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    Schlagworte: Background: Because frailty is a complex phenomenon associated with poor outcomes; the identification of patient profiles with different care needs might be of greater practical help than to look for a unifying definition. This study aimed at identifying aging phenotypes and their related outcomes in order to recognize frailty in hospitalized older patients. Methods: Patients aged 65 or older enrolled in internal medicine and geriatric wards participating in the REPOSI registry. Relationships among variables associated to sociodemographic; physical; cognitive; functional; and medical status were explored using a multiple correspondence analysis. The hierarchical cluster analysis was then performed to identify possible patient profiles. Multivariable logistic regression was used to verify the association between clusters and outcomes (in-hospital mortality and 3-month postdischarge mortality and rehospitalization). Results: 2,841 patients were included in the statistical analyses. Four clusters were identified: the healthiest (I); those with multimorbidity (II); the functionally independent women with osteoporosis and arthritis (III); and the functionally dependent oldest old patients with cognitive impairment (IV). There was a significantly higher in-hospital mortality in Cluster II (odds ratio [OR] = 2.27; 95% confidence interval [CI] = 1.15-4.46) and Cluster IV (OR = 5.15; 95% CI = 2.58-10.26) and a higher 3-month mortality in Cluster II (OR = 1.66; 95% CI = 1.13-2.44) and Cluster IV (OR = 1.86; 95% CI = 1.15-3.00) than in Cluster I. Conclusions: Using alternative analytical techniques among hospitalized older patients; we could distinguish different frailty phenotypes; differently associated with adverse events. The identification of different patient profiles can help defining the best care strategy according to specific patient needs.

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