Perioperative use of gabapentinoids for the management of postoperative acute pain: protocol of a systematic review and meta-analysis
Bibliographic record
Abstract
Opioids are commonly used for the management of postoperative pain, but their use is limited by important adverse events, such as respiratory depression and the potential for addiction. Multimodal opioid-sparing analgesia regimens can be effectively employed to manage postoperative pain and reduce exposure to opioids. Gabapentinoids (pregabalin and gabapentin) represent an attractive class of drugs for use in multimodal regimens. The American Pain Society recommends the use of gabapentinoids during the perioperative period; however, evidence to inform such a recommendation is unclear. We will conduct a systematic review and meta-analysis of randomized clinical trials evaluating the use of systemic gabapentinoids, in comparison to other analgesic regimens or placebo in adult patients undergoing surgery. We will search MEDLINE, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), the Web of Science, and ClinicalTrials.gov databases for relevant citations. Our primary outcome will be intensity of postoperative acute pain (12 h). Our secondary outcomes will be postoperative pain intensity at 6, 24, 48 h, and 72 h, cumulative dose of opioids administered within 24, 48, and 72 h following surgery, the length of stay, chronic pain, and adverse events. Two investigators will independently select trials and extract data. We will evaluate the risk of bias of included trials using the Cochrane risk of bias tools. We will represent pooled continuous data as weighted mean differences and pooled dichotomous data as risk ratios with a 95% confidence interval. We will use random effect models and assess statistical heterogeneity with the I2 index. Our study will provide the best level of evidence to inform the effect of gabapentinoids in the management of postoperative acute pain. PROSPERO CRD42017067029
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.036 | 0.008 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".