Cerebrovascular reactivity metrics as predictors of cognitive performance in healthy ageing: insights from transcranial colour-coded ultrasound
Bibliographic record
Abstract
INTRODUCTION: This study was designed to investigate the utility of cerebrovascular reactivity (CVR) metrics, derived from transcranial colour-coded Doppler ultrasound (TCCD). Three main CVR metrics were examined as potential markers for cerebrovascular risk associated with mild cognitive impairment (MCI), a stage between normal cognition and dementia. METHODS: We investigated 122 eligible, stroke-free, healthy, community-based Chinese adults (mean age, 65.34 ± 6.86 years). Cognitive performance was assessed using the validated Hong Kong version of the Montreal Cognitive Assessment. On a scale of 0-30, participants with low scores < 26 (modelled according to level of education) were designated to have a mild neurocognitive disorder or MCI. Following the measurement of cerebrovascular conductance (CVC) derived from cerebral blood flow and mean arterial pressure, three physiologic CVR metrics were assessed. The CVR assessments were based on restricted 30 s breath-holding, 60 s hyperventilation, and an unrestricted breath-holding index (BHI), respectively quantified using transcranial colour-coded Doppler ultrasound. The predictabilities and associations between CVR metrics, haemodynamic parameters, and cognitive performance were statistically investigated. RESULTS: Using TCCD, BHI emerged as the most accurate and robust metric of CVR for predicting mild cognitive disorders [AUC 0.827 (95% CI 0.725, 0.930)] and independently predicted overall cognitive performance, highlighting its clinical value for early identification of at-risk individuals. The three CVR metrics outperformed CVC in predicting mild cognitive impairment and were distinctively correlated. Although CVR measures by breath-holding and BHI were closely related (r = 0.704, 95% CI 0.598, 0.786, p < 0.001), Bland-Altman analysis revealed that they are not interchangeable, indicating the importance of metric selection for accurate cerebrovascular assessment. CONCLUSION: The BHI, derived from simple and clinically tolerable methods, demonstrates clear potential to enhance the prediction and early identification of vascular cognitive impairment in healthy adults. By leveraging insights from cerebral haemodynamics, TCCD-based cerebrovascular risk screening may enable more effective and targeted interventions, ultimately contributing to better long-term cognitive health outcomes.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".