Fluid Loss during Exercise-Heat Stress Reduces Cardiac Vagal Autonomic Modulation
Bibliographic record
Abstract
PURPOSE: Sweat-induced fluid loss during prolonged exercise-heat stress can compromise cardiovascular and thermoregulatory function, although its effects on cardiac autonomic modulation remain unclear. We therefore examined heart rate variability (HRV) and recovery (HRRec), as surrogates of cardiac autonomic modulation, during and after prolonged exercise in the heat with and without fluid replacement. METHODS: Eleven young and healthy men performed 90 min of semi-recumbent cycling in dry heat (40°C; 20% relative humidity) at a fixed rate of metabolic heat production (600 W; ~46% V˙O2peak) followed by 40-min resting recovery without fluid replacement (No-FR; ~3.4% reduction in body mass). On a separate day, participants completed the same protocol with fluid replacement (FR; 500-700 mL timed boluses) to offset sweat losses. Esophageal temperature and ECG were recorded throughout, with measurements analyzed over 10-min averaged epochs during baseline, each 30-min interval during exercise and 20-min interval during recovery. RESULTS: Esophageal temperature and heart rate were elevated in No-FR relative to FR throughout exercise (all P ≤ 0.02). The HRV indices reflecting vagal influence of heart rate including the cardiac vagal index (CVI = log10[16 × SD1 × SD2]) and root-mean-square of successive differences were attenuated throughout exercise relative to baseline in both conditions (all P < 0.05), with the magnitude of the reduction greater in the No-FR condition (all P < 0.05). Further, sample entropy was reduced throughout all time points measured during exercise in the No-FR relative to FR condition (all P ≤ 0.03). CONCLUSIONS: Our unique observations indicate that while prolonged exercise heat stress attenuates the vagal influence and complexity of cardiac rhythms, that reduction is further exacerbated by fluid loss, highlighting the importance of fluid replacement in such conditions.
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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 | 0.001 |
| 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".