Can Finnish Sauna Bathing Induce Heat Acclimation in Adults with Stable Coronary Artery Disease?
Bibliographic record
Abstract
Introduction Extreme heat is associated with a greater risk of mortality that particularly affects older adults with cardiovascular disease (CVD). Regular heat exposure induces an adaptation of thermoregulatory mechanisms (acclimation) that may alleviate thermal and/or cardiac strain during subsequent heat exposure. However, limited research has examined practical heat acclimation protocols that could be recommended to vulnerable populations, such as adults with CVD. The objective of this study was to test the hypothesis that 8 weeks of Finnish sauna bathing reduces core temperature and heart rate and increases sweating during heat exposure. Method 14 participants (11 men/3 women, 63 ± 5 years, 28.7 ± 3.8 kg/m 2 ) with stable coronary artery disease participated in an 8‐week Finnish sauna intervention (4 sessions/week, 20 to 30 min/session, at ~80°C, 20% humidity). Core temperature (ingestible telemetric pill), heart rate (Polar watch), and sweat rate (change in nude body weight) were measured during the first and last sauna sessions. Results Resting core temperature prior to the first sauna session was 37.4 ± 0.4°C, compared to 37.1 ± 0.3°C prior to the last session (p= 0.04). Core temperature at the end of sauna bathing did not differ between the first (37.77 ±0.34°C) and the last (37.59 ± 0.31°C, p=0.20) sessions. Heart rate at the end of sauna bathing was greater during the last (90 ± 17 bpm) compared to first (85 ± 16 bpm, p=0.13) sessions. Sweat rate was greater during the last sauna session (first session: 8.6 ± 5.9 mL/min vs. last session: 5.1 ± 3.0 mL/min, p<0.01). Conclusion Eight weeks of Finnish sauna bathing reduces resting core temperature and increases sweat rate during heat exposure in adults with stable coronary artery disease. However, these adaptations did not translate into reduced thermal and cardiac strain during heat exposure.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".