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Record W2043867003 · doi:10.1161/strokeaha.110.606277

Is the Montreal Cognitive Assessment Superior to the Mini-Mental State Examination to Detect Poststroke Cognitive Impairment?

2011· article· en· W2043867003 on OpenAlex
Olivier Godefroy, Andreas Fickl, Martine Roussel, Caroline Auribault, Jean Marc Bugnicourt, Chantal Lamy, Sandrine Canaple, Gil Petitnicolas

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStroke · 2011
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentMedicineReceiver operating characteristicMini–Mental State ExaminationNeuropsychological testPredictive value of testsPredictive valueNeuropsychologyArea under the curveCognitive impairmentInternal medicineNeuropsychological assessmentCognitionAudiologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: A screening test is required to improve the diagnosis of poststroke cognitive impairment. The Montreal Cognitive Assessment (MoCA), a newly designed screening test, has been found to be more sensitive than Mini-Mental State Examination (MMSE), but its clinical value has not been established by means of a comprehensive neuropsychological battery. This study was designed to assess the value of MoCA and MMSE to detect poststroke cognitive impairment determined by a neuropsychological battery. METHODS: Both screening tests and a neuropsychological battery were administered during the acute phase in 95 patients referred for recent infarct or hemorrhage. Raw MMSE and MoCA scores were used with published cutoffs and new cutoff scores for MMSE and MoCA were also computed after adjustment for age and education. RESULTS: Using raw scores, MoCA was more frequently impaired (P=0.0001) than MMSE. MoCA showed good sensitivity (sensitivity, 0.94) but moderate specificity (specificity, 0.42; positive predictive value, 0.77; negative predictive value, 0.76), whereas an inverse profile was observed for MMSE (sensitivity, 0.66; specificity, 0.97; positive predictive value, 0.98; negative predictive value, 0.58). Adjusted scores with new cutoffs (MMSE(adj) ≤24, MoCA(adj) ≤20) provided good sensitivity and very good specificity for both tests (MMSE(adj): sensitivity, 0.7, specificity, 0.97, positive predictive value, 0.98, negative predictive value, 0.61; MoCA(adj): sensitivity, 0.67, specificity, 0.9, positive predictive value, 0.93, negative predictive value, 0.57). On receiver operating characteristic curve analysis, areas under the curve of all scores were >0.88. CONCLUSIONS: The previously reported high sensitivity of MoCA is associated with low specificity. Both screening tests are moderately sensitive to acute poststroke cognitive impairment. This study provides indications for the diagnosis of poststroke cognitive 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.297
Teacher spread0.279 · 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