The Treatment of Trigeminal Neuralgia in Patients with Multiple Sclerosis using Percutaneous Radiofrequency Rhizotomy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Trigeminal neuralgia (TN) has a higher incidence among patients with multiple sclerosis (MS) than in the general population. This cohort of MS patients with TN presents a series of management challenges including poor tolerance of antineuralgic medications and occasional bilateral presentation. We analyzed our surgical series of MS patients presenting with TN who were treated with percutaneous radiofrequency rhizotomy to estimate the success, failure and recurrence rate of this procedure for those patients. METHODS: Surgical reports were retrospectively reviewed between the years 1996-2000. Patients with MS and TN who received a percutaneous rhizotomy during that time were included in the study and followed until the end of 2002. Data regarding age, sex, duration of MS and pain, response to medical treatment, pain distribution and surgical outcome were evaluated. RESULTS: There were thirteen patients with MS and medically refractory TN treated with percutaneous radiofrequency rhizotomy. The average age at diagnosis for MS was 41 with TN beginning an average of eight years later. Following rhizotomy, complete pain relief without the need for any medication was achieved in 81% of the patients. The addition of medications resulted in pain control in the remaining patients. During a mean follow-up period of 52 months, there was a 50% recurrence rate. There were no complications related to the procedure and the associated facial numbness was well-tolerated. CONCLUSIONS: Percutaneous radiofrequency rhizotomy is a safe and effective method for the treatment of TN in patients with MS. The unique susceptibility of this cohort to the side effects of antineuralgic medications may require early consideration of rhizotomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it