Laparoendoscopic Rendezvous Versus Preoperative ERCP and Laparoscopic Cholecystectomy for the Management of Cholecysto-Choledocholithiasis
Bibliographic record
Abstract
In Brief Background: Although the ideal management of cholecysto-choledocholi-thiasis is controversial, the 2-stage approach [endoscopic retrograde cholangiopancreatography (ERCP), sphincterotomy, and common bile duct (CBD) clearance followed by laparoscopic cholecystectomy] remains the standard way of management worldwide. One-stage approach using the so-called laparoendoscopic rendezvous (LERV) technique offers some advantages, mainly by reducing the hospital stay and the risk of post-ERCP pancreatitis. Objective: To compare the LERV 1-stage approach with the standard 2-stage approach consisting of preoperative ERCP followed by laparoscopic cholecystectomy for the treatment of cholecysto-choledocholithiasis. Setting: Controlled randomized trial, University/Teaching Hospital. Methods: Patients with cholecysto-choledocholithiasis were randomized either to LERV or to the 2-stage approach. Both elective and emergency cases were included in the study. Primary endpoint was to detect difference in overall hospital stay, whereas secondary endpoints were (i) to detect differences in morbidity (especially post-ERCP pancreatitis) and (ii) success of CBD clearance. This is an interim analysis of the first 100 randomized patients. Results: Hospital stay was significantly shorter in the LERV group; median 4 (2–19) days versus 5.5 (3–22) days, P = 0.0004. There was no difference in morbidity and success of CBD clearance between the 2 groups. Post-ERCP amylase value was found significantly lower in the LERV group: median 65 (16–1159) versus 91 (30–1846), P = 0.02. Conclusions: Interim analysis of the results suggests the superiority of the LERV technique in terms of hospital stay and post-ERCP hyperamylasemia. In this controlled randomized trial, patients with cholecysto-choledocholithiasis—both elective and emergency cases—were randomized either to laparoendoscopic rendezvous (LERV) or to the 2-stage approach endoscopic retrograde cholangiopancreatography (ERCP) followed by laparoscopic cholecystectomy). The interim analysis of the first 100 patients suggests the superiority of the LERV technique in terms of hospital stay and post-ERCP hyperamylasemia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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, 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".