A core outcome set for appendicitis: A consensus approach utilizing modified Delphi methodology
Bibliographic record
Abstract
BACKGROUND: Appendicitis is one of the most common pathologies encountered by general and acute care surgeons. The current literature is inconsistent, as it is fraught with outcome heterogeneity, especially in the area of nonoperative management. We sought to develop a core outcome set (COS) for future appendicitis studies to facilitate outcome standardization and future data pooling. METHODS: A modified Delphi study was conducted after identification of content experts in the field of appendicitis using both the Eastern Association for the Surgery of Trauma (EAST) landmark appendicitis articles and consensus from the EAST ad hoc COS taskforce on appendicitis. The study incorporated three rounds. Round 1 utilized free text outcome suggestions, then in rounds 2 and 3 the suggests were scored using a Likert scale of 1 to 9 with 1 to 3 denoting a less important outcome, 4 to 6 denoting an important but noncritical outcome, and 7 to 9 denoting a critically important outcome. Core outcome status consensus was defined a priori as >70% of scores 7 to 9 and <15% of scores 1 to 3. RESULTS: Seventeen panelists initially agreed to participate in the study with 16 completing the process (94%). Thirty-two unique potential outcomes were initially suggested in round 1 and 10 (31%) met consensus with one outcome meeting exclusion at the end of round 2. At completion of round 3, a total of 17 (53%) outcomes achieved COS consensus. CONCLUSION: An international panel of 16 appendicitis experts achieved consensus on 17 core outcomes that should be incorporated into future appendicitis studies as a minimum set of standardized outcomes to help frame future cohort-based studies on appendicitis. LEVEL OF EVIDENCE: Diagnostic Test or Criteria; Level V.
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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 | 0.234 | 0.204 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".