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Record W2199413880 · doi:10.1177/1533317515619480

Simple Neuropsychological Tests May Identify Participants in Whom Aspirin Use Is Associated With Lower Dementia Incidence

2015· article· en· W2199413880 on OpenAlexafffundabout
Shahram Oveisgharan, Vladimir Hachinski

Bibliographic record

VenueAmerican Journal of Alzheimer s Disease & Other Dementias® · 2015
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsDementiaNeuropsychologyIncidence (geometry)Vascular dementiaAspirinOdds ratioCognitionConfidence intervalPsychologyMedicinePsychiatryClinical psychologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: We hypothesized that neuropsychological tests could help in identifying preclinical stages of vascular cognitive impairment, when aspirin use might be associated with lower dementia incidence. METHODS: We used data of Canadian Study of Health and Aging (CSHA) which was a longitudinal study of Canadians older than 65 years and was done in 3 waves, 1991 to 1992 (CSHA-1), 1996 to 1997 (CSHA-2), and 2001 to 2002. RESULTS: CSHA-1 participants with vascular dementia performed worse in copying pentagons and writing subtests of modified Mini-Mental State Examination test than participants with probable Alzheimer's disease. Salicylates use was associated with lower incident dementia among normal cognition CSHA-1 participants who had low scores in copying pentagons and writing subtests after controlling for age, sex, education, and vascular risk factors (odds ratio = 0.25, 95% confidence interval: 0.073-0.86, P = .028). CONCLUSIONS: Two simple neuropsychological tests might help in identifying preclinical stages of vascular cognitive impairment, and salicylates use was associated with lower dementia incidence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.342
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2015
Admission routes3
Has abstractyes

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Same venueAmerican Journal of Alzheimer s Disease & Other Dementias®Same topicAntiplatelet Therapy and Cardiovascular DiseasesFrench-language works237,207