Safety and effectiveness of opioid use in adult patients presenting to emergency services with suspected acute appendicitis: a protocol for a systematic review of the literature and network meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Acute abdominal pain is a chief complaint in emergency departments and represents 7%-10% of emergency room (ER) visits. Acute appendicitis represents 15% of the causes of abdominal pain and 62% of the causes that require surgical treatment. Opioid analgesia has been evaluated in clinical trials, and they have determined it does not impact diagnostic accuracy. Despite evidence, withholding analgesia is still a common practice. Pain severely impacts quality of life and analgesia has become essential in humanised medicine. We aim to determine the safety and effectiveness of different opioid regimens for adult patients that present to the ER with acute suspected appendicitis. METHODS AND ANALYSIS: We will search MEDLINE and Embase via Ovid, and the Cochrane Central Register of Controlled Trials without restrictions on the study publication date. Screening, extraction and risk of bias assessment will be performed in duplicate. We will use the Cochrane Risk of Bias Assessment Tool. We will perform both pairwise meta-analysis and network meta-analysis (NMA) if transitivity and coherence principles are met. Heterogeneity will be evaluated using the I² and χ² and using the thresholds recommended by Cochrane. We will perform sensitivity analysis based on the pre-established potential effect modifiers, risk of bias and data that required transformation or imputation. Publication bias will be addressed by using funnel plots on a pairwise level. We will assess the strength of the body of evidence using the Grading of Recommendations Assessment, Development and Evaluation approach (GRADE) per outcome, and evidence from the NMA will be assessed using the GRADE approach for NMA. ETHICS AND DISSEMINATION: Approval by an ethics committee is not required for this study since no personal information will be handled. Information will be disseminated by publication on a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42024583804.
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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 | 0.067 | 0.103 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.023 | 0.040 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".