TY - JOUR
T1 - Addition of EEG improves accuracy of a logistic model that uses neuropsychological and cardiovascular factors to identify dementia and MCI
AU - Snyder, Steven Michael
AU - Hall, James Richard
AU - Cornwell, Sonya Lynn
AU - Falk, James David
PY - 2011/3/30
Y1 - 2011/3/30
N2 - To investigate whether addition of EEG would improve accuracy of a logistic model that uses neuropsychological assessment and cardiovascular history to identify dementia and mild cognitive impairment (MCI) as a single group, we collected data and constructed logistic models from a sample of 78 normal adults and 33 patients (aged 50-85 years). To determine accuracy, we compared logistic regression results to a geriatrician's diagnosis of MCI or dementia that included Alzheimer's disease, vascular dementia or mixed dementia. We found that the addition of EEG (non-linear complexity) to a logistic model that included both neuropsychological assessment (ADAS-Cog) and cardiovascular history increased overall accuracy from 80% to 92%. The logistic model identified dementia and MCI as a single group comprised of the following subgroups (with accuracies): Alzheimer's disease (92%; 12/13), vascular dementia (73%; 8/11), mixed dementia (100%; 4/4), and mild cognitive impairment (80%; 4/5). Whereas the analysis is limited by small sample sizes and mixing of diverse pathologies, the findings do provide support that the subgroups may share changes in neuropsychological, cardiovascular, and electroencephalographic factors (specifically ADAS-Cog total score, cardiovascular history, and EEG complexity). Taken together, the study results provide support that EEG might complement the clinician's evaluation of dementia and MCI.
AB - To investigate whether addition of EEG would improve accuracy of a logistic model that uses neuropsychological assessment and cardiovascular history to identify dementia and mild cognitive impairment (MCI) as a single group, we collected data and constructed logistic models from a sample of 78 normal adults and 33 patients (aged 50-85 years). To determine accuracy, we compared logistic regression results to a geriatrician's diagnosis of MCI or dementia that included Alzheimer's disease, vascular dementia or mixed dementia. We found that the addition of EEG (non-linear complexity) to a logistic model that included both neuropsychological assessment (ADAS-Cog) and cardiovascular history increased overall accuracy from 80% to 92%. The logistic model identified dementia and MCI as a single group comprised of the following subgroups (with accuracies): Alzheimer's disease (92%; 12/13), vascular dementia (73%; 8/11), mixed dementia (100%; 4/4), and mild cognitive impairment (80%; 4/5). Whereas the analysis is limited by small sample sizes and mixing of diverse pathologies, the findings do provide support that the subgroups may share changes in neuropsychological, cardiovascular, and electroencephalographic factors (specifically ADAS-Cog total score, cardiovascular history, and EEG complexity). Taken together, the study results provide support that EEG might complement the clinician's evaluation of dementia and MCI.
KW - Alzheimer's disease
KW - Electroencephalography
KW - Mild cognitive impairment
KW - Vascular dementia
UR - http://www.scopus.com/inward/record.url?scp=79951853574&partnerID=8YFLogxK
U2 - 10.1016/j.psychres.2010.04.058
DO - 10.1016/j.psychres.2010.04.058
M3 - Article
C2 - 20817309
AN - SCOPUS:79951853574
SN - 0165-1781
VL - 186
SP - 97
EP - 102
JO - Psychiatry Research
JF - Psychiatry Research
IS - 1
ER -