A Randomized Controlled Trial on the Effectiveness of Mild Water-filtered Near Infrared Whole-body Hyperthermia as an Adjunct to a Standard Multimodal Rehabilitation in the Treatment of Fibromyalgia
Bibliographic record
Abstract
OBJECTIVES: To evaluate whether mild water-filtered near infrared whole-body hyperthermia (NI-WBH) produces an additional benefit when applied as an adjunct to a standard multimodal rehabilitation (MR) compared with MR only in patients with fibromyalgia (FM). METHODS: One hundred thirty-nine patients of a German inpatient rehabilitation hospital meeting the ACR 1990 criteria for FM were randomly allocated to NI-WBH (heating-up to 38.1 degrees C body core temperature followed by a 15 min heat retention period) and MR or MR only, twice a week over 3 weeks. Main outcome measures were affective and sensory pain assessed by a German version of the McGill Pain Questionnaire, measured at baseline, postintervention, 3 and 6 months postintervention and analyzed by intention to treat. RESULTS: Repeated measures analysis of covariance showed significant differences between groups for both primary outcome measures in favor of NI-WBH and MR compared with MR only (P<0.001 for affective pain, P=0.001 for sensory pain). Secondary analyses on pain intensity, FM-related quality of life and tender point assessment yielded similar results. Moderate effect sizes were observed for all outcome measures considered (range, 0.41 to 0.75). NI-WBH related side effects were observed in 14 of 69 participants (20%) but all disappeared in less than 30 minutes. DISCUSSION: The study indicates that NI-WBH is a worthwhile adjunct to MR in the treatment of FM.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 | 0.003 |
| 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".