Evaluation of Efficacy of Neuro Muscular Electrical Stimulation and Electro Acupuncture in Improving the Pain and Disability in Patients with the Lumbar Degenerative Intervertebral Disk Disease
Bibliographic record
Abstract
Background: Chronic low back pain (CLBP) due to the degenerative intervertebral disk diseases is one of the most common musculoskeletal conditions in contemporary societies. A variety of pharmacological, non-pharmacological and surgical options is available for treatment of CLBP. The use of non-pharmacological methods have drastically increased in recent years, offering fewer complications and expenses. This study was conducted to compare the efficacy of the neuromuscular electrical stimulation (NMES) and electro acupuncture (EAP) with exercise therapy alone in patients with chronic low back pain. Materials and Methods: This was a randomized case-controlled clinical trial. Sixty patients with CLBP were randomly assigned to 3 groups (20 cases each) of the EAP with exercise therapy, NMES with exercise therapy, and exercise therapy only. Severity of pain and disability improvement were assessed using the visual analog scale (VAS) and Quebec back pain disability scale respectively. Results: A total of 66 individuals were enrolled, out of which 6 were excluded due to patients’ lack of cooperation. A significant decline in the amounts of Quebec and VAS was observed in the three groups (p<0.001). The pain and disability improvements did not display any significant difference in the NMES or EAP groups compared to the control group. However, the severity of disability and pain in the NMES group were significantly higher than the EAP group (p<0.05). Conclusion: These findings may indicate an almost identical efficacy of exercise therapy alone compared to the combination with electrical stimulation techniques in improving the pain and disability in patients suffering CLBP.
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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".