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Record W1974742391 · doi:10.1159/000026247

Prevalence of Cognitive Impairment and Dementia as Defined by Neuropsychological Test Performance

2000· article· en· W1974742391 on OpenAlexaffabout
Fernando A. Larrea, John D. Fisk, Janice Graham, Karen Stadnyk

Bibliographic record

VenueNeuroepidemiology · 2000
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of British ColumbiaDalhousie University
Fundersnot available
KeywordsDementiaNeuropsychologyMedicinePopulationCognitionCognitive impairmentOperationalizationNeuropsychological testPsychiatryNeuropsychological assessmentClinical psychologyGerontologyDiseasePathologyEnvironmental health

Abstract

fetched live from OpenAlex

The Canadian Study of Health and Aging (CSHA) provided a population-based estimate of the prevalence of dementia of 8% for those aged 65 and older. Other studies have produced both higher and lower prevalence estimates. Factors that may contribute to these differences include: the use of or the reliance on neuropsychological testing, the consideration of functional impairment as a criterion for dementia and the inclusion of the category of cognitive impairment without dementia in the diagnostic classification. We examined the impact of these methodological factors by reanalyzing the CSHA database for those individuals who completed neuropsychological testing. If the diagnosis of dementia required only impaired neuropsychological test performance, there was an increased prevalence of dementia relative to the clinical consensus diagnosis, but including the requirement of functional impairment for dementia reduced this discrepancy. The findings illustrate the need for clear operationalization of diagnostic criteria for cognitive impairment and dementia in neuroepidemiological studies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.329
Teacher spread0.306 · 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.

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

Citations18
Published2000
Admission routes2
Has abstractyes

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