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Record W4405421034 · doi:10.1192/bjp.2024.136

Improving dementia prognostication in cognitively normal older adults: conventional versus novel approaches to modelling risk associated with neuropsychiatric symptoms

2024· article· en· W4405421034 on OpenAlexafffund
Maryam Ghahremani, Eric E. Smith, Zahinoor Ismail

Bibliographic record

VenueThe British Journal of Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersCanadian Institutes of Health ResearchMathison Centre for Mental Health Research and EducationNational Institute for Health and Care ResearchNational Institute on AgingUniversity of Calgary
KeywordsDementiaHazard ratioIncidence (geometry)Proportional hazards modelMedicineCognitive declineCognitionPsychiatryInternal medicineGerontologyConfidence intervalDisease

Abstract

fetched live from OpenAlex

Background Studies in cognitively normal individuals on associations between psychiatric symptomatology and incident dementia have not reliably differentiated psychiatric syndromes from neuropsychiatric symptoms (NPS) that represent neurodegeneration. Conventional modelling often overlooks symptom natural history. Mild behavioural impairment (MBI) is a syndrome that leverages later-life emergent and persistent NPS to identify a high-risk group for incident dementia. Aim We aimed to explore associations of MBI, and conventionally-measured NPS (NPS-not-MBI), with incident dementia in cognitively normal individuals and the cognitively normal subset with subjective cognitive decline (SCD). Method Using National Alzheimer's Coordinating Center data, MBI was operationalised by the absence of past psychiatric disorders (symptom emergence) and the presence of symptoms at >2/3 of pre-dementia visits (symptom persistence). Kaplan–Meier survival curves and Cox proportional hazards regressions modelled dementia incidence across NPS groups and MBI domains, adjusted for age, gender, education, race, APOE-ε4, and cognitive status. Results The sample comprised 1408 MBI (age 75.2 ± 9.5; 54.3% female), 5625 NPS-not-MBI (age 71.6 ± 8.8; 65.5% female) and 5078 No-NPS (age 71.2 ± 8.9; 67.6% female) participants. Compared with No-NPS, MBI participants had lower dementia-free survival ( P < 0.0001) and 2.76-fold greater adjusted dementia incidence rate (95% CI: 2.27–3.35, P < 0.001); incidence rate in NPS-not-MBI did not differ from No-NPS (hazard ratio 0.97, 95% CI: 0.82–1.14, P = 0.687). Of those with MBI who progressed to dementia, 76.0% developed Alzheimer's disease. Similarly, in the SCD subsample ( n = 3485), persons with MBI had 1.99-fold greater dementia incidence versus No-NPS (95% CI: 1.46–2.71, P < 0.001) while NPS-not-MBI did not differ from No-NPS (hazard ratio 0.92, 95% CI: 0.70–1.19, P = 0.511). Conclusions Incorporating natural history into assessment of psychiatric symptoms in accordance with MBI criteria enhances dementia prognostication and modelling.

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)0.000
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 score0.235
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.253
Teacher spread0.226 · 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

Citations19
Published2024
Admission routes2
Has abstractyes

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