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Article type: Research Article
Authors: Ilardi, Ciro Rosarioa; * | Menichelli, Alinab | Michelutti, Marcoc | Cattaruzza, Tatianac | Federico, Giovannia | Salvatore, Marcoa | Iavarone, Alessandrod | Manganotti, Paoloc
Affiliations: [a] IRCCS SYNLAB SDN, Naples, Italy | [b] Department of Medicine, Surgery and Health Sciences, Rehabilitation Unit, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy | [c] Department of Medicine, Surgery and Health Sciences, Clinical Unit of Neurology, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy | [d] Neurological Unit, CTO Hospital, AORN ‘Ospedali dei Colli’, Naples, Italy
Correspondence: [*] Correspondence to: Ciro Rosario Ilardi, PhD, IRCCS SYNLAB SDN, Via Emanuele Gianturco 113, 80143 Naples, Italy. E-mail: cirorosario.ilardi@gmail.com; ORCiD: 0000-0003-4328-4739.
Abstract: Background:In the era of disease-modifying therapies, empowering the clinical neuropsychologist’s toolkit for timely identification of mild cognitive impairment (MCI) is crucial. Objective:Here we examine the clinimetric properties of the Montreal Cognitive Assessment (MoCA) for the early diagnosis of MCI due to Alzheimer’s disease (MCI-AD). Methods:Data from 48 patients with MCI-AD and 47 healthy controls were retrospectively analyzed. Raw MoCA scores were corrected according to the conventional Nasreddine’s 1-point correction and demographic adjustments derived from three normative studies. Optimal cutoffs were determined while previously established cutoffs were diagnostically reevaluated. Results:The original Nasreddine’s cutoff of 26 and normative cutoffs (non-parametric outer tolerance limit on the 5th percentile of demographically-adjusted score distributions) were overly imbalanced in terms of Sensitivity (Se) and Specificity (Sp). The optimal cutoff for Nasreddine’s adjustment showed adequate clinimetric properties (≤23.50, Se = 0.75, Sp = 0.70). However, the optimal cutoff for Santangelo’s adjustment (≤22.85, Se = 0.65, Sp = 0.87) proved to be the most effective for both screening and diagnostic purposes according to Larner’s metrics. The results of post-probability analyses revealed that an individual testing positive using Santangelo’s adjustment combined with a cutoff of 22.85 would have 84% post-test probability of receiving a diagnosis of MCI-AD (LR+ = 5.06). Conclusions:We found a common (mal)practice of bypassing the applicability of normative cutoffs in diagnosis-oriented clinical practice. In this study, we identified optimal cutoffs for MoCA to be allocated in secondary care settings for supporting MCI-AD diagnosis. Methodological and psychometric issues are discussed.
Keywords: Alzheimer’s Disease, clinimetrics, cutoffs, diagnosis, Mild Cognitive Impairment, Montreal Cognitive Assessment
DOI: 10.3233/JAD-240339
Journal: Journal of Alzheimer's Disease, vol. 101, no. 1, pp. 293-308, 2024
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