Regular postexercise sauna bathing does not improve heart rate variability: A multi‐arm randomized controlled trial
Bibliographic record
Abstract
Abstract Regular exercise has been shown to increase heart rate variability (HRV) for different populations. Acute and short‐term studies using heat therapy and sauna bathing have also shown HRV improvements. However, long‐term adaptations in HRV to regular exercise and sauna bathing remain unexplored. In this 1:1:1 multi‐arm trial, sedentary participants (n = 38) aged 49 ± 9 years with at least one CVD risk factor were randomly assigned to regular exercise and 15‐min postexercise sauna (EXS), regular exercise only (EXE), or control (CON) group, for an 8‐week intervention. Indices of HRV (RR interval, RMSSD, SDNN, resting heart rate [HR], HRMAX–HRMIN, high frequency power [HFP], and low frequency power [LFP]) were measured before (PRE) and after (POST) the trial. Compared to CON, EXE increased the time‐domain measure of HRMAX–HRMIN (p = 0.003), and elicited significantly smaller decreases in the frequency‐domain measure of LFP (p = 0.022). There were no statistically significant differences between EXS and EXE for any of the HRV indices measured. Eight weeks of regular exercise conferred positive changes in both time‐ and frequency‐domain measures of HRV. However, adding regular sauna bathing postexercise offered no additional benefits to HRV over regular exercise alone.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".