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Record W3109427259 · doi:10.5770/cgj.23.432

Validation of the Dépistage Cognitif de Québec in the Oldest Old

2020· article· en· W3109427259 on OpenAlexafffundvenueabout
Amélie Gravel, Carol Hudon, Synthia Meilleur‐Durand, Leila Sellami, David Bergeron, Audrey Paradis, Louis Verret, Marie‐Pierre Fortin, Stéphane Poulin, Joël Macoir, Rémi W. Bouchard, Robert Laforce

Bibliographic record

VenueCanadian Geriatrics Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsCentre intégré universitaire de santé et de services sociaux de la Capitale-NationaleCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanInstitut Universitaire en Santé Mentale de QuébecUniversité LavalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre hospitalier universitaire de Québec
FundersAlzheimer Society
KeywordsMedicineMontreal Cognitive AssessmentNormativeCognitionDementiaCognitive deficitCognitive testGerontologyEffects of sleep deprivation on cognitive performanceCognitive impairmentPsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Objective 
 We aimed to validate the Dépistage Cognitif de Québec (DCQ; www.dcqtest.org) , a new cognitive screening tool for atypical degenerative syndromes, in the oldest old.
 Methods 
 The DCQ was developed by expert behavioural neurologists and clinical neuropsychologists based on updated criteria for Alzheimer’s disease, primary progressive aphasia, and behavioural variant frontotemporal dementia. It targets five relevant cognitive domains: Memory, Visuospatial, Executive, Language, and Behaviour. Validation was performed using a prospective community-based sample consisting of 53 healthy French-speaking Canadian volunteers aged between 80 and 94 years old. Normative data were derived from participants with no history of cognitive difficulties and a Montreal Cognitive Assessment (MoCA) score ≥ 24.
 Results 
 The mean DCQ total score (out of 100) was 84.65 (SD = 6.33). Pearson’s correlation coefficient showed a moderate, but significant, correlation (r = 0.36, p < .01) with the MoCA. Normative data shown in percentiles were stratified by age and education for DCQ total score and for each of the five cognitive domains.
 Conclusions 
 This study suggests that the DCQ is a valid cognitive screen­ing test in the oldest old. It is proposed that the DCQ can help early identification of atypical degenerative syndromes.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.275
Teacher spread0.252 · 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

Citations4
Published2020
Admission routes4
Has abstractyes

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