ALTOIDA‐iADL for the diagnosis of Mild Cognitive Impairment and early Alzheimer's disease. (31st December 2021)

• Record Type: Journal Article
• Authors: Tort‐Merino, Adrià; Tarnanas, Ioannis; Bügler, Maximilian; Harms, Robbert; Fernandez‐Villullas, Guadalupe; Juncà‐Parella, Jordi; Bosch, Beatriz; Lladó, Albert; Sanchez‐Valle, Raquel; Balasa, Mircea
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 12
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.057982
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Diagnostic accuracy for the early detection of mild cognitive impairment (MCI) is critical both in the clinical and research settings. Our aim was to evaluate the diagnostic performance of the ALTOIDA‐iADL test in subjects with non‐degenerative MCI and prodromal (pAD) and mild (mAD) Alzheimer's disease. Methods: ALTOIDA‐iADL is a 10‐minute administrable cognitive test, which assesses activities of daily living in the form of an augmented virtual reality game. The task consists of placing and finding virtual objects in a real environment and provides a final score (the NeuroMotor Index; NMI). The NMI is obtained by weighting multi‐modal information such as hands' micromovements, walking bouts and speed, reaction time and navigation trajectory (among others), and represents the overall outcome of the individual task performance. Fifty‐one participants were included and classified according to cerebrospinal fluid (CSF) AD biomarkers: MCI (n = 22; age: 68.2; MMSE: 26.5), pAD (n = 15; age: 69.4; MMSE: 24.0) and mAD (n = 14; age: 70.6; MMSE: 20.7). Results: The NMI allowed differentiating between subjects with absence (Aβ‐) and presence (Aβ+) of abnormalities in the amyloid biomarker (p < 0.01). Also, differences were found between the MCI group and the pAD (p < 0.01) and mAD (p < 0.01) groups (Fig. 1). ROC curves showed good diagnostic accuracy of the NMI in the discrimination between the Aβ‐ and Aβ+ (AUC = 0.777; p < 0.01), MCI and pAD (AUC = 0.781; p < 0.01) and MCI and mAD (AUC = 0.772; p < 0.01). The NMI did not discriminate between the pAD and mAD (AUC = 0.557; p = 0.61) groups (Fig. 2). The NMI correlated with CSF NfL levels (r = ‐.456; p < 0.05) and the MMSE score (r = .432; p < 0.01), showing an association with the degree of cognitive impairment. Conclusions: ALTOIDA‐iADL is useful in the differential diagnosis between patients with non‐degenerative MCI and prodromal and mild Alzheimer's disease. Its performance is related to the degree of impairment in cognitive screening tests and with biomarkers of axonal damage/neurodegeneration.