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Record W4205636809 · doi:10.1002/alz.055833

Evaluation of blood pressure and cognitive function using individual participant data meta‐analysis: The Life‐Course Blood Pressure Cognition (LCBP‐COG) study

2021· article· en· W4205636809 on OpenAlexaffabout
Ying Xu, G. Peggy McFall, Lina Rydén, Johan Skoog, Phillip J. Tully, Kaarin J. Anstey, Nicolas Cherbuin, Roger A. Dixon, Ingmar Skoog, Ruth Peters

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
Fundersnot available
KeywordsBlood pressureMedicineCognitionCognitive declineLongitudinal studyLogistic regressionCohortCohort studyPulse pressureDemographyInternal medicinePsychologyDementiaDiseasePsychiatryPathology

Abstract

fetched live from OpenAlex

Abstract Background The prognostic significance of various blood pressure (BP) indices (i.e. systolic BP [SBP], diastolic BP [DBP], pulse pressure [PP] and mean arterial pressure [MAP]) on cardio‐ and cerebrovascular health vary across age groups. We examined the association between baseline BP indices in mid‐ and late‐life and cognitive function over a 9‐15 year period. Method We performed pooled analyses of data from 3 longitudinal cohort studies. The Personality and Total Health (PATH) Through Life study of adults initially aged 40‐44 and 60‐64 years in Australia, and Victoria Longitudinal Study (VLS) of adults initially aged 55‐85 years in Canada, included four waves of data collection every 4‐5 years. The Gothenburg H70 Birth cohort study of adults initially aged 70 years included three waves of data collection every 4‐5 years. The association between baseline BP and cognitive decline on the Mini‐Mental State Examination (MMSE) was categorized using the reliable change index (Duff K. 2012) and analyzed using logistic regression adjusted for age, sex, and study. Additional analyses examined relationships between baseline BP and repeated cognitive measures of memory, attention and processing speed, and executive function, using linear mixed models (PATH and H70). Only participants with complete BP and cognitive measures were included. Result Data from 2912 participants (mean baseline age 54.3 years, range 40 to 83 years, 1395 (47.9%) male) were included. Examining baseline BP and age, we observed SBP increasing with age until a small decrease at around 80 years. DBP and MAP also showed an increase with age until early late‐life (around 60 years) and were lower at older ages, PP consistently increased (Figure 1). There were no relationships between baseline BP measures and MMSE. For PATH only, higher SBP (P=0.002), DBP (P=0.0007) and MAP (P=0.0006) at age 40 years, and higher DBP (P=0.004) at 60 years, were associated with greater annual deterioration in attention and processing speed (symbol‐digit‐modalities test) over the subsequent decade (Figure 2). Conclusion Higher BP in midlife and DBP in early late‐life, were associated with a greater decline in measures of attention and processing speed. We observed no associations between BP and MMSE decline.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Meta-analysislow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.012
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0140.034
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.003
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 head0.314
GPT teacher head0.384
Teacher spread0.071 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical · Review

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
Published2021
Admission routes2
Has abstractyes

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