Alpha lipoic acid combined with epalrestat: a therapeutic option for patients with diabetic peripheral neuropathy
Bibliographic record
Abstract
Background: Alpha lipoic acid (ALA), a type of antioxidant, is used in combination with epalrestat in the treatment of diabetic peripheral neuropathy (DPN). However, whether combined treatment is superior to epalrestat monotherapy is controversial. Methods: We conducted a systematic search of PubMed, Cochrane Library and Chinese databases to identify all randomized controlled trials (RCTs) up to October 31, 2017. Data were extracted to evaluate methodological quality and analyzed using Review Manager 5.3.0 software. Results: Twelve studies were included. Compared to epalrestat monotherapy, ALA 600 mg/d once a day (qd) combined with epalrestat 50 mg three times a day (tid) augmented the total effectiveness rate (14 days – risk ratio [RR]: 1.40, 95% CI: 1.16–1.69, P =0.0005; 28 days – RR: 1.48, 95% CI: 1.27–1.72, P <0.00001); at the same, it could improve the median motor nerve conduction velocity (MNCV) and sensory nerve conduction velocity (SNCV), peroneal MNCV, and SNCV after 14, 21, and 28 days of treatment and could reduce the Toronto Clinical Scoring System (TCSS) (weighted mean difference [WMD]: -1.60, 95% CI: (-2.91, -0.29), P =0.02) and Total Symptom Score (TSS) (WMD: -0.93, 95% CI: -1.27, -0.60, P <0.00001) after 21 days of treatment. The treatment strategy of ALA 300 mg/d qd combined with epalrestat 50 mg tid had the same effects in regard to the total effectiveness rate (RR: 1.37, 95% CI: 1.18–1.59, P <0.0001), median MNCV (WMD: 6.12, 95% CI: 5.04, 7.20, P =0.00001), median SNCV (WMD: 6.70, 95% CI: 5.75, 7.65, P =0.00001), peroneal MNCV (WMD: 6.68, 95% CI: 5.82, 7.55, P =0.00001), and peroneal SNCV (WMD: 4.27, 95% CI: 3.34, 5.20, P =0.00001) after 28 days of treatment. Conclusion: ALA combined with epalrestat is an effective option for DPN patients. Future large-sample RCTs should be conducted to further confirm this finding. Keywords: alpha lipoic acid, diabetic peripheral neuropathy, epalrestat, meta-analysis
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".