title: Identification of a metabolic signature for multidimensional impairment and mortality risk in hospitalized older patients.
abstract: A combination of several metabolic and hormonal adaptations has been proposed to control aging. Little is known regarding the effects of multiple deregulations of these metabolic and hormonal systems in modulating frailty and mortality in hospitalized elderly patients. We measured 17 biological serum parameters from different metabolic/hormonal pathways in 594 hospitalized elderly patients followed up to 1 year who were stratified into three groups according to their multidimensional impairment, evaluated by a Comprehensive Geriatric Assessment (CGA)-based Multidimensional Prognostic Index (MPI). The mortality incidence rates were 7% at 1 month and 21% at 1 year. Our data show that frailty and mortality rate were positively associated with chronic inflammation and with a down-regulation of multiple endocrine factors. Of the 17 biomarkers examined, blood levels of IGF-1, triiodothyronine, C-reactive protein, erythrocyte sedimentation rate, white blood cell and lymphocyte counts, iron, albumin, total cholesterol, and LDL-c were significantly associated with both MPI severity grade and mortality. In multivariate Cox proportional hazard model, the following biomarkers most strongly predicted the risk of mortality (adjusted hazard ratio (HR) per 1 quintile increment in predictor distribution): IGF-1 HR = 0.71 (95% CI: 0.63-0.80), CRP HR = 1.48 (95% CI: 1.32-1.65), hemoglobin HR = 0.82 (95% CI: 0.73-0.92), and glucose HR = 1.17 (95% CI: 1.04-1.30). Multidimensional impairment assessed by MPI is associated with a distinctive metabolic 'signature'. The concomitant elevation of markers of inflammation, associated with a simultaneous reduction in multiple metabolic and hormonal factors, predicts mortality in hospitalized elderly patients.
authors.affiliation: Department of Medicine, Salerno University Medical School, Salerno, Italy. lfontana@dom.wustl.edu
authors.forename: Luigi
authors.initials: L
authors.lastname: Fontana
authors.forename: Filomena
authors.initials: F
authors.lastname: Addante
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Copetti
authors.forename: Giulia
authors.initials: G
authors.lastname: Paroni
authors.forename: Andrea
authors.initials: A
authors.lastname: Fontana
authors.forename: Daniele
authors.initials: D
authors.lastname: Sancarlo
authors.forename: Fabio
authors.initials: F
authors.lastname: Pellegrini
authors.forename: Luigi
authors.initials: L
authors.lastname: Ferrucci
authors.forename: Alberto
authors.initials: A
authors.lastname: Pilotto
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D015415:Biomarkers / Q000097:blood*; D001799:Blood Sedimentation; D002097:C-Reactive Protein / Q000378:metabolism; D008078:Cholesterol, LDL / Q000097:blood; D005260:Female; D016330:Frail Elderly; D006728:Hormones / Q000097:blood; D006760:Hospitalization; D006801:Humans; D007249:Inflammation / Q000401:mortality*; D007334:Insulin-Like Growth Factor I / Q000378:metabolism; D007501:Iron / Q000097:blood; D007958:Leukocyte Count; D018655:Lymphocyte Count; D008297:Male; D009026:Mortality; D016016:Proportional Hazards Models; D012709:Serum Albumin / Q000378:metabolism; D014284:Triiodothyronine / Q000097:blood
chemical_list: D015415:Biomarkers; D008078:Cholesterol, LDL; D006728:Hormones; D012709:Serum Albumin; D014284:Triiodothyronine; D007334:Insulin-Like Growth Factor I; D002097:C-Reactive Protein; D007501:Iron