Effects of evening primrose oil on treating painful diabetic neuropathy: a randomized, double-blind, clinical trial
Bibliographic record
Abstract
OBJECTIVES: Diabetic neuropathy results in chronic pain. Traditional treatments often offer limited relief, prompting the exploration of alternative therapies like Evening Primrose Oil (EPO). This study aimed to assess the efficacy of EPO in the treatment of painful diabetic neuropathy. METHODS: In this interventional clinical trial, Patients were randomly assigned to three groups. Group A, consisted of 24 patients, received 1,000 mg of EPO soft gel capsules every 12 h. Group B, consisted of 21 patients, received 1,000 mg of EPO soft gel capsules daily. Group C, also with 21 patients, was divided so that half of the patients received placebo capsules daily and the other half every 12 h. After 4 weeks, patients returned, and questionnaires were completed. Statistical analysis of the data was conducted using SPSS version 25. RESULTS: Groups A and B showed significant reductions in visual analog scale (VAS) pain scores, with Group A achieving the most improvement (mean pre-test: 5.96; post-test: 4.63). Analysis of covariance (ANCOVA) revealed significant differences in post-intervention scores (p<0.001) for VAS and Neuropathy total symptom score-6 (NTSS-6), indicating effective interventions. Treatment A was more effective than Treatment B for reducing pain (VAS mean difference= -0.52; p=0.044) and McGill Pain Questionnaire (MPQ) scores (mean difference= -9.56; p<0.001). CONCLUSIONS: EPO could serve as a valuable alternative therapy for managing painful diabetic neuropathy with fewer side effects than traditional treatments. Further research is warranted to validate these results and explore EPO treatment long-term efficacy and safety.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".