Botulinum toxin-A as a treatment option for refractory idiopathic trigeminal neuralgia of the ophthalmic branch: a case report and literature review
Bibliographic record
Abstract
Trigeminal neuralgia is one of the most common neurological pains affecting the head and neck and is associated with severe, lancinating, electrical pain episodes. The maxillary and mandibular branches are usually affected. The ophthalmic branch is rarely involved and, when present, it requires a comprehensive workup to rule out major conditions. Pharmacotherapy and surgery are the most common treatment options for this condition. Systemic medications may pose a wide range of side effects and effectiveness may decrease over time while surgery has inherent complications. Injectable onabotulinum toxins have been utilized for various applications in medicine and dentistry. There is, however, limited data on their use for the management of refractory trigeminal neuralgia of the ophthalmic branch. We present the case of a 58-year-old male diagnosed with refractory idiopathic trigeminal neuralgia affecting the ophthalmic branch, which was unresponsive to standard care and successfully managed with onabotulinum toxin type A. This treatment should be considered in cases of refractory trigeminal neuralgia prior to surgery. We reviewed the relevant literature concerning the application of Onabotulinum toxin A for managing trigeminal neuralgia of the ophthalmic branch. This case report and review aim to enlighten the application of Onabotulinum toxin A for managing refractory trigeminal neuralgia of the ophthalmic branch. Our case report and review show that Onabotulinum toxin A could be used for managing TN of the ophthalmic branch.
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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 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".