Far-infrared saunas for treatment of cardiovascular risk factors: summary of published evidence.
Bibliographic record
Abstract
OBJECTIVE: To review the literature about the health benefits of far-infrared sauna (FIRS) use. QUALITY OF EVIDENCE: A search of Web of Science, EBSCO, Ovid MEDLINE, Ovid HealthSTAR, and EMBASE using the terms far-infrared and sauna, refined by limiting the search to studies of humans published in English, yielded 9 relevant papers (level I or level II evidence). MAIN MESSAGE: Far-infrared saunas are approved by the Canadian Standards Association and are sold to the public. The manufacturers claim numerous health benefits; however, the published evidence to substantiate these claims is limited. Four papers support the use of FIRS therapy for those with congestive heart failure and 5 papers support its use for those with coronary risk factors. CONCLUSION: There is limited moderate evidence supporting FIRS efficacy in normalizing blood pressure and treating congestive heart failure; fair evidence, from a single study, supporting FIRS therapy in chronic pain; weak evidence, from a single study, supporting FIRS therapy in chronic fatigue syndrome; weak evidence, from a single study, supporting FIRS therapy for obesity; and consistent fair evidence to refute claims regarding the role of FIRSs in cholesterol reduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".