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Record W7116911051 · doi:10.1002/alz70860_102161

Framingham Stroke Risk Score, Mild Behavioral Impairment, and Progression to Dementia

2025· article· en· W7116911051 on OpenAlexaff
Ibadat Warring, Dylan X. Guan, Maryam Ghahremani, Eric E. Smith, Zahinoor Ismail

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsDementiaCognitionPsychological interventionStroke (engine)Framingham Heart StudyVascular dementiaCognitive impairmentFramingham Risk Score

Abstract

fetched live from OpenAlex

BACKGROUND: Vascular risk factors (VRFs) contribute to dementia risk through cerebrovascular damage, potentially accelerating dementia onset. Mild behavioral impairment (MBI) identifies dementia risk by leveraging later-life emergent and persistent neuropsychiatric symptoms. This study examined the relationship between vascular burden and progression to MBI and dementia, in MBI-free dementia-free older adults. METHOD: Data from 8519 dementia-free participants aged ≥50 years were acquired from the National Alzheimer's Coordinating Center (Figure 1). A composite measure of VRFs was calculated using the Framingham Stroke Risk Score (FSRS) (Table 1). Higher FSRS indicates greater vascular burden. MBI+ status was contingent on meeting the MBI symptom persistence criterion from consecutive Neuropsychiatric Inventory Questionnaire administrations. Accelerated failure time (AFT) models assessed associations between FSRS and time: 1) to MBI; and 2) from MBI to dementia, adjusted for race, education, marital status, and cognition using propensity score weighting to account for potential confounders. An FSRS*baseline cognitive status (normal cognition[NC]/mild cognitive impairment[MCI]) interaction term determined if FSRS association with incident dementia differed by cognitive status. Subset analyses were conducted for MBI+ participants with NC or MCI at baseline. Time ratios (TRs), expressed as percentages, quantified the effect, with TR values <100% indicating faster progression. RESULT: The sample comprised 8519 MBI-free participants (mean age:73.7±9.0 years; 57.5%female) at baseline. Over a median follow-up of 3.33 years (range: 0.45 to 8.95 years), 17% of participants developed MBI. Higher FSRS was associated with faster progression to MBI (TR%:97.6, 95%CI:0.97-0.98, p < .001), particularly for the domains of decreased motivation (TR:97.6, 95%CI:0.97-0.99, p <0.001), affective dysregulation (TR%:98.7, 95%CI: 0.98-0.99, p <0.001), and impulse dyscontrol (TR%:99.2, 95%CI:0.99-0.99, p = 0.02) (Table 2). The interaction between FSRS and cognitive status suggested a difference in dementia progression amongst MBI+ individuals with MCI and NC (p = 0.003). Higher FSRS had a greater effect size for faster progression to dementia in MBI+ participants with NC (TR%:95.41,95%CI:0.92-0.99, p = 0.01) than MCI (TR%:99.41,95%CI:0.98-1.01, p = 0.33). CONCLUSION: Vascular burden is associated with faster progression to MBI and dementia. Managing VRFs may delay MBI and dementia onset, particularly in cognitively healthy individuals. Future research should explore interventions targeting VRFs to improve cognitive and behavioral brain health.

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)0.003
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.358
Teacher spread0.330 · 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
Published2025
Admission routes1
Has abstractyes

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