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Record W2026613325 · doi:10.1159/000097791

Neuropsychological Comparison of Alzheimer’s Disease and Dementia with Lewy Bodies

2006· article· en· W2026613325 on OpenAlexaff
Timothy A. Crowell, Cheryl A. Luis, D. E. Cox, Michael Mullan

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2006
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsRichmond HospitalVancouver Coastal Health
Fundersnot available
KeywordsDementia with Lewy bodiesPsychologyDementiaCognitionNeuropsychologyAudiologyPsychomotor learningNeuropsychological testVerbal fluency testRecallAlzheimer's diseaseEpisodic memoryCognitive testPsychiatryCognitive psychologyDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: The present study examined the patterns of memory and cognitive performance associated with Alzheimer's disease (AD) and dementia with Lewy bodies (DLB). METHODS: A battery of standardized neuropsychological tests was administered to individuals with these disorders as well as to a group of cognitively intact controls. The battery included measures of memory (learning, recall and recognition), language, visuospatial ability, psychomotor speed, executive functioning and mood. All subjects (n = 115) were evaluated at a memory disorder clinic and were diagnosed based on published criteria. RESULTS: The controls outperformed both dementia groups on all cognitive measures. With respect to memory, the DLB group scored significantly higher than the AD group on measures of word list free recall and recognition (p < or = 0.001). In other cognitive domains, the AD group performed significantly better than the DLB group on constructional praxis, sustained attention, phonemic fluency, spatial judgment, psychomotor speed and working memory (all p < or = 0.01). CONCLUSION: These findings support the usefulness of memory and other cognitive test score patterns as in distinguishing AD from DLB, particularly in mild to moderately demented populations that may not present with hallmark symptomology.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.819

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)0.0000.000

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 head0.016
GPT teacher head0.309
Teacher spread0.293 · 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

Citations49
Published2006
Admission routes1
Has abstractyes

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