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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Accuracy of Two Cognitive Screening Tools to Detect Mild Cognitive Impairment in Parkinson's Disease
Emmie W Koevoets1,2, Ben Schmand1,2, Gert J Geurtsen1
1Department of Medical Psychology Academic Medical Center Amsterdam The Netherlands.
Background:
Patients with Parkinson's disease (PD) who have mild cognitive impairment (PD-MCI) are at increased risk of developing PD dementia (PDD). Therefore, it is important to identify PD-MCI in a reliable way.
Objectives:
We evaluated the accuracy of the Parkinson's Disease-Cognitive Rating Scale (PD-CRS) and the Mattis Dementia Rating Scale-2 (MDRS-2) for detecting PD-MCI. Data from healthy subjects were used to correct for demographic influences.
Methods:
We compared the accuracy of the two instruments using ROC analysis. The gold standard was level II diagnosis of PD-MCI according to consensus criteria of the International Parkinson and Movement Disorder Society.
Results:
Seventy-five healthy subjects and 125 PD patients were included. Education level, age and sex correlated with the PD-CRS, but only age correlated with the MDRS-2. Twenty-seven percent of the patients had PD-MCI. Areas under the curve (AUCs) for raw scores of PD-CRS and MDRS-2 were 0.83 and 0.81, respectively. At the optimal cut-off for the PD-CRS (101/102), sensitivity was 88% and specificity was 64%. For the MDRS-2 (139/140) sensitivity and specificity were 68% and 79%, respectively.AUCs for demographically corrected scores of PD-CRS and for age-corrected scores of MDRS-2 were 0.80 and 0.78, respectively. At the optimal cut-off for the PD-CRS, sensitivity was 79% and specificity was 72%, while for the MDRS-2 these were 77% and 67%, respectively.
Conclusions:
Both cognitive screening tools are suitable for distinguishing PD-MCI patients from cognitively intact PD patients. Demographical correction of scores did not improve sensitivity and specificity.
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