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Record W2619634823

Does a history of migraines increase the risk of late-life cognitive health outcomes?

2011· dissertation· en· W2619634823 on OpenAlexaboutno aff
Rebecca Morton

Bibliographic record

VenueUWSpace (University of Waterloo) · 2011
Typedissertation
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMedicineGerontologyPsychologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

As the Canadian population ages, the burden on our community and health care systems of age-related conditions, such as dementia, is increasing and research in these areas is becoming more critical. Dementia is a major health concern for adults as they age. Although dementia is the most common neurological disease in older adults, headaches are the most common neurological disorder across all ages. Migraines are a common form of headache disorders that affect millions of people worldwide. Both neurological disorders—dementia and migraines—cause significant impairment for the individual and strain on their caregivers, as well as substantial economic impact on society. The relationship between migraines and late-life cognitive health outcomes has not yet been thoroughly explored. \n\tUsing data from the Manitoba Study of Health and Aging (MSHA), the relationship between migraines and various late-life cognitive health outcomes, including overall dementia, Alzheimer’s disease (AD), vascular dementia (VaD) and cognitive impairment-no dementia (CIND), was examined. As migraines and cognitive impairments are often associated with various comorbid disorders, analyses also investigated the impact of possible associated intervening variables: hypertension, diabetes, stroke, myocardial infarction and other heart conditions. A secondary focus of this project was to examine whether the association between migraines and late-life cognitive health outcomes varied by sex and family history of dementia. \nMigraines were a significant risk factor for both overall dementia and AD. However, the relationship between migraines and overall dementia appeared to be driven by the significant relationship between migraines and AD. Having a history of migraines was not significantly related to VaD. However, stroke was a statistically significant intervening variable in the relationship between migraines and VaD, indicating that the vascular event, stroke, plays an important part in the migraine-VaD relationship. A history of migraines was not a significant risk factor for CIND. \nResults could not be stratified by sex because of all participants with migraines, no men developed dementia and only one man developed CIND. Furthermore, despite a lack of significant results from models stratified by family history of dementia, the results are suggestive of possible genetic influences in the relationship between migraines and AD. \nOverall, this study supports the conclusion that migraines are a significant risk factor for late-life cognitive health, specifically AD. In addition, this study highlights the possibility that vascular events, such as stroke, may play an important role in the relationship between migraines and VaD. Increased understanding of mid-life risk factors for late-life cognitive health outcomes has important implications for researchers and clinicians in the form of interventions, preventative treatments and medications. In addition, this study suggests that there is a need for further research regarding possible genetic influences in the relationship between migraines and AD. As it was unable to be fully addressed in this study, future studies should investigate gender differences among individuals with migraines developing late-life cognitive health outcomes. This research aims to help develop new strategies that could aid in the prevention of cognitive decline, improve quality of life, and increase the likelihood of healthy aging.

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)0.007
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 score0.078
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.237
Teacher spread0.217 · 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
Published2011
Admission routes1
Has abstractyes

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