The Impact of Surgical Amputation and Valproic Acid on Pain and Functional Trajectory: Results from the Veterans Integrated Pain Evaluation Research (VIPER) Randomized, Double-Blinded Placebo-Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To determine if the perioperative administration of valproic acid reduces the incidence of chronic pain three months after amputation or revision surgery. DESIGN: Multicenter, randomized, double-blind, placebo-controlled trial. SETTING: Academic, military, and veteran medical centers. SUBJECTS: One hundred twenty-eight patients undergoing amputation or amputation revision surgery at Duke University Hospital, Walter Reed National Military Medical Center, or the Durham Veterans Affairs Medical Center for either medical disease or trauma. METHODS: Patients were randomized to placebo or valproic acid for the duration of hospitalization and treated with multimodal analgesic care, including regional anesthetic blockade. Primary outcome was the proportion of patients with chronic pain at three months (average numeric pain score intensity of 3/10 or greater). Secondary outcomes included functional trajectories (assessed with the Brief Pain Inventory short form and the Defense and Veterans Pain Rating Scale). RESULTS: The overall rate of chronic pain was 68.2% in the 107 patients who completed the end point assessment. There was no significant effect of perioperative valproic acid administration, with a rate of 65.45% (N = 36) in the treatment group and a rate of 71.15% (N = 37) in the placebo group. Overall, pain scores decreased from baseline to follow-up (median = -2 on the numeric pain scale). Patients additionally experienced improvements in self-perceived function. CONCLUSIONS: The rate of chronic pain after amputation surgery is not significantly improved with the perioperative administration of valproic acid. In this cohort treated with multimodal perioperative analgesia and regional anesthetic blockade, we observed improvements in both pain severity and function.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".