Diagnostic performance of graded tuning fork vibration thresholds as a stand-alone test and within clinical assessments of diabetic neuropathy
Bibliographic record
Abstract
AIMS: We aimed to provide new reference data for C64 Hz-Rydel-Seiffer tuning fork Vibration Sensation Thresholds (VST) for the clinical diagnosis of Diabetic Sensorimotor Polyneuropathy (DSPN) and to evaluate the diagnostic performance when used in combination with other clinical tests as implemented in the Neuropathy Disability Score (NDS). METHODS: The study included 1,215 individuals with type 1 or type 2 diabetes and 207 with Normal Glucose Tolerance (NGT), who underwent clinical, electrophysiological, and Quantitative Sensory Tests (QST). Multiple regression analyses were used to determine VST in individuals with NGT. The diagnostic performance of tests to detect confirmed small or large fibre DSPN according to Toronto consensus criteria was assessed in 373 individuals with diabetes who underwent skin biopsies do determine intraepidermal nerve fibre density (IENFD). RESULTS: The new age-dependent lower normative VST showed 73.5% sensitivity, 85.4% specificity, and 82.3% accuracy in diagnosing confirmed DSPN. Combining VST with the PinPrick test resulted in 83.4% sensitivity, 80.3% specificity, and 81.2% accuracy. The NDS incorporating VST was associated with nerve conduction indices, QST, and IENFD. CONCLUSIONS: The new VST reference data shall enable clinicians to detect DSPN with higher accuracy in clinical practice, particularly when combined with a single small fibre test.
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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 | 0.011 | 0.133 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".