Divalproex sodium in the management of post-herpetic neuralgia: a randomized double-blind placebo-controlled study
Bibliographic record
Abstract
BACKGROUND: Post-herpetic neuralgia is difficult to treat. Divalproex sodium (valproic acid and sodium valproate in molar ratio 1:1) has been used successfully in the management of various painful neuropathies. AIM: To study the effectiveness and safety of divalproex sodium in the management of post-herpetic neuralgia. DESIGN: Randomized double-blind placebo-controlled trial. METHODS: We enrolled 48 consecutively attending out-patients with post-herpetic neuralgia, out of whom three were excluded (two had insufficient pain, one withdrew consent). Quantification of pain was by Short Form-McGill pain questionnaire (SF-MPQ), visual analogue scale (VAS), present pain intensity score (PPI) and 11 point Likert scale (11 PLS) at the beginning of the study, after 2 weeks, 4 weeks and at the end of the study (8 weeks). We also assessed patients' global impression of change by questionnaire at the end of the study. RESULTS: After 8 weeks treatment with 1000 mg/day divalproex sodium, there was significant reduction in pain: SF-MPQ, 20.47 +/- 2.29 to 11.90 +/- 6.52 (p < 0.0001); PPI 4.0 +/- 0.52 to 1.95 +/- 1.29 (p < 0.0001); VAS 70.17 +/- 9.21 to 31.27 +/- 29.74 (p < 0.0001) and 11 PLS 6.97 +/- 0.73 to 3.63 +/- 2.34 (p < 0.0001) in comparison to placebo (means +/- SEM). The 'global impression of change' questionnaire showed much or moderate improvement in pain in 58.2% of patients receiving divalproex vs. 14.8% of those receiving placebo. The drug was well tolerated by all patients, except one who developed severe vertigo after 10 days of treatment. DISCUSSION: Divalproex sodium provides significant pain relief in patients of post-herpetic neuralgia, with very little incidence of adverse reactions. These data provide a basis for longer trials in a larger group of patients.
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.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".