Palmitoylethanolamide in the Treatment of Chronic Pain: A Systematic Review and Meta-Analysis of Double-Blind Randomized Controlled Trials
Bibliographic record
Abstract
Chronic pain is a major source of morbidity for which there are limited effective treatments. Palmitoylethanolamide (PEA), a naturally occurring fatty acid amide, has demonstrated utility in the treatment of neuropathic and inflammatory pain. Emerging reports have supported a possible role for its use in the treatment of chronic pain, although this remains controversial. We undertook a systematic review and meta-analysis to examine the efficacy of PEA as an analgesic agent for chronic pain. A systematic literature search was performed, using the databases MEDLINE and Web of Science, to identify double-blind randomized controlled trials comparing PEA to placebo or active comparators in the treatment of chronic pain. All articles were independently screened by two reviewers. The primary outcome was pain intensity scores, for which a meta-analysis was undertaken using a random effects statistical model. Secondary outcomes including quality of life, functional status, and side effects are represented in a narrative synthesis. Our literature search identified 253 unique articles, of which 11 were ultimately included in the narrative synthesis and meta-analysis. Collectively, these articles described a combined sample size of 774 patients. PEA was found to reduce pain scores relative to comparators in a pooled estimate, with a standard mean difference of 1.68 (95% CI 1.05 to 2.31, p = 0.00001). Several studies reported additional benefits of PEA for quality of life and functional status, and no major side effects were attributed to PEA in any study. The results of this systematic review and meta-analysis suggest that PEA is an effective and well-tolerated treatment for chronic pain. Further study is warranted to determine the optimal dosing and administration parameters of PEA for analgesic effects in the context of chronic 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 | 0.023 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".