Effect of a treatment with auriculartherapy in pain, functionality and mobility of adults with chronic low back pain
Bibliographic record
Abstract
Introduction: Low back pain affects much of the world population and may cause, in addition to pain, decrease of functional capacity and lumbar mobility. One way to treat low back pain is the auricular acupuncture technique that uses the ear to treat various diseases. Objectives: To verify if there was a reduction of pain symptoms and increase of the functionality and lumbar mobility in individuals with chronic nonspecific low back pain after having undergone a treatment with auriculartherapy, and see if there was a difference between the intervention performed with needles and seeds. Methods: Randomized clinical trial with participants from 18 to 60 years with chronic nonspecific low back pain for at least three months, of both sexes, divided into three groups, needle (n = 8), seed (n = 8) and control (n = 6). The needle and seed groups received four sessions with auriculartherapy, one per week, all in the same auricular points, and the control group received no intervention until the end of treatment with the experimental groups. For the evaluation of pain variables, functionality and lumbar mobility, it was used in all groups the instruments Visual Analogue Scale, Quebec Back Pain Disability Scale Questionnaire, Sit-to-Stand-Test and Schober Test in the first week and after four weeks. The tests used for data analysis were Two Way ANOVA repeated measures, paired t-test and ANOVA with Bonferroni’s post hoc, with significance level of 5% (p0.05). Results and discussion: It was found that there was a significant difference for the EVA variables (p=0.001), QILQ (p=0.003) and TSP (p=0.033), indicating that there was a decrease in pain and an increase in functionality after treatment in the experimental groups, and no difference was found in the lumbar mobility after treatment. No difference between the treatment carried out with needles and seeds (p=0.641), demonstrating that both treatments were favorable for the reduction of pain without superiority of the two. Conclusion: Auriculotherapy, both with needles and with seeds, is an intervention that has proved beneficial for reduction of chronic low back pain and increasing function in patients with chronic nonspecific 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".