Acetyllevocarnitine Hydrochloride for the Treatment of Diabetic Peripheral Neuropathy: A Phase 3 Randomized Clinical Trial in China
Bibliographic record
Abstract
Diabetic peripheral neuropathy (DPN) is a highly prevalent chronic complication in type 2 diabetes (T2D) for which no effective treatment is available. In this multicenter, randomized, double-blind, placebo-controlled phase 3 clinical trial in China, patients with T2D with DPN received acetyllevocarnitine hydrochloride (ALC; 1,500 mg/day; n = 231) or placebo (n = 227) for 24 weeks, during which antidiabetic therapy was maintained. A significantly greater reduction in modified Toronto clinical neuropathy score (mTCNS) as the primary end point occurred in the ALC group (-6.9 ± 5.3 points) compared with the placebo group (-4.7 ± 5.2 points; P < 0.001). Effect sizes (ALC 1.31 and placebo 0.85) represented a 0.65-fold improvement in ALC treatment efficacy. The mTCNS values for pain did not differ significantly between the two groups (P = 0.066), whereas the remaining 10 components of mTCNS showed significant improvement in the ALC group compared with the placebo group (P < 0.05 for all). Overall results of electrophysiological measurements were inconclusive, with significant improvement in individual measurements limited primarily to the ulnar and median nerves. Incidence of treatment-emergent adverse events was 51.2% in the ALC group, among which urinary tract infection (5.9%) and hyperlipidemia (7.9%) were most frequent.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".