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Impact of the Prevalence of Cognitive Impairment on the Accuracy of the Montreal Cognitive Assessment: The Advantage of Using two MoCA Thresholds to Identify Error-prone Test Scores.

ABSTRACT: OBJECTIVES:The focus of this study is the classification accuracy of the Montreal Cognitive Assessment (MoCA) for the detection of cognitive impairment (CI). Classification accuracy can be low when the prevalence of CI is either high or low in a clinical sample. A more robust result can be expected when avoiding the range of test scores within which most classification errors are expected, with adequate predictive values for more clinical settings. METHODS:The classification methods have been applied to the MoCA data of 5019 patients in the Uniform Data Set of the University of Washington's National Alzheimer's Coordinating Center, to which 30 Alzheimer Disease Centers (ADCs) contributed. RESULTS:The ADCs show sample prevalence of CI varying from 0.22 to 0.87. Applying an optimal cutoff score of 23, the MoCA showed for only 3 of 30 ADCs both a positive predictive value (PPV) and a negative predictive value (NPV) ?0.8, and in 18 cases, a PPV ?0.8 and for 13 an NPV ?0.8. Overall, the test scores between 22 and 25 have low odds of true against false decisions of 1.14 and contains 55.3% of all errors when applying the optimal dichotomous cut-point. Excluding the range 22 to 25 offers higher classification accuracies for the samples of the individual ADCs. Sixteen of 30 ADCs showed both NPV and PPV ?0.8, 25 show a PPV ?0.8, and 21 show an NPV ?0.8. CONCLUSION:In comparison to a dichotomous threshold, considering the most error-prone test scores as uncertain enables a classification that offers adequate classification accuracies in a larger number of clinical settings.

SUBMITTER: Landsheer JA

PROVIDER: S-EPMC7497609 | biostudies-literature | 2020 Jul-Sep

REPOSITORIES: biostudies-literature

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Impact of the Prevalence of Cognitive Impairment on the Accuracy of the Montreal Cognitive Assessment: The Advantage of Using two MoCA Thresholds to Identify Error-prone Test Scores.

Landsheer Johannes A JA

Alzheimer disease and associated disorders 20200701 3

<h4>Objectives</h4>The focus of this study is the classification accuracy of the Montreal Cognitive Assessment (MoCA) for the detection of cognitive impairment (CI). Classification accuracy can be low when the prevalence of CI is either high or low in a clinical sample. A more robust result can be expected when avoiding the range of test scores within which most classification errors are expected, with adequate predictive values for more clinical settings.<h4>Methods</h4>The classification metho ...[more]

PMID: 31934880

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Project description:Given advantages in reperfusion therapy leading to mild stroke, less apparent cognitive deficits can be overseen in a routine neurological examination. Despite the widespread use of the Montreal Cognitive Assessment (MoCA), age- and education-specific cutoffs for the detection of post-stroke cognitive impairment (PSCI) are not established, hampering its valid application in stroke. We aimed to establish age- and education-specific MoCA cutoffs to better discriminate patients with and without acute PSCI. Patients with acute ischemic stroke underwent the MoCA and a detailed neuropsychological assessment. PSCI was defined as a performance < - 1.5 SD in ≥ 2 cognitive domains. As secondary data analysis, the discriminant abilities of the MoCAraw-score (not adding + 1 as correction for ≤ 12 years of education, YoE) cutoffs were automatically derived based on Youden Index and evaluated by receiver operating characteristic analyses across age- (< 55, 55-70, > 70 years old) and education-specific (≤ 12 and > 12 YoE) groups. 351 stroke patients (67.4 ± 14.1 years old; 13.1 ± 2.8 YoE) underwent the neuropsychological assessment 2.7 ± 2.0 days post-stroke. The original MoCA cutoff < 26 falsely classified 26.2% of examined patients, with poor sensitivity in younger adults (34.8% in patients < 55 years > 12 YoE) and poor specificity in older adults (55.0%, in > 70 years ≤ 12 YoE). By maximizing both sensitivity and specificity, the optimal MoCAraw cutoffs were: (i) < 28 in patients aged < 55 with > 12 YoE (sensitivity = 69.6%, specificity = 77.8%); (ii) < 22 and < 25 in patients > 70 years with ≤ 12 and > 12 YoE (sensitivity = 61.6%, specificity = 90.0%; sensitivity = 63.3%, specificity = 84.0%, respectively). In other groups the optimal MoCAraw cutoff was < 26. Age and education level should be considered when interpreting MoCA-scores. Though new age- and education-specific cutoffs demonstrated higher discriminant ability for PSCI, their performance in young stroke and adults with higher education level was low due to ceiling effects and MoCA subtests structure, and cautious interpretation in these patients is warranted.Trial registration: ClinicalTrials.gov Identifier: NCT05653141.

Project description:PurposeMany age-related structural and functional changes in the brain have important consequences. Long-term exposure to mercury and the impact of functional polymorphisms of metal-regulating proteins such as metallothioneins (MTs) can result in neurological-neurobehavioral effects in elderly individuals. Therefore, the aims of this study are to examine the associations between biomarkers of mercury exposure and cognitive impairment and to investigate the effect of the rs8052394 single nucleotide polymorphism (SNP) of the potential modifier gene MT1A on different domains of the Montreal Cognitive Assessment (MoCA).Materials and methodsWe studied 436 participants aged ≥55 years from the Electricity Generating Authority of Thailand study. They underwent a physical examination, an extensive cognitive assessment with the MoCA (cutoff <26 points), and a biochemical analysis related to diabetes and dyslipidemia. The blood mercury level was determined by inductively coupled plasma mass spectrometry. Genotyping of the MT1A rs8052394 SNP was performed by the restriction fragmentation length polymorphism method.ResultsThe mean age of the study population was 58.8±3.01 years, and most had ≥12 years of education (75.7%). The primary study finding was that the prevalence of mild cognitive impairment (MCI) in older Thai adults was 39.7%. The frequency distributions of the G allele of the rs8052394 SNP of the MT1A gene were significantly associated with the total and sub-domain MoCA scores. The prevalence of MCI was significantly associated with increased age, hypertriglyceridemia, hyperhomocysteinemia, the third tertile of blood mercury concentration, and the rs8052394 variant genotype of MT1A (P values for all odds ratios <0.05).ConclusionThese findings suggested that neurocognitive effects associate with mercury exposure and genetic susceptibility in toxicokinetics. Public health strategies can be used to implement as a comprehensive action plan to educate vulnerable populations on how to reduce mercury exposure. Concurrently, impact of such genetic predisposition requires replication for identifying and protecting susceptible individuals from mercury toxicity.

Dataset Information

Impact of the Prevalence of Cognitive Impairment on the Accuracy of the Montreal Cognitive Assessment: The Advantage of Using two MoCA Thresholds to Identify Error-prone Test Scores.

Publications

Impact of the Prevalence of Cognitive Impairment on the Accuracy of the Montreal Cognitive Assessment: The Advantage of Using two MoCA Thresholds to Identify Error-prone Test Scores.

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