A randomized placebo-controlled pilot study of the efficacy and safety of D-cycloserine in people with chronic back pain
Bibliographic record
Abstract
BACKGROUND: Few effective pharmacological treatment options exist for chronic back pain, the leading cause of disability in the US, and all are associated with significant adverse effects. OBJECTIVE: To determine the efficacy and safety of D-cycloserine, a partial agonist to the N-methyl-D-aspartate receptor, in the treatment of chronic low back pain. METHODS: A total of 41 participants with chronic back pain who met all inclusion and exclusion criteria were enrolled in a double-blind, placebo-controlled randomized pilot trial of D-cycloserine. Treatment was administered orally for six weeks at escalating daily doses of 100 mg, 200 mg, and 400 mg, each for two weeks. The primary outcome measure was back pain intensity using the Numeric Rating Scale (0-10). Secondary measures were back pain-related questionnaires: McGill Pain Questionnaire short form, painDETECT, PANAS, and BDI. The pre-specified analysis was a two-way repeated measures analysis of variance. RESULTS: A treatment difference was observed between groups treated with D-cycloserine and placebo at six weeks of 1.05 ± 3.1 units on the Numeric Rating Scale, with an effect size of 0.4 and p = 0.14. This trend of better chronic back pain relief with D-cycloserine was also observed in the secondary measures. No safety issues were seen. CONCLUSION: The difference in mean pain between the D-cycloserine and placebo groups did not reach statistical significance. However, a clinically meaningful effect size in the magnitude of pain relief was observed with a consistent pattern across multiple outcome measures with good safety, supporting further research into the effectiveness of D-cycloserine for chronic back pain.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".