Utility of the RBANS in detecting cognitive impairment associated with Alzheimer's disease: Sensitivity, specificity, and positive and negative predictive powers

AbstractObjective: The original DWR test, which measured delayed free recall, was reported to have high predictiveaccuracy in discriminating Alzheimer's disease (AD) patients from control subjects (overall accuracy of 95%).Comparison of differential performance in free recall and recognition of the same material may be of clinical interest. In the present study a delayed recognition component was added to the DWR test and the utility of both measures in discriminating AD patients from control subjects was evaluated.Procedure: This extended version of the DWR test was administered to 66 patients meeting NINCDS/ADRDA criteria for probable AD and 42 control subjects.Results: In a comparison between 42 of these patients (MMSE range 18–29), and 42 age matched healthy controls, both the delayed free recall and recognition measures were highly accurate in distinguishing patients from controls. The free recall measure achieved 98% sensitivity, specificity and overall accuracy, while the recognition measure yielded 98% sensitivity, 95% specificity, and 96% overall accuracy. The recognition performance of all 66 patients, ranging in severity from very mild to severe (MMSE range 11–29), was also evaluated to determine its relationship, if any, to measures of global cognitive impairment. While therecognition measure correlated poorly with MMSE and CAMCOG there was a modest but significant correlation with the CAMCOG memory subscale.Conclusions: In this study of highly selected AD patients both the free recall and recognition measures were sensitive and specific indicators of AD compared to control subjects. Recognition performance appears to be more closely related to degree of amnesia than to degree of global cognitive impairment.

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A-02 A Novel Tool for the Differential Diagnosis of Clinical Alzheimer’s Disease, Mild Cognitive Impairment, and Normal Cognition: Development and Validation

Archives of Clinical Neuropsychology ◽

10.1093/arclin/acaa067.02 ◽

2020 ◽

Vol 35 (6) ◽

pp. 775-775

Author(s):

A Parker ◽

L Hynan ◽

C Munro ◽

W Goette ◽

L Lacritz ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Demographic Data ◽

Roc Curves ◽

Weighted Sum ◽

Validation Sample ◽

Sum Scores ◽

Sensitivity Specificity ◽

Normal Cognition

Abstract Objective To create a clinician-friendly diagnostic tool based on neuropsychological and demographic data to assist classification of Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), and normal cognition (NC). Methods Neuropsychological and demographic data from 652 (256 NC,122 MCI,274 AD) subjects were selected from a regional Alzheimer’s Disease Research Center. Utilizing half the sample, two binary logistic regressions compared NC to (MCI + AD) and AD to (NC + MCI) groups. Initial models were reduced in a step-wise manner to determine significant predictors. Raw scores for these variables were multiplied by weights derived from the final regression models and combined to create weighted-sum scores. Cut-points between diagnoses were established using ROC curves based on weighted-sum scores. The tool was validated in the remaining subjects through ROC analyses and sensitivity/specificity calculations for each diagnosis. Results Age, education, sex, Trails A&B, Logical Memory, Animals, and CVLT were all diagnostic predictors. ROC curves comparing weighted sum scores and consensus diagnoses in the validation set showed good discriminability (NC vs MCI + AD: AUC = .95; AD vs NC + MCI: AUC = .98). Scores of 305.75 predicted AD, MCI, and NC respectively, with good sensitivity/specificity in the validation sample (NC = .857/.913, MCI = .711/.883, AD = .914/.951), with 83% of all subjects correctly classified. Conclusions We created a user-friendly diagnostic tool based on demographic and neuropsychological test scores which distinguished between AD, MCI, and NC in an initial validation sample with relatively good accuracy. Results merit replication in other samples, but suggest that this approach may be useful to aid clinical diagnosis, particularly when biomarker data are not available in clinical settings.

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Unfolded p53 as a marker of oxidative stress in Mild Cognitive Impairment, Alzheimer’s and Parkinson’s disease

Current Alzheimer Research ◽

10.2174/1567205018666211117101216 ◽

2021 ◽

Vol 18 ◽

Author(s):

Sara García ◽

Olaya Amor-Gutiérrez ◽

María Palomares-Albarrán ◽

Celia Toyos-Rodríguez ◽

Fernando Cuetos ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Parkinson’S Disease ◽

Alzheimer's Disease ◽

Parkinson's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Plasma Concentration ◽

Electrochemical Immunosensor ◽

Significant Difference ◽

Sensitivity Specificity

Aims: There are several candidate biomarkers for AD and PD which differ in sensitivity, specificity, cost-effectiveness, invasiveness, logistical and technical demands. This study is aimed to test whether plasma concentration of unfolded p53 may help to discriminate among the neurodegenerative processes occurring in Mild Cognitive Impairment, Alzheimer’s disease and Parkinson's disease. Method: An electrochemical immunosensor was used to measure unfolded p53 in plasma samples of 20 Mild Cognitive Impairment (13 males/7 females; mean age 74.95±5.31), 20 Alzheimer’s (11 males/9 females; mean age: 77.25±7.79), 15 Parkinson’s disease patients (12 males/3 females; mean age: 68.60 ± 7.36) and its respective age/sex/studies-matched controls. Result: We observed a significantly higher concentration of unfolded p53 in the plasma of patients of each of the three pathologies with respect to their control groups (p=0.000). Furthermore, the plasma concentration of unfolded p53 was significantly higher in Alzheimer’s disease patients in comparison with Mild Cognitive Impairment patients (p=0.000) and Parkinson’s disease patients (p=0.006). No significant difference between Mild Cognitive Impairment and Parkinson’s disease patients was observed (p=0.524). Conclusion: Our results suggest that unfolded p53 concentration in the plasma may be a useful biomarker for an undergoing neuropathological process that may be common, albeit with a different intensity, to different diseases.

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