Association Between Blood Pressure Variability With Dementia and Cognitive Impairment: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Research links high blood pressure variability (BPV) with stroke and cerebrovascular disease, however, its association with cognition remains unclear. Moreover, it remains uncertain which BP-derived parameter (ie, variability or mean) holds more significance in understanding vascular contributions to cognitive impairment. We searched PubMed, Embase, PsycINFO, and Scopus and performed a meta-analysis of studies that quantified the association between resting BPV with dementia or cognitive impairment in adults. Two authors independently reviewed all titles, abstracts, and full-texts and extracted data, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-Analysis of Observational Studies in Epidemiology guidelines. Study quality was assessed using the (modified) Newcastle-Ottawa Scale. A multilevel meta-analysis was used, which included effect sizes for both BPV and mean BP, with a combined end point of dementia or cognitive impairment as primary outcome. In the primary analysis, 54 effect sizes were extracted from 20 studies, with a total analytical sample of n=7 899 697. Higher systolic BPV (odds ratio [OR], 1.25 [95% CI, 1.16–1.35]), mean systolic pressure (OR, 1.12 [95% CI, 1.02–1.29]), diastolic BPV (OR, 1.20 [95% CI, 1.12–1.29]), and mean diastolic pressure (OR, 1.16 [95% CI, 1.04–1.29]) were associated with dementia and cognitive impairment. A direct comparison showed that mean BP effect sizes were less strong than BPV effect sizes (OR, 0.92 [95% CI, 0.87–0.97], P <0.01), indicating that the relative contribution of BPV exceeded that of mean BP. Methodological and statistical heterogeneity was high. Secondary analyses were less consistent as to whether BPV and mean BP were differentially associated with dementia subtypes and cognitive domains. Future studies are required to investigate BPV as a target for dementia prevention.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.001 |
| Bibliometrics | 0.000 | 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".