Evaluation of Tibial nerve morphology by high resolution ultrasonography in diabetic patients with clinically suspected diabetic peripheral neuropathy: A cross sectional study
Bibliographic record
Abstract
Background: Diabetic peripheral neuropathy is diagnosed by nerve conduction studies by presence of atypical parameters with respect to amplitude, latency as well as conduction velocity of nerve. In adjunct to current screening modalities, use of ultrasonography for evaluation of peripheral neuropathy in diabetic patients has been advocated as a promising diagnostic tool. The purpose of this study is to evaluate & measure Cross-sectional area of tibial nerve & maximum thickness of nerve fascicles of tibial nerve in diabetic patients with clinical suspicion of diabetic peripheral neuropathy by ultrasonography & its correlation with clinical symptoms, duration of diabetes & HbA1c. Materials and methods: This cross-sectional study was conducted in Mahatma Gandhi Medical College and Research Institute from January 2021 to June 2022 amongst 30 clinically suspected diabetic peripheral neuropathy patients. Results: The mean age, Hb1Ac & duration of diabetes was found to be 67.83, 10.08 & 21.27, with a male predominance (26 males & 4 females). Average Cross sectional area of tibial nerve, maximum thickness of nerve fascicles of tibial nerve & average total Toronto clinical neuropathy score was found to be 23.82 mm2, 0.68 mm & 10.23 respectively. Correlation of duration of diabetes, HbA1c as well as Toronto neuropathy score against average Cross sectional area of tibial nerve, average maximum thickness of nerve fascicles of tibial nerve in both limbs was found to be statistically significant with a strong positive correlation. Conclusion: High resolution ultrasonography is efficient in detecting morphological changes in tibial nerve in clinically suspected diabetic neuropathic patients. Cross-sectional area and maximum thickness of nerve fascicles of tibial nerve were found to be significantly higher than typical cut off values used in this study and high-resolution ultrasound is an important tool for diagnosis of diabetic peripheral neuropathy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".