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Record W4396953757 · doi:10.1161/circ.149.suppl_1.p335

Abstract P335: Predictors of Cognitive Resilience in Those With and Without High White Matter Hyperintensity Burden: A Post-Hoc Analysis of Systolic Blood Pressure Intervention Trial Memory & Cognition in Decreased Hypertension (SPRINT MIND)

2024· article· en· W4396953757 on OpenAlexaboutno aff
Eric Stulberg, Alexander R. Zheutlin, Adam de Havenon

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHyperintensityBlood pressurePost-hoc analysisCognitionCardiologyInternal medicineRandomized controlled trialMagnetic resonance imagingPsychiatry

Abstract

fetched live from OpenAlex

Introduction: Little is known if predictors of cognitive resilience (CR) differ between adults with or without large white matter hyperintensity burdens. In the current analysis of cross-sectional baseline SPRINT MIND data, we a) determined bivariate associations of sociodemographic, vascular-metabolic, and neurodegenerative biomarkers with CR and b) delineated variables that maximized predictive fit of CR among participants with the highest and lowest white matter hyperintensity volumes (WMHv). Methods: We included SPRINT MIND participants with baseline available plasma biomarker concentrations & Montreal Cognitive Assessment (MoCA) scores. We then created two analytic samples: those with the highest tertile of WMHv (N = 186) and those with the lowest tertile (N=134). We defined CR two ways: as a MoCA score a) >25 or b) >22. We determined the association between sociodemographic, vascular-metabolic, and serum neurodegenerative variables, as well as WMHv with CR using logistic regressions to generate unadjusted odds ratios (OR) & 95% confidence intervals (CI). Multivariate lasso regressions were then used to determine which variables optimized predictive fit of CR, and R 2 values were calculated. Results: In participants with the lowest tertile of WMHv , the median age was 66 years, 45.5% were female and 63% were Non-Hispanic white. In participants with the highest tertile of WMHv, the median age was 73 years, 45.7% were female and 66% were Non-Hispanic white. . CR defined as MoCA scores > 25 & >22 was present in 37.3% and 64.9% in those with the lowest tertile of WMHv and 28.5% & 56.5% in those with the highest tertile, respectively. Higher education and self-reported race generally had the strongest ORs in all analyses (Table 1 excerpt). Only age and education level were included in all four predictive models after lasso shrinkage. The R 2 values for all lasso regressions were <0.25. Conclusion: Education level may be associated with CR irrespective of WMHv. However, a large variation of CR remains unaccounted for.

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 score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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