title: White matter changes and diabetes predict cognitive decline in the elderly: the LADIS study.
abstract: OBJECTIVE
  We aimed to study if age-related white matter changes (WMC) and vascular risk factors were predictors of cognitive decline in elderly subjects with WMC living independently.
  
  
  METHODS
  The Leukoaraiosis and Disability prospective multinational European study (LADIS) evaluates the impact of WMC on the transition of independent elderly subjects into disability. Independent elderly were enrolled due to the presence of WMC. Subjects were evaluated yearly during 3 years with a comprehensive clinical protocol and a neuropsychological battery. Additionally, dementia, subtypes of dementia, and cognitive decline without dementia were classified according to usual clinical criteria. MRI was performed at entry and at the end of the study.
  
  
  RESULTS
  A total of 639 subjects were included (74.1 +/- 5 years, 55% women, 9.6 +/- 3.8 years of schooling). At end of follow-up, 90 patients had dementia and 147 had cognitive impairment no dementia. Using Cox regression analysis, WMC severity independently predicted cognitive decline (dementia and not dementia), independently of age, education, and medial temporal atrophy (MTA). Diabetes at baseline was the only vascular risk factor that independently predicted cognitive decline during follow-up, controlling for age, education, WMC severity, and temporal atrophy. Considering subtypes of dementia, Alzheimer disease (AD) was predicted only by MTA, while vascular dementia was predicted by previous stroke, WMC severity, and MTA.
  
  
  CONCLUSIONS
  WMC severity and diabetes are independent predictors of cognitive decline in an initially nondisabled elderly population. Vascular dementia is predicted by previous stroke and WMC, while AD is predicted only by MTA.
authors.affiliation: Neurosciences Department, Lisbon University, Santa Maria Hospital, Lisbon, Portugal. averdelho@fm.ul.pt
authors.forename: A
authors.initials: A
authors.lastname: Verdelho
authors.forename: S
authors.initials: S
authors.lastname: Madureira
authors.forename: C
authors.initials: C
authors.lastname: Moleiro
authors.forename: J M
authors.initials: JM
authors.lastname: Ferro
authors.forename: C O
authors.initials: CO
authors.lastname: Santos
authors.forename: T
authors.initials: T
authors.lastname: Erkinjuntti
authors.forename: L
authors.initials: L
authors.lastname: Pantoni
authors.forename: F
authors.initials: F
authors.lastname: Fazekas
authors.forename: M
authors.initials: M
authors.lastname: Visser
authors.forename: G
authors.initials: G
authors.lastname: Waldemar
authors.forename: A
authors.initials: A
authors.lastname: Wallin
authors.forename: M
authors.initials: M
authors.lastname: Hennerici
authors.forename: D
authors.initials: D
authors.lastname: Inzitari
mesh_terms: D000203:Activities of Daily Living; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology; D001284:Atrophy / Q000473:pathology; D001921:Brain / Q000473:pathology*; D003072:Cognition Disorders / Q000150:complications / Q000175:diagnosis / Q000473:pathology*; D003924:Diabetes Mellitus, Type 2 / Q000150:complications / Q000473:pathology*; D004185:Disability Evaluation; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D009483:Neuropsychological Tests; D018579:Patient Selection; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012307:Risk Factors; D012720:Severity of Illness Index