Evaluating the impact of cannabinoids on sleep health and pain in patients with chronic neuropathic pain: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Background Chronic neuropathic pain is often debilitating and can have a significant impact on sleep health and quality of life. There is limited information on the impact of cannabinoids on sleep health when treating neuropathic pain. Objective The objectives of this systematic review and meta-analysis were to determine the effect of cannabinoids on sleep quality, pain intensity, and patient impression of treatment efficacy in patients with neuropathic pain. Evidence review Nine available medical literature databases were searched for randomized controlled trials comparing synthetic and natural cannabinoids to placebo in patients with neuropathic pain syndromes. Data on validated tools for sleep quality, pain intensity, patients’ global impression of change (PGIC), and incidence of adverse effects of cannabinoids were extracted and synthesized. Findings Of the 3491 studies screened, eight randomized controlled trials satisfied the inclusion criteria for this review. Analyses were performed using R -4.1.2. using the metafor package and are interpreted using alpha=0.05 as the threshold for statistical significance. Validated measures for sleep health were not used in most studies. Meta-analysis of data from six studies showed that cannabinoids were associated with a significant improvement in sleep quality (standardized mean difference (SMD): 0.40; 95% CI: 0.19 to −0.61, 95% prediction interval (PI): −0.12 to 0.88, p-value=0.002, I2=55.26, τ2=0.05, Q-statistic=16.72, GRADE: moderate certainty). Meta-analysis of data from eight studies showed a significant reduction in daily pain scores in the cannabinoid (CB) group (SMD: −0.55, 95% CI:−0.69 to −0.19, 95% PI: −1.51 to 0.39, p=0.003, I2=82.49, τ2=0.20, Q-statistic=47.69, GRADE: moderate certainty). However, sleep health and analgesic benefits were associated with a higher likelihood of experiencing daytime somnolence, nausea, and dizziness. Conclusions Cannabinoids have a role in treating chronic neuropathic pain as evidenced by significant improvements in sleep quality, pain intensity, and PGIC. More research is needed to comprehensively evaluate the impact of cannabinoids on sleep health and analgesic efficacy. PROSPERO registration number CRD42017074255.
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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 | 0.050 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.026 | 0.045 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".