Evidence map›Paper›PMID 36169756›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2023

Optimal MoCA cutoffs for detecting biologically-defined patients with MCI and early dementia.

Ciro Rosario Ilardi, Alina Menichelli, Marco Michelutti, Tatiana Cattaruzza, Paolo Manganotti

Open access · hybridAbstract read
In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
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  4. Multimodal neuroimaging approach for cognitive impairment in Alzheimer's disease.medRxiv : the preprint server for health sciences · 2026
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  12. No matter how big it is, but how you use it: the importance of demographic adjustment in clinical neuropsychology.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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  18. Psychometrics and diagnostics of the Italian version of the Alternate Verbal Fluency Battery (AVFB) in non-demented Parkinson's disease patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Ciro Rosario IlardiDepartment of Psychology, University of Campania "Luigi Vanvitelli", Viale Ellittico 31, 81100, Caserta, Italy. cirorosario.ilardi@unicampania.it.ORCID http://orcid.org/0000-0003-4328-4739
Alina MenichelliNeuropsychology Service, Rehabilitation Unit, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy.
Marco MicheluttiClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy.
Tatiana CattaruzzaClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy.
Paolo ManganottiClinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Trieste University Hospital-ASUGI, University of Trieste, Trieste, Italy.
University of Trieste · ITUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIn this phase II psychometric study on the Montreal cognitive assessment (MoCA), we tested the clinicometric properties of Italian norms for patients with mild cognitive impairment (PwMCI) and early dementia (PwD) and provided optimal cutoffs for diagnostic purposes.

methodsRetrospective data collection was performed for consecutive patients with clinically and biologically defined MCI and early dementia. Forty-five patients (24 PwMCI and 21 PwD) and 25 healthy controls were included. Raw MoCA scores were adjusted according to the conventional 1-point correction (Nasreddine) and Italian norms (Conti, Santangelo, Aiello). The diagnostic properties of the original cutoff (< 26) and normative cutoffs, namely, the upper limits (uLs) of equivalent scores (ES) 1, 2, and 3, were evaluated. ROC curve analysis was performed to obtain optimal cutoffs.

resultsThe original cutoff demonstrated high sensitivity (0.93 [95% CI 0.84-0.98]) but low specificity (0.44 [0.32-0.56]) in discriminating between patients and controls. Nominal normative cutoffs (ES0 uLs) showed excellent specificity (SP range = 0.96-1.00 [0.88-1.00]) but poor sensitivity (SE range = 0.09-0.24 [0.04-0.36]). The optimal cutoff for Nasreddine's method was 23.50 (SE = 0.82 [0.71-0.90]; SP = 0.72 [0.60-0.82]). Optimal cutoffs were 20.97, 22.85, and 22.29 (SE range = 0.69-0.73 [0.57-0.83], SP range = 0.88-0.92 [0.77-0.97]) for Conti's, Santangelo's, and Aiello's methods, respectively.

conclusionUsing the 1-point correction, combined with a cutoff of 23.50, might be useful in ambulatory settings with a large turnout. Our optimal cutoffs can offset the poor sensitivity of Italian cutoffs.

Indexed as

Cognitive DysfunctionDementiaHumansMental Status and Dementia TestsNeuropsychological TestsRetrospective StudiesSensitivity and SpecificityCutoffDementiaMild Cognitive ImpairmentMontreal Cognitive AssessmentSensitivitySpecificity

Identifiers

PMID36169756
PMCPMC9816212
OpenAlexW4297458824

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.