Ranirestat Improves Electrophysiologic but not Clinical Measures of Diabetic Polyneuropathy
Bibliographic record
Abstract
Ranirestat, an aldose reductase inhibitor evaluated in several randomised controlled trials (RCTs) in diabetic peripheral neuropathy (DPN). However, to date, no meta-analysis has evaluated the efficacy and safety of ranirestat in DPN. We undertook this meta-analysis to address this knowledge gap. Detailed search of electronic databases for RCTs published till December 2021 was done at Cochrane register, Medline, PubMed, Embase, clinicaltrials.gov, ctri.nic.in, global health and Google Scholar using the Boolean search strategy: ((ranirestat) OR (aldose reductase inhibitor)) AND ((diabetes) OR (“diabetes mellitus”)). The primary outcome was to evaluate changes in nerve conduction velocities (NCV) of different nerves. The secondary outcomes were to evaluate alterations in amplitudes, F-wave latencies of nerves, modified Toronto Clinical Neuropathy Score (mTCNS) and adverse events. Data from 5 studies involving 1461 patients with DPN was analysed to establish the impact of ranirestat (20-40 mg/day) as compared to placebo on different electrophysiologic outcomes over a median follow-up of 52 weeks. Patients receiving ranirestat had significantly greater improvement in proximal median sensory NCV [MD 0.77 m/s (95%CI: 0.50–1.05); P < 0.01; I 2 = 26%], distal median sensory NCV [MD 0.91 m/s (95%CI: 0.87–0.95); P < 0.01; I 2 = 0%], median motor NCV [MD 0.63 m/s (95%CI: 0.60–0.66); P < 0.01; I 2 = 0%], tibial motor NCV [MD 0.46 m/s (95%CI: 0.43–0.49); P < 0.01; I 2 = 0%] and peroneal motor NCV [MD 0.80 m/s (95%CI: 0.66–0.93); P < 0.01; I 2 = 0%]. mTCNS was not significantly different among groups. Treatment-emergent adverse events [risk ratio (RR) 0.85 (95%CI: 0.63–1.14); P = 0.28; I 2 = 0%] and severe adverse events [RR 1.35 (95%CI: 0.86–2.11); P = 0.20; I 2 = 0%] were comparable across study groups. In people with established DPN with long-standing diabetes, ranirestat is safe and effective in improving electrophysiologic but not clinical 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| 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".