Clinical observation of combination therapy for the treatment of diabetic peripheral neuropathy
Bibliographic record
Abstract
Objective To explore the clinical efficacy of combination therapy( Shenqi hypoglycemic particles,mecobalamin and moxibustion) for the treatment of diabetic peripheral neuropathy( DPN). Methods Sixty-nine cases of DPN were randomly divided into two groups. With basic treatment,the Shenqi hypoglycemic particles( 3g per time,3 times per day),mecobalamin tablets( 500 μg per time,3 times per day,oral administration) and moxibustion( at Zusanli,Taixi Sanyinjiao,5 to 7 min per acupoint until slight red of skin,three times per week) were applied in the treatment group. With basic treatment,oral administration of Shenqi hypoglycemic particles and mecobalamin tablets was applied with identical dose as treatment group. Three months were required in the treatment. The clinical efficacy of two groups and changes of Toronto Clinical Scoring System( TCSS) and neural conductive velocity( NCV) before and after treatment were observed. Results There was statistical significance on total effective rate between two groups( P 0. 01). Compared before treatment,the TCSS was significantly decreased after the treatment in both groups( P 0. 01),and the difference in the treatment group was higher than that in the control group with a statistical significance( P 0. 01). After the treatment,the sensory NCV of median nerve and common peroneal nerve as well as motor NCV of median nerve and superficial peroneal nerve were all increased in both groups,which had statistical significance compared before the treatment( P 0. 01). The NCV difference in treatment group was high than that in the control group with a statistical significance( P 0. 01). Conclusion The combined therapy of Shenqi hypoglycemic particles, mecobalamin and moxibustion has superior efficacy to treatment of oral administration for DPN.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".