Quantitative Sensory Changes Following Gasserian Ganglion Radiofrequency Thermocoagulation in Patients with Medical Refractory Trigeminal Neuralgia: A Prospective Consecutive Case Series
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Microsurgical vascular nerve decompression and percutaneous ablative interventions aiming at the Gasserian ganglion are promising treatment modalities for patients with medical refractory trigeminal neuralgia (TN). Apart from clinical reports on a variable manifestation of facial hypoesthesia, the long-term impact of trigeminal ganglion radiofrequency thermocoagulation (RFT) on sensory characteristics has not yet been determined using quantitative methods. MATERIAL AND METHODS: = 11) TN before and after percutaneous Gasserian ganglion RFT (mean follow-up: 6 months). The test battery included thermal detection and thermal pain thresholds as well as mechanical detection and mechanical pain sensitivity measures. Clinical improvement was also assessed by means of renowned pain intensity and impairment questionnaires (Short-Form McGill Pain Questionnaire, Pain Disability Index, and Pain Catastrophizing Scale), pain numeric rating scale, and anti-neuropathic medication reduction at follow-up. RESULTS: All clinical parameters developed favorably following percutaneous thermocoagulation. Only mechanical and vibration detection thresholds of the affected side of the face were located below the reference frame of the norm population before and after the procedure. Statistically significant persistent changes in quantitative sensory variables caused by the intervention could not be detected in our patient sample. CONCLUSION: Our data suggest that TN patients improving considerably after RFT do not undergo substantial long-term alterations regarding quantitative sensory perception.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".