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Record W4401886969 · doi:10.1080/13607863.2024.2394591

Potential for reducing dementia risk: association of the CAIDE score with additional lifestyle components from the LIBRA score in a population at high risk of dementia

2024· article· en· W4401886969 on OpenAlexaboutno aff
Mandy Claus, Melanie Luppa, Andrea Zülke, Iris Blotenberg, María Isabel Cardona, Juliane Döhring, Catharina Escales, Robert P. Kosilek, Anke Oey, Isabel Zöllinger, Christian Brettschneider, David Czock, Thomas Frese, Jochen Gensichen, Wolfgang Hoffmann, Hanna Kaduszkiewicz, Hans‐Helmut König, Birgitt Wiese, Jochen René Thyrian, Steffi G. Riedel‐Heller

Bibliographic record

VenueAging & Mental Health · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaMedicineAssociation (psychology)Framingham Risk ScoreDiseaseGerontologyIncidence (geometry)PopulationPsychologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: Various dementia risk scores exist that assess different factors. We investigated the association between the Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) score and modifiable risk factors in the Lifestyle for Brain Health (LIBRA) score in a German population at high risk of Alzheimer's disease. METHOD: Baseline data of 807 participants of AgeWell.de (mean age: 68.8 years (SD = 4.9)) were analysed. Stepwise multivariable regression was used to examine the association between the CAIDE score and additional risk factors of the LIBRA score. Additionally, we examined the association between dementia risk models and cognitive performance, as measured by the Montreal Cognitive Assessment. RESULTS: = 0.032). Although all were classified as high risk on CAIDE, 31.5% scored ≤0 points on LIBRA, indicating a lower risk of dementia. Higher CAIDE and LIBRA scores were associated with lower cognitive performance. CONCLUSION: Regular cognitive activities and increased fruit and vegetable intake were associated with lower CAIDE scores. Different participants are classified as being at-risk based on the dementia risk score used.

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 score0.011
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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