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Record W3093327417 · doi:10.1002/trc2.12068

CCCDTD5 recommendations on early non cognitive markers of dementia: A Canadian consensus

2020· article· en· W3093327417 on OpenAlexaffabout
Manuel Montero‐Odasso, Frederico Pieruccini‐Faria, Zahinoor Ismail, Karen Li, Andrew Lim, Natalie A. Phillips, Nellie Kamkar, Yanina Sarquis‐Adamson, Mark Speechley, Olga Theou, Joe Verghese, Lindsay Wallace, Richard Camicioli

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2020
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of AlbertaDalhousie UniversityHealth Sciences CentreWestern UniversityConcordia UniversityUniversity of CalgaryParkwood InstituteSunnybrook Health Science CentreLawson Health Research Institute
Fundersnot available
KeywordsDementiaCognitionCognitive declinePsychologyDiseasePhysical medicine and rehabilitationMedicinePsychiatryClinical psychologyPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Cognitive impairment is the hallmark of Alzheimer's disease (AD) and related dementias. However, motor decline has been recently described as a prodromal state that can help to detect at-risk individuals. Similarly, sensory changes, sleep and behavior disturbances, and frailty have been associated with higher risk of developing dementia. These clinical findings, together with the recognition that AD pathology precedes the diagnosis by many years, raises the possibility that non-cognitive changes may be early and non-invasive markers for AD or, even more provocatively, that treating non-cognitive aspects may help to prevent or treat AD and related dementias. METHODS: A subcommittee of the Canadian Consensus Conference on Diagnosis and Treatment of Dementia reviewed areas of emerging evidence for non-cognitive markers of dementia. We examined the literature for five non-cognitive domains associated with future dementia: motor, sensory (hearing, vision, olfaction), neuro-behavioral, frailty, and sleep. The Grading of Recommendations Assessment, Development, and Evaluation system was used to assign the strength of the evidence and quality of the recommendations. We provide recommendations to primary care clinics and to specialized memory clinics, answering the following main questions: (1) What are the non-cognitive and functional changes associated with risk of developing dementia? and (2) What is the evidence that sensory, motor, behavioral, sleep, and frailty markers can serve as potential predictors of dementia? RESULTS: Evidence supported that gait speed, dual-task gait speed, grip strength, frailty, neuropsychiatric symptoms, sleep measures, and hearing loss are predictors of dementia. There was insufficient evidence for recommending assessing olfactory and vision impairments as a predictor of dementia. CONCLUSIONS: Non-cognitive markers can assist in identifying people at risk for cognitive decline or dementia. These non-cognitive markers may represent prodromal symptoms and several of them are potentially amenable to treatment that might delay the onset of cognitive decline.

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)0.086
metaresearch head score (Gemma)0.196
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.522
Threshold uncertainty score0.950

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0860.196
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0070.017
Bibliometrics0.0190.013
Science and technology studies0.0070.004
Scholarly communication0.0100.007
Open science0.0210.013
Research integrity0.0260.020
Insufficient payload (model declined to judge)0.0150.008

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 head0.330
GPT teacher head0.508
Teacher spread0.177 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations79
Published2020
Admission routes2
Has abstractyes

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