On the Clinimetrics of the Montreal Cognitive Assessment: Cutoff Analysis in Patients with Mild Cognitive Impairment due to Alzheimer's Disease.
Autor: | Ilardi CR; IRCCS SYNLAB SDN, Naples, Italy., Menichelli A; Department of Medicine, Surgery and Health Sciences, Rehabilitation Unit, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy., Michelutti M; Department of Medicine, Surgery and Health Sciences, Clinical Unit of Neurology, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy., Cattaruzza T; Department of Medicine, Surgery and Health Sciences, Clinical Unit of Neurology, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy., Federico G; IRCCS SYNLAB SDN, Naples, Italy., Salvatore M; IRCCS SYNLAB SDN, Naples, Italy., Iavarone A; Neurological Unit, CTO Hospital, AORN 'Ospedali dei Colli', Naples, Italy., Manganotti P; Department of Medicine, Surgery and Health Sciences, Clinical Unit of Neurology, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy. |
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Jazyk: | angličtina |
Zdroj: | Journal of Alzheimer's disease : JAD [J Alzheimers Dis] 2024; Vol. 101 (1), pp. 293-308. |
DOI: | 10.3233/JAD-240339 |
Abstrakt: | 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. |
Databáze: | MEDLINE |
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