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Record W4406051224 · doi:10.1002/alz.088099

Functional impairment in a dementia‐free sample associated with a higher risk of Mild Behavioral Impairment

2024· article· en· W4406051224 on OpenAlexaff
Moyra E. Mortby, Zahinoor Ismail, Kaarin J. Anstey

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsDementiaPsychologyLogistic regressionActivities of daily livingCognitive impairmentCognitionClinical Dementia RatingPopulationClinical psychologyAudiologyPsychiatryMedicineInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Mild Behavioral Impairment (MBI) and functional ability are two non-cognitive markers of dementia. To date, little is known about the impact of functional ability on the clinical manifestation of MBI. Using data from the Australian population-based PATH Through Life Study we examined the impact of functional ability on MBI. We hypothesized that poorer functional ability in a dementia-free sample (with at most Mild Cognitive Impairment; MCI) would be associated with a higher likelihood of MBI. METHOD: 1377 dementia-free participants (52% male; aged 72-79; 847 cognitively healthy, 397 cognitively normal, but-at-risk (i.e., subjective cognitive decline), 133 MCI) were included. Functional ability was assessed using the Bayer Activities of Daily Living scale (B-ADL), which comprises 25 items assessed by an informant. Items are scored 1-10 with higher scores indicating poorer functional ability. Presence and absence of MBI and its five domains (decreased motivation, affect dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content) were approximated using a previously published transformation algorithm, which utilizes items from the Neuropsychiatric Inventory assessed at a single study visit. Binomial logistic regression analyses were conducted to examine risk of MBI associated with functional impairment. Models controlled for Mini Mental State Exam scores (MMSE) and self-reported gender (male/female). RESULT: Adjusted logistic regression (MMSE and gender) showed that a one-unit increase on the B-ADL was associated with a 2.27-fold greater risk of MBI (95% CI 1.962-2.624; p<.001). Similarly, for all 5 MBI domains, a one-unit increase of B-ADL was associated with greater risk of all domains: decreased motivation (B = 2.26; 95% CI 1.898-2.684; p<.001), affect dysregulation (B = 2.02; 95% CI 1.763-2.306; p<.001), impulse dyscontrol (B = 2.01; 95% CI 1.756-2.301; p<.001), social inappropriateness (B = 2.01; 95% CI 1.707-2.378; p<.001), and abnormal perception/thought content (B = 1.82; 95% CI 1.417-2.335; p<.001). CONCLUSION: This study is amongst the first to identify a higher risk of MBI associated with functional ability in dementia-free older adults. These findings highlight the importance of early monitoring of changes in functional ability and behaviour, even prior to the onset of cognitive symptomatology. They also provide further evidence of the clinical utility of functional ability and MBI as early markers of 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)0.001
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.038
GPT teacher head0.312
Teacher spread0.273 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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