Amitriptyline and fluphenazine in the treatment of postherpetic neuralgia. (UCLA Pain Management Center, Los Angeles, CA) <i>Clin J Pain</i> 2000;16:188–192.
Bibliographic record
Abstract
In this double‐blinded, placebo‐controlled study, 49 patients with postherpetic neuralgia (PHN) were randomly assigned to 4 treatment groups: Group 1, amitriptyline; Group 2, amitriptyline and fluphenazine; Group 3, fluphenazine; Group 4, a placebo. An active placebo was used to mimic the anticholinergic side effects of dry mouth. The study lasted 8 weeks, with weekly progress evaluations with the use of visual analog scales, the McGill Pain Questionnaire, and a side‐effects scale. A statistically significant decrease was seen in pain Groups 1 and 2, and no significant changes were seen in Groups 3 and 4. There was no significant difference when fluphenazine was added to amitriptyline. Conclude that these data support the effectiveness of amitriptyline in the treatment of PHN, but do not support the addition of fluphenazine. Comment by Lian‐Kah Ti, M.D. Amitriptyline is an established modality of treatment for postherpetic neuralgia. It is believed to exert its effect by its analgesic properties, rather than its antidepressant effect. It has been shown to raise the pain threshold, brought about by its prevention of serotonin re‐uptake. Although isolated case studies suggested a role for fluphenazine in combination with amitriptyline in the treatment of postherpetic neuralgia, the authors could not demonstrate this benefit. This study highlights the difficulties in the treatment of this condition. The use of amitriptyline reduced the intensity of pain, but did not eliminate it (VAS scores decreased from 55.9 to 26.6). When MPQ scores were compared, there was no difference, suggesting that the qualitative aspect of the pain was not reduced. More importantly, the authors noted a ceiling effect for amitriptyline, effectively limiting its potency. Combining therapies may be the answer, but as this study clearly shows, a combination with fluphenazine is not.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".