BACKGROUND AND PURPOSE: Although it is understood that dementia is a risk factor for adverse outcomes, little is known about the predictive validity of the numerous methods that have been proposed for its diagnosis. Thus, we performed the present study to assess the utility of a variety of diagnostic methods in the prediction of adverse outcomes following stroke. METHODS: We administered neuropsychological, neurological, and functional examinations to 244 patients (age, 71.7+/-8.5 years) 3 months after ischemic stroke. We diagnosed dementia using each of the following methods: (1) neuropsychological testing, requiring deficits in increasing numbers of cognitive domains, both with and without memory impairment, as well as functional impairment; (2) Mini-Mental State Examination (MMSE) score of <24; and (3) neurologists' clinical judgment. We then used survival analyses to investigate the ability of diagnoses based on those methods to predict death and recurrent stroke during long-term follow-up. RESULTS: Log-rank tests and Cox proportional hazards analyses, with recurrent stroke entered as a time dependent covariate, determined that all of the paradigms were significant predictors of mortality, but the performance of paradigms based on neuropsychological testing was superior to the use of the MMSE and clinical judgment, particularly when memory impairment was required. Log-rank tests determined that paradigms based on neuropsychological testing were the only significant predictors of recurrent stroke and performed best when memory impairment was required. CONCLUSIONS: Our results suggest that dementia diagnosis based on neuropsychological assessment and an operationalized paradigm requiring deficits in memory and other cognitive domains is superior to other conventional methods in its ability to identify patients at elevated risk of adverse outcomes following stroke.
BACKGROUND AND PURPOSE: Although it is understood that dementia is a risk factor for adverse outcomes, little is known about the predictive validity of the numerous methods that have been proposed for its diagnosis. Thus, we performed the present study to assess the utility of a variety of diagnostic methods in the prediction of adverse outcomes following stroke. METHODS: We administered neuropsychological, neurological, and functional examinations to 244 patients (age, 71.7+/-8.5 years) 3 months after ischemic stroke. We diagnosed dementia using each of the following methods: (1) neuropsychological testing, requiring deficits in increasing numbers of cognitive domains, both with and without memory impairment, as well as functional impairment; (2) Mini-Mental State Examination (MMSE) score of <24; and (3) neurologists' clinical judgment. We then used survival analyses to investigate the ability of diagnoses based on those methods to predict death and recurrent stroke during long-term follow-up. RESULTS: Log-rank tests and Cox proportional hazards analyses, with recurrent stroke entered as a time dependent covariate, determined that all of the paradigms were significant predictors of mortality, but the performance of paradigms based on neuropsychological testing was superior to the use of the MMSE and clinical judgment, particularly when memory impairment was required. Log-rank tests determined that paradigms based on neuropsychological testing were the only significant predictors of recurrent stroke and performed best when memory impairment was required. CONCLUSIONS: Our results suggest that dementia diagnosis based on neuropsychological assessment and an operationalized paradigm requiring deficits in memory and other cognitive domains is superior to other conventional methods in its ability to identify patients at elevated risk of adverse outcomes following stroke.
Authors: Mark B Snowden; Lesley E Steinman; Lucinda L Bryant; Monique M Cherrier; Kurt J Greenlund; Katherine H Leith; Cari Levy; Rebecca G Logsdon; Catherine Copeland; Mia Vogel; Lynda A Anderson; David C Atkins; Janice F Bell; Annette L Fitzpatrick Journal: Int J Geriatr Psychiatry Date: 2017-02-01 Impact factor: 3.485
Authors: Shadi Yaghi; George Cotsonis; Adam de Havenon; Shyam Prahbakaran; Jose G Romano; Ronald M Lazar; Randolph S Marshall; Edward Feldmann; David S Liebeskind Journal: J Stroke Cerebrovasc Dis Date: 2020-02-07 Impact factor: 2.136