Abstract
Background and aims: Optimal training strategies in endoscopic retrograde cholangiopancreatography (ERCP) remain controversial despite the shift towards competence-based training models, with limited data available on patient safety during training. We aimed to assess whether pre-procedural clinical predictors could identify patients at low-risk of developing procedure-related adverse-events(AE) in a training environment. Methods: We performed a prospective, multicenter,cohort study including 5 training centers. A data collection system documenting indication, clinical data, trainee performance as assessed using a validated competence assessment tool (TEESAT), technical outcomes and AEs over a 30-day follow-up was utilized. We compared the rate of AE in a training environment between low-risk and high-risk patients as stratified using a previously derived clinical risk score (Trainee involvement in ERCP Risk Score-TIERS). The association between the trainee performance as assessed using TEESAT scores and the occurrence of AEs was also evaluated. Results: A total of 1283 ERCPs (409 (31.9% 95%CI 29.3%-34.4%) with trainee involvement) performed by 11 trainers and 10 trainees were analyzed. AE were more frequent in the high risk compared to the low risk group 27% (CI95% 20.5%-34.7%) vs 17.1% (CI95% 12.8%-22.2%). The TIERS risk score demonstrated a high negative predictive value for AE (82.86%, 95% CI 79.40% - 85.84%) and was the only predictor of AE (OR 1.38 (1.09-1.75)) on multivariate analysis. Suboptimal trainee performance was associated with an increase in AE rates. Conclusion: Simple, clinical-based predictive tools, could improve ERCP training through an individualized selection of cases for hands-on training, with the aim of increasing patient safety.
Lingua originale | English |
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pagine (da-a) | 804-811 |
Numero di pagine | 8 |
Rivista | Endoscopy |
Volume | 55 |
DOI | |
Stato di pubblicazione | Pubblicato - 2023 |
Keywords
- Endoscopic retrograde cholangiopancreatography
- Training
- adverse events
- performance measures