Validity of Non-Invasive Tests for Small Fiber Neuropathy (P03.205)
Bibliographic record
Abstract
Objective: The aim of this study was to evaluate the accuracy of different methods for evaluation of small fiber neuropathy (SFN) using intra epidermal nerve fiber density (IENFD) as the reference standard. Background IENFD is the current standard for evaluation of SFN but limited by invasiveness, expense and availability. Heat-induced neurogenic vasodilation by Laser Doppler Imaging (LDI), cold detection thresholds (CDT) and heat perception (HP) are noninvasive nerve function alternatives whose accuracy relative to morphological IENFD is unknown. Design/Methods: We performed a retrospective chart review of 75 patients suspected of having SFN at the Toronto General Hospital, University Health Network from 2008-2011. A detailed history and clinical examination, laboratory studies, nerve conduction studies (NCS), CDT, HP, LDI and IENFD were performed in all patients. We quantitatively compared the results of clinical evaluation including pain on the visual analogue scale (VAS), LDI, CDT and HP relative to IENFD for the diagnosis of SFN. Results: The mean IENFD was 7.52 +/- 4.12 with a median value of 7.59 and interquartile range of 4.64-10.91 (25% to 75%). 34.7% had abnormal IENFD and 65.3% had normal IENFD according to published criteria (normal defined as > 5.4 fibers/mm). Low-magnitude correlation was observed between IENFD and CDT (R2 =0.0812, p Conclusions: None of the objective measures reflected IENFD with very good diagnostic validity, but of these small fiber non-invasive methods, CDT had the highest level of accuracy, while we could not demonstrate acceptable performance of LDI. Alternate non-invasive methods for the determination of small fiber function or morphology are urgently needed. Disclosure: Dr. Ebadi has nothing to disclose. Dr. Perkins has nothing to disclose. Dr. Katzberg has received personal compensation for activities with Genzyme as a speaker and participant on an advisory board. Dr. Katzberg has received research support from Griffolds Biotherapeutics. Dr. Bril has received personal compensation for activities with Talecris Biotherapeutics as a consultant. Dr. Bril has received research support from Talecris Biotherapeutics.
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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 | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".