Effects of Foot Dry Cupping in Diabetic Distal Polyneuropathy: A Pilot Controlled Clinical Trial
Bibliographic record
Abstract
Background: Distal polyneuropathy is a common complication of diabetes mellitus with a considerable negative impact on the quality of life. This study aimed to evaluate the effect of dry cupping on distal polyneuropathy in diabetic patients. Methods: This controlled clinical trial was performed on 34 patients with diabetic polyneuropathy (DPN) for eight weeks. The non-invasive dry, fixed cupping therapy was performed on the sole of the right foot in the patients three times a week for 10 minutes, and the left foot of the same patient was considered as a control. The severity of diabetic neuropathy was measured using the modified Toronto Clinical Neuropathy Score (mTCNS), and the symptom and sensory test scores were determined. Results: Twenty patients (40 feet) completed the study. There was a significant difference between the control foot and the treated foot in terms of the mTCNS after four and eight weeks (P values=0.004 and 0.001, respectively), in terms of the sensory test scores after four and eight weeks (P values=0.007 and 0.005, respectively), and in terms of the symptom scores after eight weeks (P value=0.002). Conclusion: For the first time, this study demonstrated that cupping therapy might be effective as a complementary treatment in alleviating the symptoms of DPN, although understanding the underlying mechanism requires further investigation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".