Early cholangioscopy-assisted electrohydraulic lithotripsy in difficult biliary stones is cost-effective
Bibliographic record
Abstract
BACKGROUND AND AIMS: Single-operator cholangioscopy-assisted electrohydraulic lithotripsy (SOC-EHL) is effective and safe in difficult choledocholithiasis. The optimal timing of SOC-EHL use, however, in refractory stones has not been elucidated. The following aims to determine the most cost-effective timing of SOC-EHL introduction in the management of choledocholithiasis. METHODS: A cost-effectiveness model was developed assessing three strategies with a progressively delayed introduction of SOC-EHL. Probability estimates of patient pathways were obtained from a systematic review. The unit of effectiveness is complete ductal clearance without need for surgery. Cost is expressed in 2018 US dollars and stem from outpatient US databases. RESULTS: The three strategies achieved comparable ductal clearance rates ranging from 97.3% to 99.7%. The least expensive strategy is to perform SOC-EHL during the first endoscopic retrograde cholangiography pancreatography (ERCP) (SOC-1: 18,506$). The strategy of postponing the use of SOC-EHL to the third ERCP (SOC-3) is more expensive (US$18,895) but is 2% more effective. (0.9967). SOC-EHL during the second ERCP in the model (SOC-2) is the least cost-effective. Sensitivity analyses show altered conclusions according to the cost of SOC-EHL, effectiveness of conventional ERCP, and altered willingness-to-pay (WTP) thresholds with early SOC-1 being the most optimal approach below a WTP cut-off of US$20,295. CONCLUSIONS: Early utilization of SOC-EHL (SOC-1) in difficult choledocholithiasis may be the least costly strategy with an effectiveness approximating those achieved with a delayed approach where one or more conventional ERCP(s) are reattempted prior to SOC-EHL introduction.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.007 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".