Opioid versus opioid-free analgesia after surgical discharge: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Excessive prescribing after surgery has contributed to a public health crisis of opioid addiction and overdose in North America. However, the value of prescribing opioids to manage postoperative pain after surgical discharge remains unclear. We propose a systematic review and meta-analysis to assess the extent to which opioid analgesia impact postoperative pain intensity and adverse events in comparison to opioid-free analgesia in patients discharged after surgery. METHODS AND ANALYSIS: Major electronic databases (MEDLINE, Embase, Cochrane Library, Scopus, AMED, BIOSIS, CINAHL and PsycINFO) will be searched for multi-dose randomised-trials examining the comparative effectiveness of opioid versus opioid-free analgesia after surgical discharge. Studies published from January 1990 to July 2019 will be targeted, with no language restrictions. The search will be re-run before manuscript submission to include most recent literature. We will consider studies involving patients undergoing minor and major surgery. Teams of reviewers will, independently and in duplicate, assess eligibility, extract data and evaluate risk of bias. Our main outcomes of interest are pain intensity and postoperative vomiting. Study results will be pooled using random effects models. When trials report outcomes for a common domain (eg, pain intensity) using different scales, we will convert effect sizes to a common standard metric (eg, Visual Analogue Scale). Minimally important clinical differences reported in previous literature will be considered when interpreting results. Subgroup analyses defined a priori will be conducted to explore heterogeneity. Risk of bias will be assessed according to the Cochrane Collaboration's Risk of Bias Tool 2.0. The quality of evidence for all outcomes will be evaluated using the GRADE rating system. ETHICS AND DISSEMINATION: Ethical approval is not required since this is a systematic review of published studies. Our results will be published in a peer-reviewed journal and presented at relevant conferences. Further knowledge dissemination will be sought via public and patient organisations focussed on pain and opioid-related harms.
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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 | 0.070 | 0.113 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.025 | 0.031 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.057 | 0.006 |
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".