MétaCan
Menu
Back to cohort
Record W7011587536

MoCA, ACE-R, and MMSE versus the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards Neuropsychological Battery after TIA and stroke.

2012· article· en· W7011587536 on OpenAlexaboutno aff

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeuropsychologyCognitionStroke (engine)Cognitive impairmentNeuropsychological assessmentNeuropsychological test
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The Montreal Cognitive Assessment (MoCA) and Addenbrooke's Cognitive Examination-Revised (ACE-R) are proposed as short cognitive tests for use after stroke, but there are few published validations against a neuropsychological battery. We studied the relationship between MoCA, ACE-R, Mini-Mental State Examination (MMSE) and mild cognitive impairment (MCI) in patients with cerebrovascular disease and mild cognitive impairment (MCI). METHODS: One hundred consecutive non-institutionalized patients had the MMSE, MoCA, ACE-R, and National Institute of Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Harmonization Standards Neuropsychological Battery ≥ 1 year after transient ischemic attack or stroke in a population-based study. MCI was diagnosed using modified Petersen criteria in which subjective cognitive complaint is not required (equivalent to cognitive impairment-no dementia) and subtyped by number and type of cognitive domains affected. RESULTS: Among 91 nondemented subjects completing neuropsychological testing (mean/SD age, 73.4/11.6 years; 44% female; 56% stroke), 39 (42%) had MCI (amnestic multiple domain=10, nonamnestic multiple domain=9, nonamnestic single domain=19, amnestic single domain=1). Sensitivity and specificity for MCI were optimal with MoCA <25 (sensitivity=77%, specificity=83%) and ACE-R <94 (sensitivity=83%, specificity=73%). Both tests detected amnestic MCI better than nonamnestic single-domain impairment. MMSE only achieved sensitivity >70% at a cutoff of <29, mainly due to relative insensitivity to single-domain impairment. CONCLUSIONS: The MoCA and ACE-R had good sensitivity and specificity for MCI defined using the Neurological Disorders and Stroke-Canadian Stroke Network Vascular Cognitive Impairment Battery ≥1 year after transient ischemic attack and stroke, whereas the MMSE showed a ceiling effect. However, optimal cutoffs will depend on use for screening (high sensitivity) or diagnosis (high specificity). Lack of timed measures of processing speed may explain the relative insensitivity of the MoCA and ACE-R to single nonmemory domain impairment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.281
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueOxford University Research Archive (ORA) (University of Oxford)Same topicMetallurgy and Cultural ArtifactsFrench-language works237,207