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Pre-clinical cognitive phenotypes for Alzheimer disease: a latent profile approach.
Hayden, Kathleen M; Kuchibhatla, Maragatha; Romero, Heather R; Plassman, Brenda L; Burke, James R; Browndyke, Jeffrey N; Welsh-Bohmer, Kathleen A.
Afiliación
  • Hayden KM; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC. Electronic address: khayden@duke.edu.
  • Kuchibhatla M; Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC.
  • Romero HR; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
  • Plassman BL; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
  • Burke JR; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
  • Browndyke JN; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
  • Welsh-Bohmer KA; Joseph and Kathleen Bryan ADRC, Duke University Medical Center, Durham, NC.
Am J Geriatr Psychiatry ; 22(11): 1364-74, 2014 Nov.
Article en En | MEDLINE | ID: mdl-24080384
BACKGROUND: Cognitive profiles for pre-clinical Alzheimer disease (AD) can be used to identify groups of individuals at risk for disease and better characterize pre-clinical disease. Profiles or patterns of performance as pre-clinical phenotypes may be more useful than individual test scores or measures of global decline. OBJECTIVE: To evaluate patterns of cognitive performance in cognitively normal individuals to derive latent profiles associated with later onset of disease using a combination of factor analysis and latent profile analysis. METHODS: The National Alzheimer Coordinating Centers collect data, including a battery of neuropsychological tests, from participants at 29 National Institute on Aging-funded Alzheimer Disease Centers across the United States. Prior factor analyses of this battery demonstrated a four-factor structure comprising memory, attention, language, and executive function. Factor scores from these analyses were used in a latent profile approach to characterize cognition among a group of cognitively normal participants (N = 3,911). Associations between latent profiles and disease outcomes an average of 3 years later were evaluated with multinomial regression models. Similar analyses were used to determine predictors of profile membership. RESULTS: Four groups were identified; each with distinct characteristics and significantly associated with later disease outcomes. Two groups were significantly associated with development of cognitive impairment. In post hoc analyses, both the Trail Making Test Part B, and a contrast score (Delayed Recall - Trails B), significantly predicted group membership and later cognitive impairment. CONCLUSIONS: Latent profile analysis is a useful method to evaluate patterns of cognition in large samples for the identification of preclinical AD phenotypes; comparable results, however, can be achieved with very sensitive tests and contrast scores.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Cognición / Enfermedad de Alzheimer Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Am J Geriatr Psychiatry Asunto de la revista: GERIATRIA / PSIQUIATRIA Año: 2014 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Cognición / Enfermedad de Alzheimer Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Am J Geriatr Psychiatry Asunto de la revista: GERIATRIA / PSIQUIATRIA Año: 2014 Tipo del documento: Article