title: Nursing home admission in elderly subjects with dementia: predictive factors and future challenges.
abstract: OBJECTIVE
  The aim of this study was to identify factors predictive of nursing home admission (NHA) over a period of 1 year among elderly subjects with dementia.
  
  
  METHODS
  The study population was drawn from the SAFES cohort that was formed within a national research program into the recruitment of emergency departments in 9 teaching hospitals. Subjects were to have been hospitalized in a medical ward in the same hospital as the emergency department to which they were initially admitted. Subjects who experienced NHA before emergency department admission were excluded. Those with a confirmed diagnosis of dementia were considered in the present analysis. NHA has been defined as the incident admission into either a nursing home or other long term care facility within the follow-up period. Data obtained from a Comprehensive Geriatric Assessment were used in a Cox model to predict 1-year NHA.
  
  
  RESULTS
  The 425 subjects of the study were 86 ± 6 years old, and were mainly women (63%). NHA rate was 40% (n = 172). Four factors were identified to increase NHA risk: age 85 or older (hazard ratio [HR] = 1.5; 95% confidence interval [CI] = 1.1-2.1), inability to use the toilet (HR = 2.5; 95% CI = 1.5-4.2), balance disorders (HR = 1.5; 95% CI = 1.1-2.1), and living alone (HR = 1.5; 95% CI = 1.1-2.1). Three factors decreased this risk significantly: inability to transfer (HR = 0.5; 95% CI = 0.3-0.8), increased number of children (HR = 0.88; 95% CI = 0.96-0.99), and increased initial Mini-Mental State Examination score (HR = 0.97; 95% CI = 0.8-0.9).
  
  
  CONCLUSIONS
  NHA determinants in dementia are strongly linked to the patient's own characteristics but also to his or her physical or social environment. Interventions should target both members of the dyad "patient-caregiver" because both are affected by the disease.
authors.affiliation: Faculty of Medicine, University of Reims Champagne-Ardenne, EA 3797, Reims, France. mdrame@chu-reims.fr
authors.forename: Moustapha
authors.initials: M
authors.lastname: Dramé
authors.forename: Pierre-Olivier
authors.initials: PO
authors.lastname: Lang
authors.forename: Damien
authors.initials: D
authors.lastname: Jolly
authors.forename: David
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authors.lastname: Narbey
authors.forename: Rachid
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authors.forename: Isabelle
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authors.lastname: Lanièce
authors.forename: Dominique
authors.initials: D
authors.lastname: Somme
authors.forename: Jean-Bernard
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authors.lastname: Gauvain
authors.forename: Damien
authors.initials: D
authors.lastname: Heitz
authors.forename: Thierry
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authors.lastname: Voisin
authors.forename: Benoît
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authors.lastname: de Wazières
authors.forename: Régis
authors.initials: R
authors.lastname: Gonthier
authors.forename: Joël
authors.initials: J
authors.lastname: Ankri
authors.forename: Olivier
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authors.lastname: Saint-Jean
authors.forename: Claude
authors.initials: C
authors.lastname: Jeandel
authors.forename: Pascal
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authors.lastname: Couturier
authors.forename: François
authors.initials: F
authors.lastname: Blanchard
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Novella
mesh_terms: D000369:Aged, 80 and over; D015331:Cohort Studies; D003704:Dementia; D005260:Female; D005544:Forecasting; D005602:France; D006801:Humans; D007407:Interviews as Topic; D008297:Male; D009735:Nursing Homes; D010343:Patient Admission / Q000639:trends*; D016016:Proportional Hazards Models