Effect of Adding Taurine to Gabapentin on Toronto Clinical Neuropathy Score in Patient with Diabetic Neuropathy
Bibliographic record
Abstract
Diabetic neuropathy is a type of nerve damage that can occur in patients with diabetes mellitus. High blood glucose can injure nerves throughout the body. Diabetic neuropathy most often damages nerves in the legs and feet causing symptoms like pain and numbness. Taurine has been widely investigated regarding to its properties as a neuroprotective agent, antioxidant, anti-inflammatory in several neurodegenerative diseases. A sample consist of 40 participants enrolled randomly into two groups; group A, 20 patients treated with gabapentin capsules 300 mg once daily at night for 3 consecutive months, and group B, 20 patients treated with gabapentin capsules 300 mg once daily at night plus taurine 1 g thrice daily for 3 consecutive months. Adding taurine in combination with gabapentin significantly improves numbness, tingling, and temperature when compared with gabapentin alone. As well as, has a highly significant improving on ataxia. Taurine is better in improving insulin sensitivity due to lowering HbA1c level significantly, beside a medium degree in increasing insulin secretion; as evidenced by decreased fasting serum glucose, decreased HbA1c significantly, increased insulin level significantly, and increased C-peptide level. The conclusion of this study, adding taurine to patients with diabetic neuropathy has a significant improving effect on Toronto clinical neuropathy score by alleviating signs and symptoms, and improving insulin sensitivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 teacher head, 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".