EAT volume (ß = 10.6, p = 0.005) and EAT attenuation (ß = 5.2, p = 0.004). EAT volume correlated with serum levels of lactate dehydrogenase (r = 0.361, p = 0.001) and C-reactive protein (r = 0.450, p < 0.001). Clinical deterioration or death occurred in 23 (21.1%) patients at a median of 3 days (IQR 1-13 days) following the chest CT. In multivariable logistic regression analysis, EAT volume (OR 5.1 [95% CI 1.8-14.1] per doubling p = 0.011) and EAT attenuation (OR 3.4 [95% CI 1.5-7.5] per 5 Hounsfield unit increase, p = 0.003) were independent predictors of clinical deterioration or death, as was total pneumonia burden (OR 2.5, 95% CI 1.4-4.6, p = 0.002), chronic lung disease (OR 1.3 [95% CI 1.1-1.7], p = 0.011), and history of heart failure (OR 3.5 [95% 1.1-8.2], p = 0.037). CONCLUSIONS: EAT measures quantified from chest CT are independently associated with extent of pneumonia and adverse outcomes in patients with COVID-19, lending support to their use in clinical risk stratification.