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Record W3084193514 · doi:10.1002/gps.5426

Trajectories of decline on instrumental activities of daily living prior to dementia in persons with mild cognitive impairment

2020· article· en· W3084193514 on OpenAlexafffund
Simon Cloutier, Howard Chertkow, Marie‐Jeanne Kergoat, Isabelle Gélinas, Serge Gauthier, Sylvie Belleville

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcGill UniversityJewish General HospitalInstitut Universitaire de Gériatrie de Montréal
FundersCanadian Institutes of Health Research
KeywordsDementiaActivities of daily livingCognitive declineCognitionGerontologyNeuropsychologyPsychologyCognitive impairmentAutonomyMedicinePsychiatryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The main objective was to determine the trajectory of instrumental activities of daily living (iADL) decline in persons with mild cognitive impairment (MCI) who progressed towards dementia relative to persons with MCI who remained stable. METHODS/DESIGN: At study entry, 121 participants met criteria for MCI. Based on the follow-up, 47 participants later converted to dementia and were identified as progressors. Sixteen participants, identified as decliners, presented a significant cognitive decline but did not reach the criteria for dementia within the study timeframe. Stable MCI remained cognitively stable during the 5-year follow-up; n = 58. Participants completed a yearly assessment using clinical tests/questionnaires, neuropsychological measures, and functional autonomy assessment until they met criteria for dementia. The average number of months for the follow-up was 34. RESULTS: Many years of stable performance followed by an accelerated decline just prior to diagnosis, was observed for complex activities for progressors. No change was found for stable MCI and a gradual linear decline characterized decliners. The housekeeping-related activities component showed a linear decline in progressors and did not change in stable and decliner MCI. We found a predictive model that includes significant predictors of dementia conversion with a high diagnostic accuracy the following year (area under the curve = 0.94 [95% confidence level; lower bound: 0.87, upper bound: 1]). CONCLUSIONS: It is critical to assess iADL that reflect complex activities in the evaluation of MCI individuals as their impairment, combined with change on cognitive markers, indicates a higher risk of dementia progression 1 or 2 years later.

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 score0.010
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.305
Teacher spread0.291 · 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

Citations56
Published2020
Admission routes2
Has abstractyes

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