Comparison of efficacy of adriamycin chemo-ganglionectomy and radiofrequency thermocoagulation of gasserian ganglionin in treating craniofacial postherpetic neuralgia
Bibliographic record
Abstract
Objective To compare the efficacy of adriamycin chemo-ganglionectomy and radiofrequency thermocoagulation (RFT) of semilunar ganglion in treating craniofacial postherpetic neuralgia (PHN). Methods A total of 95 patients with PHN in the areas innervated by maxillary and mandibular divisions of trigeminal nerve, aged 55-90 yr, with the course of disease 6 months-3 yr, were divided into 2 groups using a random number table method: adriamycin chemo-ganglionectomy group (ADM group, n=48) and RFT group (n=47). Hartel anterior approach to puncture was performed via the foramen ovale under the guidance of CT in two groups.In group ADM, 0.5% adriamycin 2.5 mg (0.5 ml) was injected via the foramen ovale, and RFT of gasserian ganglion was performed in group RFT.Visual Analog Scale (VAS) and the short-form McGill pain questionnaire (SF-MPQ) scores were evaluated before and after treatment.The rate of effective treatment was calculated, and treatment-related complications were recorded. Results Compared with group RFT, no significant change was found in VAS or SF-MPQ scores before treatment, VAS and SF-MPQ scores were increased and the rate of effective treatment was decreased at 1 and 7 days after treatment, VAS and SF-MPQ scores were decreased and the rate of effective treatment was increased at 6 and 12 months after treatment, the incidence of facial numbness, hypoesthesia, masticatory muscle weakness and weakened corneal reflex was decreased in group ADM (P<0.05). Conclusion Compared with semilunar ganglion RFT, the long-term efficacy of adriamycin chemo-ganglionectomy of semilunar ganglion in treating craniofacial PHN is enhanced, and the safety is higher. Key words: Neuralgia, postherpetic; Doxorubicin; Electrocoagulation; Trigeminal ganglion
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".