The Relationship between NCS Findings and Toronto Clinical Scoring System of Neuropathy in Diabetic Polyneuropathy
Bibliographic record
Abstract
Introduction: Diabetic polyneuropathy is one of the most common and important complications of diabetes mellitus for its clinical ranking. Several clinical categorising scoring systems have been designated. Among them only Toronto Clinical Scoring System (TCSS) had been partially evaluated on the basis of pathologic findings in sural nerve biopsy. Only the mild cases had been studied since the myelin of sural nerve is destroyed in more severe cases of neuropathy and they are not appropriate for pathologic studies. This study was designed to evaluate TCSS on the basis of electro diagnostic findings in the mild to severe diabetic polyneuropathy in Kermanshah. Materials and Methods: , 61 patients with diabetic polyneuropathy who have been referred to Clinic of Diabetes, were recruited and screened by using TCSS. In the next phase, nerve conduction studies measuring the amplitude and velocity of the sural, proneal, tibial, radial and ulnar nerves on both sides were examined in a single blind study. Nerve conduction abnormity index (NCAI) was calculated for each patient on the basis of the number of abnormalities in amplitude and velocity in these nerves. Correlation between TCSS and NCAI scorings were analysed using Spearman and Pearson co- efficient and the Kappa coefficient test. Results: 49 (80%) subjects were female and 12 (20%) male. The mean age for the female and male were 55±12 and 54±13 years respectively. 6 patients were IDDM and 55 patients were NIDDM. A significant correlation was found between TCSS and NCAI and (r =0. 733, p<0.001) and (k=0.708, p<0.001). Discussion: A nearly direct correlation was found between the number of abnormalities in conduction studies and TCSS in diabetic polyneuropathy. In a previous study the correlation between TCSS and pathologic finding was shown in the mild diabetic polyneuropathy. We can recommend that TCSS is a valid scoring system for grading of diabetic polyneuropathy in clinical examinations. In addition, it is an easy method and suitable for clinical approaches.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".