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COVID-19 may have a heterogeneous onset, especially in older age. However, whether and how COVID-19 signs and symptoms may present and aggregate together according to sociodemographic and health factors is unclear, as well as their prognostic value. This study included 981 COVID-19 inpatients who participated in the GeroCovid Observational study. Signs/symptoms at disease onset, sociodemographic, health, cognitive status, and mobility were systematically recorded. Clusters of signs/symptoms were identified through agglomerative hierarchical clustering. The associations of single signs/symptoms and symptom clusters with longer hospitalization (≥16 days) and in-hospital mortality were explored through logistic and Cox regressions. The signs/symptoms most reported in our sample (age 78.3 ± 9.39 years; 49.4% women) were fever (62.5%), cough (45.5%), and dyspnea (62.7%). Atypical symptoms were reported by up to one-third of patients, and delirium by 9.1%. Atypical symptoms were more frequent with advancing age and with lower pre-COVID-19 cognitive and mobility levels. Older men more likely reported respiratory symptoms than women. Dyspnea (hazard ratio [HR] = 1.47, 95% confidence interval [CI]: 1.02-2.12), tachypnea (HR = 1.53, 95% CI: 1.14-2.07), low oxygen saturation (HR = 1.95, 95% CI: 1.32-2.88) and delirium (HR = 1.60, 95% CI: 1.13-2.28) were associated with higher in-hospital mortality. Four symptom clusters were identified. Compared with the mild respiratory symptoms cluster, the severe clinical impairment cluster was associated with higher mortality (HR = 2.57, 95% CI: 1.58-4.18). The severe clinical impairment and aspecific symptoms clusters were associated with longer hospitalization (odds ratio [OR] = 2.38, 95% CI: 1.56-3.63, and OR = 1.75, 95% CI: 1.08-2.83, respectively). Multiple health aspects influence COVID-19 clinical presentation. A symptom clusters approach may help predict adverse health outcomes in older patients. In addition to respiratory symptoms

BACKGROUND: Although the prevalence of sarcopenic obesity is increasing, nowadays a universally accepted definition still does not exist. Because, this clinical entity is defined as the combination of obesity and sarcopenia, the diagnosis appears to be strictly linked to criteria used for sarcopenia and the available prevalence data are not uniform. To investigate the prevalence of sarcopenic obesity in older persons according to EWGSOP2 and FNIH criteria. Second, to evaluate the prevalence of diabetes in patients with sarcopenia diagnosed by the two definitions. METHODS: Observational multicenter study performed in 2014 on older patients admitted to 12 Italian hospitals (GLISTEN Study). Data were collected through standardized questionnaires, which assessed: socio-demographic data, cognitive status, functional abilities, pharmacological therapy, comorbidities, and blood tests. Moreover, muscle mass and strength and physical performance were evaluated. RESULTS: Six hundred and ten were included in the analyses. Among sarcopenic patients, the prevalence of sarcopenic obesity was 30.8% with FNIH and 0% with EWGSOP2 criteria. According to EWGSOP2 criteria, 23.7% of sarcopenic and 30.8% of non-sarcopenic patients were affected by diabetes (p = 0.101); otherwise, using FNIH criteria, 36.3% of sarcopenic and 26.9% of non-sarcopenic patients were diabetic (p = 0.030). After adjustment for potential confounders, diabetic patients had a 73% higher probability of being sarcopenic according to FNIH criteria (OR 1.73; 95% CI 1.13-2.64). CONCLUSIONS: The EWGSOP2 and FNIH sarcopenia criteria are differently related to the prevalence of obesity and diabetes. The EWGSOP2 criteria seem to be not suitable to identify people with sarcopenic obesity.