P.086 The clinical significance of trigeminal neuralgia nomenclature
Bibliographic record
Abstract
Background: A diagnosis of trigeminal neuralgia (TN) may be broadly applied to many neuralgic facial pains, while more stringent criteria are required for management decisions, outcome assessment, and pathophysiological correlations. Our aim was to evaluate existing classification systems of facial pain. Methods: The study population was comprised of 534 Manitobans referred to neurosurgery for facial pain from 2001 to 2013. A retrospective chart review identified presenting features; pain distribution, nature, and duration. The recorded diagnoses (rDx) were then re-classified according to the International Classification of Headache Disorders (ICHD-3) and Burchiel System of TN1 and TN2. Results: There was complete correlation between rDx and ICHD-3 for typical TN (tTN) in 266(49.8%) patients, atypical TN (aTN) in 39(7.3%), and idiopathic facial pain (IFP) in 59(11%). Idiopathic trigeminal neuropathy (iTn) in 35(6.6%) was not classified in ICHD-3. Burchiel-TN1 included heterogeneous diagnoses including tTN (266), aTN (27), iTn (2) and IFP (8); Burchiel-TN2 included aTN (10), iTn (23), and IFP (15). Another 135(25.5%) had other facial pain diagnoses. Conclusions: Classification of TN is especially important when selecting and evaluating surgical treatments. Diagnostic criteria should clearly differentiate between unique conditions and ideally have basis on underlying etiology. The ICHD-3 nomenclature best satisfies these aims although should be expanded to include iTn.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.012 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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; both teacher heads agree on what is shown here.
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".