IDDF2018-ABS-0144 Single-operator peroral cholangioscopy in the treatment of difficult biliary stones: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Current evidence supporting the utility of single-operator peroral cholangioscope (SOPOC) in the management of difficult bile duct stones is limited. We conducted the present systemic review and meta-analysis to evaluate the efficacy and safety of SOPOC in the treatment of difficult bile duct stones. Methods A search of studies up to January 2018 was acquired, using MEDLINE, EMBASE, the Cochrane Library and Google Scholar. Quality assessment of the studies was completed with a modified Newcastle-Ottawa Scale. The main outcomes of interest were single-session stone clearance rate, complete stone clearance rate and adverse events. We calculated the pooled proportions with random-effects models. Subgroup analyses were also performed based on SOPOC type. Results A total of 21 studies involving 2490 patients met the inclusion criteria. Average number of stones per patient was 2.2. Mean stone size was 17.4 mm. The pooled proportion of patients with single-session stone clearance was 72.5% (95% confidence interval [95% CI], 63.2%–80.9%). (Figure 1). Complete stone clearance was achieved in 94.7% (95% CI, 90.1%–98.1%) of patients with median endoscopic sessions of 2.0. The pooled adverse event rate was 5.5% (95% CI, 3.3%–8.2%). For SOPOC type SpyGlass and SpyGlass DS, single-session stone clearance rate was 69.1% (95%CI: 56.3%–80.6%) and 80.0% (95%CI: 75.8%–83.9%), respectively. Complete stone clearance rate was 92.8% (95%CI: 86.5%–97.5%) and 96.7% (95%CI: 88.1%–100.0%), respectively. Adverse events rate was 6.2% (95%CI: 3.4%–9.7%) and 3.0% (95%CI: 1.8%–4.4%), respectively. Conclusions SOPOC is an effective and safe management option for the treatment of bile duct stones when conventional methods have failed. More randomised controlled trials are required to elucidate the precise role of SOPOC during ERCP.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.022 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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; 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".