Clinical Significance of the Double-Peak Sensory Response in Nerve Conduction Study of Normal and Diabetic Patients
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to understand the meaning of the double-peak responses in digital nerve conduction study in normal and diabetic patients. DESIGN: This was a cross-sectional and correlative study. Sixty healthy subjects (10 people per decade from 20 to 79 yrs of age; 26 men; mean age, 48 yrs) and 60 diabetic patients (10 people per decade from 22 to 79 yrs of age; 36 men, mean age, 53 yrs) were included. The composite score of the nerve conduction study was obtained. Orthodromic sensory nerve conduction studies were performed on the median nerves using submaximal stimulation. The latencies and amplitudes of first and second peaks were measured. The Toronto clinical scoring system for diabetic neuropathy was applied to all diabetic patients. RESULTS: The first and second peak latencies of both 3- and 4-cm interpeak distance in diabetic patients were significantly increased compared with those of age-matched control subjects (P < 0.05). The correlation between the Toronto clinical scoring system and first and second peak latency and amplitude were significantly high, and the correlation between the composite score and first and second peak latency and amplitude was also related. CONCLUSIONS: The double-peak response represents the far distal nerve pathophysiology. The authors suspect that they will find an increasing role in diagnosing the peripheral neuropathy, which starts at the distal nerve in centripetal pattern.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".