Effect of thermal therapy and exercises on acute low back pain: a protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Low back pain (LBP) is the first cause of years lived with disability worldwide. This is due to the development of chronic pain. Thus, it is necessary to identify the best therapeutic approaches in the acute phase of LBP to limit the transition to chronic pain. Superficial heat presents the highest level of evidence for short-term reduction in pain and disability in acute LBP. Physical activity is also recommended to avoid transition to chronic LBP, but there is a lack of evidence to determine its effect to reduce acute LBP. Also, the long-term effects of these interventions are unknown. This is a protocol for a randomized controlled trial (RCT) to determine the short and long-term effects of wearable continuous low-level thermal therapy, in combination with exercises or not, on disability and pain. METHODS/DESIGN: Sixty-nine participants with acute LBP will be randomly assigned to one of three intervention programs: 1) thermal therapy, 2) thermal therapy + exercises, and 3) control. The interventions will be applied for 7 continuous days. The primary outcome will be disability and secondary outcomes will be pain intensity, pain-related fear, self-efficacy, number of steps walked and perception of change. The evaluators will be blinded to the interventions, and participants will be blinded to other groups' interventions. Primary and secondary outcomes will be compared between intervention groups. DISCUSSION: This study will provide new evidence about acute LBP treatments, to limit transition to chronicity. This will be the first study to measure the long-term effects of wearable continuous low-level thermal therapy, combined or not to exercises. TRIAL REGISTRATION: This RCT has been retrospectively registered on ClinicalTrials.gov ( NCT03986047 ) on June 14th, 2019.
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 | 0.076 | 0.062 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.071 | 0.013 |
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".