Age alters cardiac autonomic modulations during and following exercise-induced heat stress in females
Bibliographic record
Abstract
The aim of this study was to examine the effect of natural ageing on heart rate variability during and following exercise-induced heat stress in females. Eleven young (∼24 years) and 13 older (∼51 years), habitually active females completed an experimental session consisting of baseline rest, moderate intensity intermittent exercise (four 15-min bouts separated by 15-min recovery) and 1-hour of final recovery in a hot and dry (35°C, 20% relative humidity) environment. Respiratory and heart rate recordings were continuously logged with 10-min periods analysed at the end of: baseline rest; each of the exercise and recovery bouts; and during the 1-hour final recovery period. Comparisons over time during exercise and recovery, and between groups were conducted via two-way repeated-measures ANCOVAs with rest values as the covariate. During baseline rest, older females exhibited lower heart rate variability compared to young females with similar levels of respiration and most (∼71-79%) heart rate variability measures during repeated exercise and recovery. However, older females exhibited heart rate variability metrics suggestive of greater parasympathetic modulation (greater long axis of Poincare plot, cardiac vagal index; lower low-high frequency ratio) during repeated exercise with lower indices during the latter stage of prolonged recovery (less very low frequency component, Largest Lyapunov Exponent; greater cardiac sympathetic index). The current study documented several unique, age-dependent differences in heart rate variability, independent of respiration, during and following exercise-induced heat stress for females that may assist in the detection of normal heat-induced adaptations as well as individuals vulnerable to heat stress.
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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 | 0.000 | 0.000 |
| 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".