Assessment of the Medial Dorsal Cutaneous, Dorsal Sural, and Medial Plantar Nerves in Impaired Glucose Tolerance and Diabetic Patients With Normal Sural and Superficial Peroneal Nerve Responses
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the nerve conduction study (NCS) parameters of the most distal sensory nerves of the lower extremities-namely, the medial dorsal cutaneous (MDC), dorsal sural (DS), and medial plantar (MP) nerves-in diabetic (DM) and impaired glucose tolerance (IGT) patients who displayed normal findings on their routine NCSs. RESEARCH DESIGN AND METHODS: Standard NCSs were performed on healthy control (HC), DM, and IGT groups (N = 147). The bilateral NCS parameters of the MDC, DS, and MP nerves were investigated. The Toronto Clinical Scoring System (TCSS) was assessed for the DM and IGT groups. RESULTS: The mean TCSS scores of the IGT and DM groups were 2.5 ± 2.3 and 2.8 ± 2.2, respectively. No significant differences between the two groups were observed. After adjustment of age and BMI, the DM group showed significant NCS differences in DS and MDC nerves compared with the HC group (P < 0.05). These differences were also exhibited in the left DS of the IGT group (P = 0.0003). More advanced NCS findings were observed in the DM group. Bilateral abnormal NCS responses in these distal sensory nerves were found in 40 and 16% of DM and IGT patients, respectively. CONCLUSIONS: These results showed that the simultaneous assessment of the most distal sensory nerves allowed the detection of early NCS changes in the IGT and DM groups, even when the routine NCS showed normal findings.
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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 | 0.001 |
| 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) | 0.001 | 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".