Global evaluation and outcomes of cholecystectomy: protocol for a multicentre, international, prospective cohort study (GlobalSurg 4)
Bibliographic record
Abstract
INTRODUCTION: Cholecystectomy is one of the most common operations performed worldwide. Although laparoscopic surgery has been the 'gold-standard' approach for this operation, there is a paucity of global evidence around the variations of safe provision of cholecystectomy, including low-income and middle-income countries. This international collaborative study will allow contemporaneous data collection on the quality of cholecystectomies using measures covering infrastructure, care processes and outcomes, with the primary aim define the global variation in compliance with preoperative, intraoperative and postoperative audit standards. METHODS AND ANALYSIS: Global Evaluation of Cholecystectomy Knowledge and Outcomes is a prospective, international, multicentre, observational cohort study delivered by the GlobalSurg Collaborative. Consecutive patients undergoing cholecystectomy between 31 July 2023 and 19 November 2023 will be recruited, with follow-up at 30 days and 1-year postoperatively. The study will be undertaken at any hospital providing emergency or elective surgical services for biliary disease. The primary endpoint of this study is compliance with preoperative, intraoperative and postoperative audit standards. Secondary outcomes include rates of 30-day complications, achievement of critical view of safety and rates of gallbladder cancer. ETHICS AND DISSEMINATION: This project will not affect clinical practice and has been classified as clinical audit following research ethics review at University Hospital Birmingham NHS Trust. The protocol will be disseminated through the international GlobalSurg and CovidSurg network. TRIAL REGISTRATION NUMBER: NCT06223061.
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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 | 0.057 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.037 | 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".