P300 and neuropsychological assessment in mild cognitive impairment and alzheimer dementia

• Autores: Parra, Mario A.; Ascencio, Lindsay Lorena; Urquina, Hugo Fenando; Manes, Facundo Francisco; Ibañez, Agustin Mariano
• Año de publicación: 2012
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: ALZHEIMER'S DISEASE; EARLY DETECTION; EVENT RELATED POTENTIALS; MILD COGNITIVE IMPAIRMENT; NEUROPSYCHOLOGY; P300; PRECLINICAL MARKERS
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Only a small proportion of individuals with Mild Cognitive Impairment (MCI) will convert to dementia. Methods currently available to identify risk for conversion do not combine enough sensitivity and specificity, which is even more problematic in low-educated populations. Current guidelines suggest the use of combined markers for dementia to enhance the prediction accuracy of assessment methods. The present study adhered to this proposal and investigated the sensitivity and specificity of the electrophysiological component P300 and standard neuropsychological tests to assess patients with Alzheimer?s disease (AD) and MCI recruited from a low-income country. The neuropsychological battery comprised tests of memory, attention, language, praxis and executive functions. The P300 was recorded using a classical visual odd-ball paradigm. Three variables were found to achieve sensitivity and specificity values above 80% (Immediate and Delayed recall of word list ? CERAD ? and the latency of P300) for both MCI and AD. When they entered the model together (i.e., combined approach) the sensitivity for MCI increased to 96% and the specificity remained high (80%). Our preliminary findings suggest that the combined use of sensitive neuropsychological tasks and the analysis of the P300 may offer a very useful method for the preclinical assessment of AD, particularly in populations with low socioeconomic and educational levels. Our results provide a platform and justification to employ more resources to convert P300 and related parameters into a biological marker for AD.
Fil: Parra, Mario A.. University of Edinburgh; Reino Unido
Fil: Ascencio, Lindsay Lorena. Surcolombiana University; Colombia
Fil: Urquina, Hugo Fenando. Universidad Favaloro; Argentina. Surcolombiana University; Colombia
Fil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Favaloro; Argentina
Fil: Ibañez, Agustin Mariano. Universidad Favaloro; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina