The Efficacy of Thermotherapy and Cryotherapy on Pain Relief in Patients with Acute Low Back Pain, a Clinical Trial Study
Bibliographic record
Abstract
INTRODUCTION: Acute low back pain is one of the most common health problems especially in industrialized countries where 75 per cent of the population develop it at least once during their life. This study examined the efficacy of thermotherapy and cryotherapy, alongside a routine pharmacologic treatment, on pain relief in patients with acute low back pain referring an orthopedic clinic in Shahrekord, Iran. MATERIALS AND METHODS: This clinical trial study was conducted on 87 patients randomly assigned to three (thermotherapy and cryotherapy as intervention, and naproxen as control) groups of 29 each. The first (thermotherapy) group underwent treatment with hot water bag and naproxen, the second (cryotherapy) group was treated with ice and naproxen, and the naproxen group was only treated with naproxen, all for one week. All patients were examined on 0, 3(rd), 8(th), and 15(th) day after the first visit and the data gathered by McGill Pain Questionnaire. The data were analyzed by SPSS software using paired t-test, ANOVA, and chi-square. RESULTS: In this study, mean age of the patients was 34.48 (20-50) years and 51.72 per cent were female. Thermotherapy patients reported significantly less pain compared to cryotherapy and control (p≤0.05). In thermotherapy and cryotherapy groups, mean pain in the first visit was 12.70±3.7 and 12.06±2.6, and on the 15(th) day after intervention 0.75±0.37 and 2.20±2.12, respectively. CONCLUSION: The results indicated that the application of thermo-therapy and cryotherapy accompanied with a pharmacologic treatment could relieve pain in the patients with acute low back pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".