Acetyl-l-Carnitine to Enhance Nerve Regeneration in Carpal Tunnel Syndrome: A Double-Blind, Randomized, Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Carpal tunnel syndrome is very common. Although surgery is effective in mild and moderate cases, recovery is often incomplete in severe cases. Therefore, adjuvant therapy to improve nerve regeneration in those patients is much needed. Acetyl-L-carnitine has been shown to be effective in other neuropathies. The goal of this study is to test the hypothesis that acetyl-L-carnitine can promote nerve regeneration and improve function in patients with severe carpal tunnel syndrome. METHODS: In this proof-of-principle, double-blind, randomized, placebo-controlled trial, adults with severe carpal tunnel syndrome were randomized to receive 3000 mg/day of acetyl-L-carnitine orally or placebo following carpal tunnel release surgery for 2 months. Outcomes were assessed at baseline and at 3, 6, and 12 months postoperatively. Symptom severity and functional outcomes were assessed using the Boston Carpal Tunnel Questionnaire and a wide range of physiologic and functional outcome measures. Patient safety was monitored by physical examination, blood work, and serum drug levels. The outcomes were analyzed using repeated measure two-way analysis of variance. RESULTS: Twenty patients with similar baseline characteristics were assigned randomly to the treatment or placebo group in a 1:1 ratio. Sixty percent were women with a mean age ± SD of 59 ± 2. The treatment was safe with no major adverse events reported. Although patients in both groups showed improvements postoperatively, there was no significant difference in any of the outcome measures between the groups. CONCLUSION: Although acetyl-L-carnitine was well tolerated, it did not improve nerve regeneration or functional recovery in patients with severe carpal tunnel syndrome. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".