RESUMEN
BACKGROUND: In neuropsychology and neurology, there is no consensus on the definition of abnormal cognition. OBJECTIVE: To operationally define 'abnormal cognition' for optimally predicting progression to dementia in a memory clinic sample, and to test whether multivariate profile analysis of cognitive test results improves this prediction compared to standard clinical evaluation. METHODS: We used longitudinal data from 835 non-demented patients of the Amsterdam Dementia Cohort. For 10 cognitive measures at baseline, we determined which number of abnormal tests and which magnitude of score deviations best predicted progression. RESULTS: Predictive ability for progression to dementia of one, two, and three abnormal test scores out of 10 is highly similar (Cox hazard ratios: 3.7-4.1) provided cut-off values are adapted appropriately. Cut-offs have to be less stringent if the number of abnormal tests required increases: the optimal cut-off is zâ<â-1.45 when one deviating score is required, zâ<â-1.15 when two abnormal tests are required, and zâ<â-0.70 when three abnormal tests are required. The profile analysis has similar predictive ability at the cut-off of pâ<â0.22 (hazard ratio 3.8). A likelihood ratio test showed that this analysis improves prediction of progression to dementia when added to standard clinical evaluation (pâ<â0.001). CONCLUSION: Abnormal cognition may be defined as one, two, or three abnormal test scores out of 10 if the magnitude of score deviations is adapted accordingly. An abnormal score profile predicts decline to dementia equally well, and improves the prediction when used complimentary to standard clinical evaluation.
Asunto(s)
Cognición/fisiología , Disfunción Cognitiva/diagnóstico por imagen , Disfunción Cognitiva/psicología , Progresión de la Enfermedad , Pruebas de Estado Mental y Demencia/normas , Anciano , Disfunción Cognitiva/epidemiología , Demencia/diagnóstico por imagen , Demencia/epidemiología , Demencia/psicología , Femenino , Estudios de Seguimiento , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Análisis Multivariante , Países Bajos/epidemiologíaRESUMEN
OBJECTIVE: Parkinson's disease with mild cognitive impairment (PD-MCI) is a risk factor for progression to PD dementia (PDD) at a later stage of the disease. The consensus criteria of PD-MCI use a traditional test-by-test normative comparison. The aim of this study was to investigate whether a new multivariate statistical method provides a more sensitive tool for predicting dementia status at 3- and 5-year follow-ups. This method allows a formal evaluation of a patient's profile of test scores given a large aggregated database with regression-based norms. METHOD: The cognitive test results of 123 newly diagnosed PD patients from a previously published longitudinal study were analyzed with three different methods. First, the PD-MCI criteria were applied in the traditional way. Second, the PD-MCI criteria were applied using the large aggregated normative database. Last, multivariate normative comparisons (MNCs) were made using the same aggregated normative database. The outcome variable was progression to dementia within 3 and 5 years. RESULTS: The MNC was characterized by higher sensitivity and higher specificity in predicting progression to PDD at follow-up than the two PD-MCI criteria methods, although the difference in classification accuracy did not reach statistical significance. CONCLUSION: We conclude that MNCs could allow for a more accurate prediction of PDD than the traditional PD-MCI criteria, because there are encouraging trends in both increased sensitivity and increased specificity. (JINS, 2019, 25, 678-687).