The Addenbrooke’s Cognitive Examination–Revised (ACE‐R) in the diagnosis of Alzheimer’s disease: A new logarithm using Mokken scaling analysis

Abstract

AbstractBackgroundThe ACE‐R is an accurate and brief cognitive battery for the detection of mild dementia, especially for the discrimination between Alzheimer’s disease (AD) and frontotemporal dementia. The aim of this study was to develop a new logarithm based on discriminative items of the ACE‐R combined with relevant demographic characteristics that may interfere on cognition.MethodThe ACE‐R was administered to 102 patients with mild dementia due to probable AD and 161 controls from two Brazilian research centers. All individuals were submitted to the Mattis Dementia Rating Scale (DRS) and the ACE‐R. The performance of the patients was compared and analyzed. Mokken scaling analysis was applied to identify the latent trait on the AD Group. Multivariate logistic regression and ROC curve analysis were carried out.ResultMean ± SD total scores in the ACE‐R were 70.2 ± 10.8 in AD and 85.1 ± 8.2 in controls. AD Mokken ACE‐R (AMokACE‐R) comprises 12 items measuring the same latent concept. Logistic regression with cross‐validation pointed that AMokACE‐R + Years of education + ACE‐R items Orientation (time) and Memory (name and address recall) share importance as independent variables (p<0.05). The proposed logarithm reached an area under the curve of 0.968, with 93% sensitivity, 94% specificity, 90% PPV and 95% NPV.ConclusionThe new logarithm using the ACE‐R items achieved high diagnostic accuracy in identifying mild AD versus controls. Furthermore, the final ROC curves showed the superiority of the model proposed in relation to the analysis of the subscales individually, as the literature previously reported. Further analysis in larger samples, with biomarkers or pathological confirmation, are necessary to confirm these findings.