Peripheral Microvascular and Endothelial Dysfunction as Predictors of Cognitive Decline and Small Vessel Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Endothelial and microvascular dysfunction play a central role in the pathogenesis of both cardiovascular and neurodegenerative disorders. However, whether impaired peripheral endothelial function independently predicts cognitive decline, cerebral small-vessel disease (SVD) progression, or stroke remains uncertain. Methods: We conducted a systematic review and meta-analysis of prospective cohort studies assessing the prognostic value of non-invasive peripheral endothelial tests—flow-mediated dilation (FMD), peripheral arterial tonometry (PAT/EndoPAT), and sublingual microcirculatory imaging—for cognitive or cerebrovascular outcomes. Databases (PubMed, Embase, Scopus, Web of Science) were searched from inception through 30 September 2025. Study quality was appraised using the Newcastle–Ottawa Scale (NOS), and evidence certainty was graded via GRADE. Random-effects models (DerSimonian–Laird or REML) pooled hazard ratios (HRs) using inverse-variance weighting. PROSPERO-registered (CRD42025211876). Results: Fifteen prospective cohorts (n = 13,972 participants; median follow-up 4.3 years) met inclusion criteria. Across all modalities, impaired endothelial or microvascular function predicted cognitive decline, SVD progression, or cerebrovascular events (pooled HR = 1.72, 95% CI 1.38–2.14, p < 0.001; I2 = 57%). Subgroup analyses confirmed consistent associations for FMD (HR = 1.59, 95% CI 1.27–1.98) and PAT/EndoPAT (HR = 1.84, 95% CI 1.40–2.41). Evidence certainty was rated moderate-to-high according to GRADE. Conclusions: Peripheral endothelial dysfunction, measured by validated non-invasive techniques, independently predicts future cognitive and cerebrovascular events. These findings support the concept of a vascular–neural continuum, suggesting that endothelial health represents a modifiable biomarker for early neurovascular risk stratification. Routine assessment of endothelial function may help identify high-risk individuals and guide preventive interventions aimed at preserving brain and vascular health.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".