[Toronto clinical scoring system in diabetic peripheral neuropathy].
Bibliographic record
Abstract
OBJECTIVE: To evaluate the application value of Toronto clinical scoring system (TCSS) and its grading of neuropathy for diabetic peripheral neuropathy (DPN), and to explore the relationship between TCSS grading of neuropathy and the grading of diabetic nephropathy and diabetic retinopathy. METHODS: A total of 209 patients of Type 2 diabtes (T2DM) underwent TCSS. Taking electrophysiological examination as a gold standard for diagnosing DPN, We compared the results of TCSS score > or = 6 with electrophysiological examination, and tried to select the optimal cut-off points of TCSS. RESULTS: The corresponding accuracy, sensitivity, and specificity of TCSS score > or = 6 were 76.6%, 77.2%, and 75.6%, respectively.The Youden index and Kappa were 0.53 and 0.52, which implied TCSS score > or = 6 had a moderate consistency with electrophysiological examination. There was a linear positive correlation between TCSS grading of neuropathy and the grading of diabetic nephropathy and diabetic retinopathy (P<0.05). The optimal cut-off point was 5 or 6 among these patients. CONCLUSION: TCSS is reliable in diagnosing DPN and its grading of neuropathy has clinical value.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".