BACKGROUND/AIMS: Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and identify individuals at risk for developing Alzheimer's disease (AD). While evidence suggests that subjects with AD perform worse on category fluency than letter fluency tasks, the pattern in mild cognitive impairment (MCI) is less well known. METHODS: Performance on the Controlled Oral Word Association Test (COWAT) and Animal fluency was compared in control, amnestic MCI, non-amnestic MCI, and AD groups. The sample included 136 participants matched for age, education, and gender. RESULTS: Both MCI groups performed similarly with a category > letter fluency pattern rather than a category < letter fluency pattern typically observed in AD. The pattern in MCI, albeit relatively more impaired than in controls, was more similar to healthy controls who exhibited a category > letter fluency pattern. CONCLUSION: MCI using a category < letter fluency pattern may not represent AD; however, future research requires longitudinal studies of pattern analysis.
BACKGROUND/AIMS: Verbal fluency patterns can assist in differential diagnosis during neuropsychological assessment and identify individuals at risk for developing Alzheimer's disease (AD). While evidence suggests that subjects with AD perform worse on category fluency than letter fluency tasks, the pattern in mild cognitive impairment (MCI) is less well known. METHODS: Performance on the Controlled Oral Word Association Test (COWAT) and Animal fluency was compared in control, amnestic MCI, non-amnestic MCI, and AD groups. The sample included 136 participants matched for age, education, and gender. RESULTS: Both MCI groups performed similarly with a category > letter fluency pattern rather than a category < letter fluency pattern typically observed in AD. The pattern in MCI, albeit relatively more impaired than in controls, was more similar to healthy controls who exhibited a category > letter fluency pattern. CONCLUSION: MCI using a category < letter fluency pattern may not represent AD; however, future research requires longitudinal studies of pattern analysis.
Authors: Kimberly Diggle Mueller; Rebecca L Koscik; Asenath LaRue; Lindsay R Clark; Bruce Hermann; Sterling C Johnson; Mark A Sager Journal: Arch Clin Neuropsychol Date: 2015-05-29 Impact factor: 2.813
Authors: David R Roalf; Tyler M Moore; David A Wolk; Steven E Arnold; Dawn Mechanic-Hamilton; Jacqueline Rick; Sushila Kabadi; Kosha Ruparel; Alice S Chen-Plotkin; Lama M Chahine; Nabila A Dahodwala; John E Duda; Daniel A Weintraub; Paul J Moberg Journal: J Neurol Neurosurg Psychiatry Date: 2016-04-12 Impact factor: 10.154
Authors: Alar Kaskikallio; Mira Karrasch; Juha Koikkalainen; Jyrki Lötjönen; Juha O Rinne; Terhi Tuokkola; Riitta Parkkola; Petra Grönholm-Nyman Journal: Front Aging Neurosci Date: 2021-05-06 Impact factor: 5.750
Authors: Marzieh Araghi; Martin J Shipley; Ian B Wilkinson; Carmel M McEniery; Carlos A Valencia-Hernández; Mika Kivimaki; Séverine Sabia; Archana Singh-Manoux; Eric J Brunner Journal: Eur J Epidemiol Date: 2019-11-27 Impact factor: 8.082
Authors: Michael K Yeung; Sophia L Sze; Jean Woo; Timothy Kwok; David H K Shum; Ruby Yu; Agnes S Chan Journal: Front Aging Neurosci Date: 2016-03-29 Impact factor: 5.750
Authors: Marta Bisbe; Andrea Fuente-Vidal; Elisabet López; Marta Moreno; Marian Naya; Claudio de Benetti; Raimon Milà; Olga Bruna; Mercè Boada; Montserrat Alegret Journal: J Alzheimers Dis Date: 2020 Impact factor: 4.472