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)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".