Associations between Cardiovascular Signal Entropy and Cognitive Performance over Eight Years
Bibliographic record
Abstract
In this study, the relationship between non-invasively measured cardiovascular signal\nentropy and global cognitive performance was explored in a sample of community-dwelling older\nadults from The Irish Longitudinal Study on Ageing (TILDA), both cross-sectionally at baseline\n(n = 4525; mean (SD) age: 61.9 (8.4) years; 54.1% female) and longitudinally. We hypothesised that\nsignal disorder in the cardiovascular system, as quantified by short-length signal entropy during\nrest, could provide a marker for cognitive function. Global cognitive function was assessed via Mini\nMental State Examination (MMSE) across five longitudinal waves (8 year period; n = 4316; mean\n(SD) age: 61.9 (8.4) years; 54.4% female) and the Montreal Cognitive Assessment (MOCA) across\ntwo longitudinal waves (4 year period; n = 3600; mean (SD) age: 61.7 (8.2) years; 54.1% female).\nBlood pressure (BP) was continuously monitored during supine rest at baseline, and sample entropy\nvalues were calculated for one-minute and five-minute sections of this data, both for time-series\ndata interpolated at 5 Hz and beat-to-beat data. Results revealed significant associations between BP\nsignal entropy and cognitive performance, both cross-sectionally and longitudinally. Results also\nsuggested that as regards associations with cognitive performance, the entropy analysis approach\nused herein potentially outperformed more traditional cardiovascular measures such as resting heart\nrate and heart rate variability. The quantification of entropy in short-length BP signals could provide\na clinically useful marker of the cardiovascular dysregulations that potentially underlie cognitive\ndecline.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".