Cognition and elevated blood pressure in community‐dwelling older adults with subjective cognitive decline: A cross‐sectional exploratory study
Bibliographic record
Abstract
Abstract Background The impact of blood pressure (BP) on cognition in older adults remains equivocal. We investigated the relationships between cognition (global and domain‐specific) and ambulatory blood pressure in older adults with subjective cognitive decline (SCD). Method We conducted a cross‐sectional exploratory analysis of data collected from 230 community‐dwelling older adults (age mean [SD]: 69.3 [7.2], 57.8% female) with self‐reported SCD. We assessed global cognitive functioning, memory, concentration, planning, and reasoning using the computer‐based Cambridge Brain Sciences battery. Assessment of 24‐hour BP was performed using an automated, ambulatory BP monitoring device (SpacelabsModel 90207). Ambulatory BP was measured every 30 minutes between 6am and 10pm, and hourly between 10pm and 6am. We employed hierarchical regression models to examine associations between 24‐hour systolic BP and cognition. Further, we conducted ANCOVAs exploring dose‐response relationships by stratifying our sample using clinical cut‐offs for normal (≤120 mmHg, n = 52), preclinical (121 to 135 mmHg, n = 119), and hypertensive (>135 mmHg, n = 59) BP. All analyses were adjusted for age, sex, MoCA, years of education, and diagnosis of diabetes and/or hypertension. Result In our sample, 24‐hour systolic BP was negatively associated with reasoning scores (unstandardized B [95% CI] = ‐0.008 [‐0.016 to ‐0.001], R2Change = 0.016, p = 0.028). The dose‐response analysis revealed a main group effect (F[2,221] = 3.6, p = 0.029, ηp2= 0.032), with post‐hocpairwise comparisons indicating that individuals with normal BP levels outperformed those with preclinical (mean difference [95% CI] = 0.280 [0.068 to 0.492], p = 0.010), and hypertensive (0.265 [0.021 to 0.508], p = 0.034) BP levels. The tasks adopted to assess reasoning targeted specifically grammatical reasoning, conflict resolution, and deductive reasoning, which fall under the overall scope of executive function tasks. No other relevant associations or interactions were found. Conclusion In this sample of older adults with SCD, 24‐hour systolic BP levels above optimal clinical parameters were negatively associated with cognitive reasoning performance. Future research should investigate whether interventions that target BP control could mitigate impairment on reasoning performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".