Influence of Age on Linear and Nonlinear Measures of Autonomic Cardiovascular Modulation
Bibliographic record
Abstract
BACKGROUND: Age has been identified as an independent risk factor for cardiovascular diseases. In addition, autonomic imbalance toward sympathetic preponderance has been shown to facilitate the occurrence of heart disease. Here, we aimed to assess autonomic modulation of cardiovascular parameters during normal ageing applying well-established linear and novel nonlinear parameters. METHODS: Linear and nonlinear measures of heart rate variability and complexity as well as measures of QT interval variability and baroreflex sensitivity were obtained from a total of 131 healthy, medication-free participants from a continuous age range between 20 and 90 years, who were allocated to three different age groups. RESULTS: Heart rate variability and complexity significantly decreased with age, while regularity of heart rate time series increased. In addition, QT interval variability linearly increased with age, while baroreflex sensitivity showed a pronounced decrease. Overall, concerning effects of ageing, linear and nonlinear parameters showed equal differentiation between groups. CONCLUSION: These data indicate a shift of autonomic balance toward sympathetic predominance in higher age groups, limiting the reactiveness of the cardiovascular system to adjust to different demands and increasing the risk for developing tachyarrhythmias.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".