MétaCan
Menu
Back to cohort
Record W2102841000 · doi:10.3109/02699052.2013.835867

The mini-mental state examination and the montreal cognitive assessment after traumatic brain injury: An early predictive study

2013· article· en· W2102841000 on OpenAlexafffundabout
Élaine de Guise, Joanne LeBlanc, Marie-Claude Champoux, Céline Couturier, Abdulrahman Y. Alturki, Julie Lamoureux, Monique Desjardins, Judith Marcoux, Mohammed Maleki, Mitra Feyz

Bibliographic record

VenueBrain Injury · 2013
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcGill University Health CentreUniversité de MontréalMontreal General Hospital
FundersMcGill University Health Centre
KeywordsMontreal Cognitive AssessmentTraumatic brain injuryCognitionMini–Mental State ExaminationMedicineCognitive impairmentMental stateMental status examinationPsychologyPhysical therapyPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

PRIMARY OBJECTIVE: To compare results on the Montreal Cognitive Assessment (MoCA) to those on the Mini-Mental State Examination (MMSE) in patients with traumatic brain injury (TBI) and to predict the outcome at discharge from the acute care setting. RESEARCH DESIGN: A retrospective study. METHODS AND PROCEDURES: The MoCA and the MMSE were administered to 214 patients with TBI during their acute care hospitalization in a Level I trauma centre. Outcome was measured with the Disability Rating Scale (DRS). MAIN OUTCOMES AND RESULTS: A linear regression determined that the MoCA, the MMSE, TBI severity, education level and presence of diffuse injuries predicted 57% of the total variability of the DRS scores. The model without the MMSE had a R2 of 53.7% and the model without the MoCA had a R2 of 55.0%. The models without the MMSE or the MoCA had a R2 of 24.9%. CONCLUSIONS: These results indicated that the MoCA and the MMSE function as similar predictors of the DRS at discharge.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.847
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.032
GPT teacher head0.353
Teacher spread0.321 · 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; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations45
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueBrain InjurySame topicTraumatic Brain Injury ResearchFrench-language works237,207