A Study Protocol on the Evaluation of Comparative Efficacy of Waj (Acorus calamus Linn.) versus Pregabalin in Diabetic Peripheral Neuropathy
Bibliographic record
Abstract
Background: Diabetes is a major global health concern in the twenty-first century. The International Diabetes Federation (IDF) estimates that by the end of 2021, complications from diabetes would have killed 747,000 peoples in India. Diabetic peripheral neuropathy (DPN) is a disorder that develops in patients with diabetes (type 1 and type 2) and is not attributable to any other peripheral neuropathy causes. Clinically, it may manifest as burning, tingling, numbness, or neuropathic pain in the foot that tends to get worse at night. DPN frequently results in ulceration, infection, deterioration of the skin, and ultimately amputation. Methods: This study will be conducted as randomized standard-controlled, single-blind trial on 150 DPN subjects with type 2 diabetes by randomly assigned them to two groups (test or standard), where test group will receive two capsules twice (containing 500 mg powder of test drug in each capsule) with water and control group will receive one capsule of pregabalin 75 mg twice. Both groups will be treated for 60 days with 30 days post treatment follow-up addition to their regular anti-diabetic treatment. The subjective parameters of burning, tingling, and pain in the feet will be evaluated every two weeks using the visual analog scale (VAS) and arbitrary scale. Objective parameters, Toronto Clinical Scoring System (TCSS) will be assessed fortnightly along with vibratory perception threshold (VPT), assessed pre and post-treatment. Data will be assessed statistically with appropriate tests.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.067 | 0.010 |
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".