Sural sensory action potential identifies diabetic peripheral neuropathy responders to therapy
Bibliographic record
Abstract
Identifying patients with diabetic peripheral neuropathy (DPN) amenable to therapy is a challenge. To determine whether the amplitude of the sural sensory nerve action potential (sural SNAP) reflects the severity of DPN, an analysis was performed on 205 patients with DPN, identified by an abnormal vibration detection threshold (VDT), who were enrolled in a multinational clinical trial investigating ruboxistaurin (RBX) mesylate. Nerve conduction velocity and response amplitude and latency were measured and compared. VDT was significantly lower in those with preserved sural SNAPs (n = 128) than in those in whom they were absent (n = 77; 21.5 vs. 22.7 JND units, P = 0.002). Thus, preserved sural SNAP denoted less severe DPN. Logistic regression analyses evaluating baseline characteristics, HbA(1c), and baseline symptom scores identified only DPN duration as a factor that might contribute to the presence of sural SNAP (P = 0.004; OR = 0.896). For patients with abnormal VDT, preserved sural SNAP identifies a patient population with less severe DPN who may respond to therapeutic intervention in clinical trials.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".