Tramadol Iontophoresis Added to Treatment of Knee Osteoarthritis
Bibliographic record
Abstract
Objective: The objective of the present study was to investigate whether tramadol iontophoresis added to therapy is superior to the therapy methods alone (transcutaneous electrical nerve stimulation (TENS), hot pack, ultrasound, and exercise therapy) in patients with knee OA. Materials and Methods: A total of 72 patients who admitted to the outpatient clinic of Physical Medicine and Rehabilitation were included in this study. The diagnosis was based on the American College of Rheumatology (ACR) criteria for knee OA. The patients were randomly separated into two groups. Group 1 received physical therapy and Group 2 received tramadol iontophoresis in addition to the therapy for a period of two weeks. Patients were evaluated according to pain and functional capacity assessed using visual analogue scale (VAS) and Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) before therapy and following the 10th session, and at 1 and 3 months. Results: The mean age and duration of the knee pain were 58.53±8.38, 5.00±2.66 years in the control group and 58.15±7.70, 4.71±2.70 years in the tramadol iontophoresis group. There were no significant differences between groups in the mean age and duration of the knee pain, body mass index (BMI), VAS and WOMAC scores before therapy. Following the 10th session, and after 1 and 3 months, VAS and WOMAC scores were significantly decreased in both groups when compared with the baseline values (p
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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 | 0.000 |
| 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 | 0.000 | 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".