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.

Sex disparities in COVID-19 outcomes of inpatients with diabetes: insights from the CORONADO study.

OBJECTIVE: Male sex is one of the determinants of severe coronavirus diseas-e-2019 (COVID-19). We aimed to characterize sex differences in severe outcomes in adults with diabetes hospitalized for COVID-19. METHODS: We performed a sex-stratified analysis of clinical and biological features and outcomes (i.e. invasive mechanical ventilation (IMV), death, intensive care unit (ICU) admission and home discharge at day 7 (D7) or day 28 (D28)) in 2380 patients with diabetes hospitalized for COVID-19 and included in the nationwide CORONADO observational study (NCT04324736). RESULTS: The study population was predominantly male (63.5%). After multiple adjustments, female sex was negatively associated with the primary outcome (IMV and/or death, OR: 0.66 (0.49-0.88)), death (OR: 0.49 (0.30-0.79)) and ICU admission (OR: 0.57 (0.43-0.77)) at D7 but only with ICU admission (OR: 0.58 (0.43-0.77)) at D28. Older age and a history of microvascular complications were predictors of death at D28 in both sexes, while chronic obstructive pulmonary disease (COPD) was predictive of death in women only. At admission, C-reactive protein (CRP), aspartate amino transferase (AST) and estimated glomerular filtration rate (eGFR), according to the CKD-EPI formula predicted death in both sexes. Lymphocytopenia was an independent predictor of death in women only, while thrombocytopenia and elevated plasma glucose concentration were predictors of death in men only. CONCLUSIONS: In patients with diabetes admitted for COVID-19, female sex was associated with lower incidence of early severe outcomes, but did not influence the overall in-hospital mortality, suggesting that diabetes mitigates the female protection from COVID-19 severity. Sex-associated biological determinants may be useful to optimize COVID-19 prevention and management in women and men.

COVID-19 and Obesity: Role of Ectopic Visceral and Epicardial Adipose Tissues in Myocardial Injury.

In March 2020, the WHO declared coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a global pandemic. Obesity was soon identified as a risk factor for poor prognosis, with an increased risk of intensive care admissions and mechanical ventilation, but also of adverse cardiovascular events. Obesity is associated with adipose tissue, chronic low-grade inflammation, and immune dysregulation with hypertrophy and hyperplasia of adipocytes and overexpression of pro-inflammatory cytokines. However, to implement appropriate therapeutic strategies, exact mechanisms must be clarified. The role of white visceral adipose tissue, increased in individuals with obesity, seems important, as a viral reservoir for SARS-CoV-2 via angiotensin-converting enzyme 2 (ACE2) receptors. After infection of host cells, the activation of pro-inflammatory cytokines creates a setting conducive to the "cytokine storm" and macrophage activation syndrome associated with progression to acute respiratory distress syndrome. In obesity, systemic viral spread, entry, and prolonged viral shedding in already inflamed adipose tissue may spur immune responses and subsequent amplification of a cytokine cascade, causing worse outcomes. More precisely, visceral adipose tissue, more than subcutaneous fat, could predict intensive care admission; and lower density of epicardial adipose tissue (EAT) could be associated with worse outcome. EAT, an ectopic adipose tissue that surrounds the myocardium, could fuel COVID-19-induced cardiac injury and myocarditis, and extensive pneumopathy, by strong expression of inflammatory mediators that could diffuse paracrinally through the vascular wall. The purpose of this review is to ascertain what mechanisms may be involved in unfavorable prognosis among COVID-19 patients with obesity, especially cardiovascular events, emphasizing the harmful role of excess ectopic adipose tissue, particularly EAT.

Phenotypic Characteristics and Development of a Hospitalization Prediction Risk Score for Outpatients with Diabetes and COVID-19: The DIABCOVID Study.

Diabetes mellitus (DM) has been identified as a risk factor for severe COVID-19. DM is highly prevalent in the general population. Defining strategies to reduce the health care system burden and the late arrival of some patients thus seems crucial. The study aim was to compare phenotypic characteristics between in and outpatients with diabetes and infected by COVID-19, and to build an easy-to-use hospitalization prediction risk score. This was a retrospective observational study. Patients with DM and laboratory- or CT-confirmed COVID-19, who did (n = 185) and did not (n = 159) require hospitalization between 10 March and 10 April 2020, were compared. Data on diabetes duration, treatments, glycemic control, complications, anthropometrics and peripheral oxygen saturation (SpO2) were collected from medical records. Stepwise multivariate logistic regressions and ROC analyses were performed to build the DIAB score, a score using no more than five easy-to-collect clinical parameters predicting the risk of hospitalization. The DIAB score was then validated in two external cohorts (n = 132 and n = 2036). Hospitalized patients were older (68.0 ± 12.6 vs. 55.2 ± 12.6 years, p < 0.001), with more class III obesity (BMI ≥ 40 kg/m2, 9.7 vs. 3.5%, p = 0.03), hypertension (81.6 vs. 44.3%, p < 0.0001), insulin therapy (37% vs. 23.7%, p = 0.009), and lower SpO2 (91.6 vs. 97.3%, p < 0.0001) than outpatients. Type 2 DM (T2D) was found in 94% of all patients, with 10 times more type 1 DM in the outpatient group (11.3 vs. 1.1%, p < 0.0001). A DIAB score > 27 points predicted hospitalization (sensitivity 77.7%, specificity 89.2%, AUC = 0.895), and death within 28 days. Its performance was validated in the two external cohorts. Outpatients with diabetes were found to be younger, with fewer diabetic complications and less severe obesity than inpatients. DIAB score is an easy-to-use score integrating five variables to help clinicians better manage patients with DM and avert the saturation of emergency care units.