Comparison of the Effect of Gabapentin and Evening Primrose Oil on Peripheral Neuropathy Pain in Patients with Type 2 Diabetes
Bibliographic record
Abstract
Background and Objective: Neuropathic pain is one of the common, important, and irritating complications in diabetes.Despite the importance of this pain, there is still no effective treatment for that.The aim of this study was to determine the effect of evening primrose oil and gabapentin on neuropathic pain in patients with type 2 diabetes.Materials and Methods: This triple-blind clinical trial was performed on 70 patients with diabetic neuropathy who obtained score 2 from the Michigan Questionnaire and referred to the Department of Endocrinology at Khayyam clinic affiliated to Hakim Hospital in Neyshabour from December 2017 to May 2018.The participants were divided into two groups of 35 people.The intervention group was treated with a capsule of evening primrose oil orally (1000 mg) twice daily for three months and gabapentin (300 mg) daily.On the other hand, the control group was treated with gabapentin (300 mg) and placebo.The neuropathy pain severity was measured before and after the end of three-month intervention using Michigan and McGill Pain Questionnaires.Data analysis was performed in SPSS software (version 21) through Fisher's exact test, ANCOVA, multilevel logistic regression, Mann Whitney U test, Kolmogorov-Smirnov test, and the Chi-square tests.P-value less than 0.05 was considered statistically significant.Results: According to the results obtained from the McGill questionnaire, the mean scores of neuropathy before the intervention were obtained at 10.12±0.57and 9.85±0.65 in the intervention and control groups, respectively.However, the mean scores of neuropathy after the intervention were estimated at 6.18±0.48 and 8.31±0.60 in the intervention and control groups, respectively, which was statistically significant (P<0.02).Conclusion: Evening primrose oil is effective in reducing neuropathic pain in type 2 diabetic patients.Therefore, this can be a supplementary treatment for reducing pain associated with diabetic neuropathy.
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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) | 0.000 | 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) | 0.002 | 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".