BACKGROUND: Memory tests using controlled encoding and cued recall paradigm (CECR) have been shown to identify prodromal Alzheimer's disease (AD), but information about the effectiveness of CECR compared to other memory tests in predicting clinical progression is missing. OBJECTIVE: The aim was to examine the predictive ability of a memory test based on the CECR paradigm in comparison to other memory/non-memory tests for conversion to dementia in patients with amnestic mild cognitive impairment (aMCI). METHODS: 270 aMCI patients from the clinical-based Czech Brain Aging Study underwent a comprehensive neuropsychological assessment including the Enhanced Cued Recall test (ECR), a memory test with CECR, two verbal memory tests without controlled encoding: the Auditory Verbal Learning Test (AVLT) and Logical memory test (LM), a visuospatial memory test: the Rey-Osterrieth Complex Figure test, and cognitive testing based on the Uniform Data Set battery. The patients were followed prospectively. Conversion to dementia as a function of cognitive performance was examined using Cox proportional hazard models. RESULTS: 144 (53%) patients converted to dementia. Most converters (89%) developed dementia due to AD or mixed (AD and vascular) dementia. Comparing the four memory tests, the delayed recall scores on AVLT and LM best predicted conversion to dementia. Adjusted hazard ratios (HR) of immediate recall scores on ECR, AVLT, and LM were similar to the HR of categorical verbal fluency. CONCLUSION: Using the CECR memory paradigm in assessment of aMCI patients has no superiority over verbal and non-verbal memory tests without cued recall in predicting conversion to dementia.

• Klíčová slova
• Alzheimer’s disease, memory, mild cognitive impairment, verbal fluency,
• MeSH
• Alzheimerova nemoc * diagnóza   MeSH
• kognitivní dysfunkce * psychologie   MeSH
• krátkodobá paměť MeSH
• lidé MeSH
• neuropsychologické testy MeSH
• progrese nemoci MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH