Efficacy of Vitamin B1, B6, and B12 Forte Therapy in Peripheral Neuropathy Patients
Bibliographic record
Abstract
Background: Peripheral neuropathy can be caused by diabetes mellitus, nutritional deficiencies, entrapment or Carpal Tunnel Syndrome (CTS), and idiopathic.Objective: To determine the therapeutic efficacy of Vitamin B1, B6, and B12 forte in relieving symptoms of peripheral neuropathy.Methods: This was pre- and post-experimental study involving patients with moderate peripheral neuropathy (Toronto Clinical Neuropathy Score [TCNS] ≥6 and Michigan Neuropathy Screening Instrument [MNSI] ≥7) taken from outpatient neurological clinic of Dr. Kariadi Hospital, Semarang. The patient was prescribed Vit B1 100 mg, B6 100 mg, and B12 5000 mcg once daily for 2 months. Evaluation of the numerical pain rating scale in the form of VAS and Total Symptom Score (TSS) was conducted at the first and second month. The VAS score difference test was conducted with the Wilcoxon test and TSS with the Post Hoc test and considered significant if p <0.05.Results: There were 30 patients aged 18 - 65 years, consisted of 70% female and 30% male. The etiology of peripheral neuropathy were idiopathic (40%), CTS (26.7%), DM (23.3%), and HNP (10%). There were significant differences of the VAS scale and TSS at every evaluations.Conclusion: Administration of VitB1, B6, and B12 forte relieved symptoms of moderate peripheral neuropathy with improvement of VAS and TSS scores
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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 | 0.000 | 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) | 0.001 | 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".