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Record W4205482429 · doi:10.1002/alz.055314

Self and informant‐rated mild behavioral impairment and genetic risk for AD: The respondent matters

2021· article· en· W4205482429 on OpenAlexaff
Byron Creese, Ryan Arathimos, Helen Brooker, Anne Corbett, Dag Aarsland, Cathryn M. Lewis, Clive Ballard, Zahinoor Ismail

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsApathyPsychologyClinical psychologyAnxietyMoodDiseaseDepression (economics)Logistic regressionPsychiatryMedicineCognitionInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Late‐life onset neuropsychiatric symptoms (NPS) have received increasing attention in recent years because of their prognostic potential for neurodegenerative disease. As focus intensifies, appropriate measurement will be critical. The emergence of Mild Behavioral Impairment ‐ which describes late‐life onset apathy, mood/anxiety symptoms, impulse dyscontrol, social inappropriateness, and psychosis ‐ and the MBI‐Checklist (MBI‐C), developed to capture these symptoms in accordance with the ISTAART‐AA MBI criteria, has been a step forward. Previous work has demonstrated only modest correlation between proxy informant and self‐rated MBI‐C responses, but the significance of these differences in responses is not yet understood. Moreover, there is relatively less work examining non‐affective late‐life NPS. To explore both of these factors, we examined the relationship between genetic risk for Alzheimer’s disease and the five MBI domains in a sample of cognitively normal older adults. Method Genetic and clinical data from 2,529 cognitively normal participants aged ≥65 in the PROTECT study were analysed. MBI was evaluated using the MBI‐C; individual domain scores were calculated, and participants dichotomised into domain ‘present’ or ‘absent’. Polygenic risk scores (PRS) for Alzheimer’s disease were used as predictors in binary logistic regression models with the MBI domains, each rated by self and by proxy, as separate outcomes. To evaluate whether AD PRS was associated with depression, the most commonly considered NPS in older adults, we also tested the association between AD PRS and PHQ‐9 score (>=5 or <5). Result AD PRS was associated with a greater risk of apathy and impulse dyscontrol in proxy MBI‐C ratings but not in self‐report MBI‐C ratings (OR: 1.2 [95% CI: 1.06‐1.40], p=0.004; OR: 1.12 [95% CI: 1.01‐1.24], p=0.03, respectively). There was no association between AD PRS and PHQ‐9 symptoms. Conclusion Proxy informant and self‐reported MBI‐C elicit different associations in analysis of AD genetic risk. These findings suggest that even in cognitively normal older adults, proxy informant ratings are important to consider in the evaluation of NPS and risk of dementia. There was no association between PHQ‐9 symptoms and AD PRS, highlighting the importance of the multi‐domain MBI‐C as a specific tool to capture late‐life NPS as risk factors for dementia.

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)0.006
metaresearch head score (Gemma)0.020
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 score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.063
GPT teacher head0.392
Teacher spread0.329 · 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
Published2021
Admission routes1
Has abstractyes

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