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Dementia is becoming a major health problem as the population of the Northern Hemisphere ages. Early differential diagnosis between normal cognitive decline and dementia is particularly difficult. If psychometric evaluation can contribute to the diagnosis, quantitative cerebral functional imaging would play an important role. We therefore proposed, first, to constitute a normative dataset that could later be used to identify subjects at risk for neurodegenerative processes and, second, to describe the risk of abnormal global cerebral blood flow (gCBF) by defining categories based on the standardized cutoff scores of a young, healthy population (T-score). METHODS: Of a total of 203 healthy volunteers, 187 were included in the protocol, which included evaluation of medical history, neurologic and neuropsychologic status, and body composition; analysis of blood; and measurement of gCBF by means of (133)Xe SPECT. RESULTS: With ANOVA analysis using age and sex as between-subject factors and gCBF as a within-subject factor, a significantly higher gCBF was found in women than in men. In addition, a linear reduction as a function of age was observed for both sexes (-0.3%/y). T-score was determined for the 18- to 28-y-old age group, for whom gCBF was found to be 46.7 +/- 5.1 mL/min/100 g tissue in men and 49.0 +/- 5.0 mL/min/100 g tissue in women. The age-dependent decrease could thus be expressed in T-scores and, in the 29- to 38-y-old, 39- to 48-y-old, and >48-y-old age groups, averaged -0.63, -1.29, and -1.92, respectively, in men and -0.63, -0.83, and-2.40, respectively, in women. Cognitive performance, body composition, and blood analysis revealed the expected significant effects from sex and age. CONCLUSION: The large-scale reference database of gCBF measurements constituted from a healthy, well-controlled population enabled age and sex stratification, which showed significant differences between the sexes and a significant decline as a function of age. T-scores were determined and warrant further studies on the prospective identification of early dementia by (133)Xe SPECT in elderly individuals.

The COVID-19 pandemics has created unprecedented challenges and threats to patients and healthcare systems worldwide. Acute respiratory complications that require intensive care unit (ICU) management are a major cause of morbidity and mortality in COVID-19 patients. Among other important risk factors for severe COVID-19 outcomes, obesity has emerged along with undernutrition-malnutrition as a strong predictor of disease risk and severity. Obesity-related excessive body fat may lead to respiratory, metabolic and immune derangements potentially favoring the onset of COVID-19 complications. In addition, patients with obesity may be at risk for loss of skeletal muscle mass, reflecting a state of hidden malnutrition with a strong negative health impact in all clinical settings. Also importantly, obesity is commonly associated with micronutrient deficiencies that directly influence immune function and infection risk. Finally, the pandemic-rvelated lockdown, deleterious lifestyle changes and other numerous psychosocial consequences may worsen eating behaviors, sedentarity, body weight regulation, ultimately leading to further increments of obesity-associated metabolic complications with loss of skeletal muscle mass and higher non-communicable disease risk. Therefore, prevention, diagnosis and treatment of malnutrition and micronutrient deficiencies should be routinely included in the management of COVID-19 patients in the presence of obesity; lockdown-induced health risks should also be specifically monitored and prevented in this population. In the current document, the European Society for Clinical Nutrition and Metabolism (ESPEN) aims at providing clinical practice guidance for nutritional management of COVID-19 patients with obesity in various clinical settings.