Incidence, Predictors, and Outcomes of Clinically Significant Post-ERCP Bleeding: a Contemporary Multi-center Study.

BACKGROUND AIMS: Clinically significant post-endoscopic retrograde cholangiopancreatography (ERCP) bleeding (CSPEB) is common. Contemporary estimates of risk are lacking. We aimed to identify risk factors for and outcomes following CSPEB. METHODS: We analyzed multi-center prospective ERCP data between 2018-2023 with 30-day follow-up. The primary outcome was CSPEB, defined as hematemesis, melena, or hematochezia resulting in: hemoglobin drop ≥20 g/L or transfusion and/or endoscopy to evaluate suspected bleeding, and/or unplanned healthcare visitation and/or prolongation of existing admission. Firth logistic regression was employed. P-values <0.05 were significant, with odds ratios (ORs) and 95% confidence intervals reported. RESULTS: CSPEB occurred following 129 (1.5%) of 8,517 ERCPs (mean onset 3.2 days), with 110 of 4,849 events (2.3%) occurring following higher-risk interventions (sphincterotomy, sphincteroplasty, pre-cut sphincterotomy, and/or needle-knife access). CSPEB patients required endoscopy and transfusion in 86.0% and 53.5% of cases, respectively, with three cases (2.3%) being fatal. P2Y12 inhibitors were held for a median of 4 days (IQR 4) prior to higher-risk ERCP. Following higher-risk interventions, P2Y12 inhibitors (OR 3.33, 1.26-7.74), warfarin (OR 8.54, 3.32-19.81), dabigatran (OR 13.40, 2.06-59.96), rivaroxaban (OR 7.42, 3.43-15.24) and apixaban (OR 4.16, 1.99-8.20) were associated with CSPEB. Significant intraprocedural bleeding post sphincterotomy (OR 2.32, 1.06-4.60), but not post sphincteroplasty, was also associated. Concomitant cardiorespiratory events occurred more frequently within 30 days following CSPEB (OR 12.71, 4.75-32.54). CONCLUSIONS: Risks of antiplatelet-related CSPEB may be underestimated by endoscopists based on observations of suboptimal holding before higher-risk ERCP. Appropriate periprocedural antithrombotic management is essential and could represent novel quality initiative targets.

Limited exposure to pancreatic ERCP during advanced endoscopy training impacts competence and performance in independent practice.

BACKGROUND/OBJECTIVES: The impact of competency-based training programs on pancreatic endoscopic retrograde cholangiopancreatography (ERCP) performance remains unclear. This study aimed to describe the learning curves of pancreatic ERCP and subsequent performance during independent practice. METHODS: This was a multicenter prospective cohort study involving advanced endoscopy trainees (AETs). In the 1st phase, trainees were assessed on every 5th ERCP using the ERCP and EUS Skills Assessment Tool (TEESAT). Cumulative sum (CUSUM) analysis of pancreatic ERCP evaluations was used to establish learning curves. During the 2nd phase (1st year of independent practice), now-graduated participants documented their performance on key ERCP quality indicators. RESULTS: A total of 24 AETs (20 training programs) received sufficient evaluations for CUSUM analysis. Pancreatic ERCP accounted for 14.6 % (196/1339) of all ERCPs evaluated with 45 % of pancreatic ERCPs carrying a Grade 3 level of complexity. A minority of AETs (16.7 %) performed enough pancreatic ERCPs to generate meaningful learning curves with no AETs achieving competence in pancreatic cannulation, sphincterotomy, or stone clearance during Phase 1. In Phase 2, a total of 3620 ERCPs were performed, of which 281 (7.8 %) were pancreatic ERCPs. While the overall pancreatic duct cannulation rate was 92.2 %, the native papilla pancreatic duct cannulation rate was 85.7 %, which was below the recommended 90 % threshold. CONCLUSIONS: Advanced endoscopy training offers a low level of exposure to pancreatic ERCP, which is mirrored in independent practice, highlighting the inadequate training in pancreatic ERCP. Given the complexity of pancreatic ERCP, novel strategies are warranted to improve training in pancreatic ERCP.

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the current literature, highlighted potential areas, and outlined the necessary research in artificial intelligence (AI) to allow a clearer understanding of AI as it pertains to endoscopy currently. METHODS: A modified Delphi process was used to develop these consensus statements. RESULTS: Statement 1: Current advances in AI allow for the development of AI-based algorithms that can be applied to endoscopy to augment endoscopist performance in detection and characterization of endoscopic lesions. Statement 2: Computer vision-based algorithms provide opportunities to redefine quality metrics in endoscopy using AI, which can be standardized and can reduce subjectivity in reporting quality metrics. Natural language processing-based algorithms can help with the data abstraction needed for reporting current quality metrics in GI endoscopy effortlessly. Statement 3: AI technologies can support smart endoscopy suites, which may help optimize workflows in the endoscopy suite, including automated documentation. Statement 4: Using AI and machine learning helps in predictive modeling, diagnosis, and prognostication. High-quality data with multidimensionality are needed for risk prediction, prognostication of specific clinical conditions, and their outcomes when using machine learning methods. Statement 5: Big data and cloud-based tools can help advance clinical research in gastroenterology. Multimodal data are key to understanding the maximal extent of the disease state and unlocking treatment options. Statement 6: Understanding how to evaluate AI algorithms in the gastroenterology literature and clinical trials is important for gastroenterologists, trainees, and researchers, and hence education efforts by GI societies are needed. Statement 7: Several challenges regarding integrating AI solutions into the clinical practice of endoscopy exist, including understanding the role of human-AI interaction. Transparency, interpretability, and explainability of AI algorithms play a key role in their clinical adoption in GI endoscopy. Developing appropriate AI governance, data procurement, and tools needed for the AI lifecycle are critical for the successful implementation of AI into clinical practice. Statement 8: For payment of AI in endoscopy, a thorough evaluation of the potential value proposition for AI systems may help guide purchasing decisions in endoscopy. Reliable cost-effectiveness studies to guide reimbursement are needed. Statement 9: Relevant clinical outcomes and performance metrics for AI in gastroenterology are currently not well defined. To improve the quality and interpretability of research in the field, steps need to be taken to define these evidence standards. Statement 10: A balanced view of AI technologies and active collaboration between the medical technology industry, computer scientists, gastroenterologists, and researchers are critical for the meaningful advancement of AI in gastroenterology. CONCLUSIONS: The consensus process led by the ASGE AI Task Force and experts from various disciplines has shed light on the potential of AI in endoscopy and gastroenterology. AI-based algorithms have shown promise in augmenting endoscopist performance, redefining quality metrics, optimizing workflows, and aiding in predictive modeling and diagnosis. However, challenges remain in evaluating AI algorithms, ensuring transparency and interpretability, addressing governance and data procurement, determining payment models, defining relevant clinical outcomes, and fostering collaboration between stakeholders. Addressing these challenges while maintaining a balanced perspective is crucial for the meaningful advancement of AI in gastroenterology.

Development of American Society for Gastrointestinal Endoscopy standards for training in advanced endoscopy within dedicated advanced endoscopy fellowship programs.

BACKGROUND AND AIMS: Training in interventional endoscopy is offered by nonaccredited advanced endoscopy fellowship programs (AEFPs). The number of these programs has increased dramatically with a concurrent increase in the breadth and complexity of interventional endoscopy procedures. Accreditation is governed by competency-based education, yet what constitutes a "high-quality" nonaccredited AEFP has not been defined. Using an evidence-based consensus process, we aimed to establish standards for AEFPs. METHODS: The RAND UCLA appropriateness method, a well-described modified Delphi process to develop quality indicators, was used. A task force established by the American Society for Gastrointestinal Endoscopy drafted potential quality indicators (structure, process, and outcome) in 6 categories: activity preceding training; structure of AEFPs; training in ERCP, EUS, and EMR; and luminal stent placement. Three rounds of iterative feedback from 20 experts were conducted. Round 0 involved discussion of project details. In round 1, experts independently ranked proposed quality indicators on a 9-point interval scale ranging from highly inappropriate (1) to highly appropriate (9). Next, proposed quality indicators were discussed and reworded in a group meeting followed by round 2, in which experts independently reranked proposed quality indicators and provided benchmarks (when applicable). The median score for each quality indicator was calculated. Mean absolute deviation from the median was calculated, and appropriateness of potential quality indicators was assessed using the BIOMED concerted action on appropriateness definition, P value method, and interpercentile range adjusted for symmetry definition. A quality indicator was deemed appropriate if the median score was ≥7 and met criteria for appropriateness using all 3 defined statistical methods. RESULTS: Of 89 proposed quality indicators, 37 statements met criteria as appropriate for a quality indicator (activity preceding training, 2; structure of AEFPs, 10; training in ERCP, 7; training in EUS, 8; training in EMR, 7; luminal stent placement, 3). Minimum thresholds were defined for 19 relevant quality indicators for number of trainers, procedures during fellowship, and procedures before assessment of competence. Among the final appropriate quality indicators were that all trainees should undergo qualitative and quantitative competence assessments using validated tools at least quarterly with documented feedback throughout the training period and that trainees should track outcomes and relevant quality metrics for specific procedures. CONCLUSIONS: This consensus process using validated methodology established standards for an AEFP in an effort to ensure adequate training in the most commonly taught interventional endoscopic procedures (ERCP, EUS, EMR, and luminal stent placement) during fellowship. An important component of an AEFP is the use of competency-based assessments that are compliant with the Accreditation Council for Graduate Medical Education's Next Accreditation System, with the goal of ensuring that trainees achieve specific milestones in their progression to achieving cognitive and technical competency.

Effect of an online educational module incorporating real-time feedback on accuracy of polyp sizing in trainees: a randomized controlled trial.

BACKGROUND: Although polyp size dictates surveillance intervals, endoscopists often estimate polyp size inaccurately. We hypothesized that an intervention providing didactic instruction and real-time feedback could significantly improve polyp size classification. METHODS: We conducted a multicenter randomized controlled trial to evaluate the impact of different components of an online educational module on polyp sizing. Participants were randomized to control (no video, no feedback), video only, feedback only, or video + feedback. The primary outcome was accuracy of polyp size classification into clinically relevant categories (diminutive [1-5mm], small [6-9mm], large [≥10mm]). Secondary outcomes included accuracy of exact polyp size (inmm), learning curves, and directionality of inaccuracy (over- vs. underestimation). RESULTS: 36 trainees from five training programs provided 1360 polyp size assessments. The feedback only (80.1%, P=0.01) and video + feedback (78.9%, P=0.02) groups had higher accuracy of polyp size classification compared with controls (71.6%). There was no significant difference in accuracy between the video only group (74.4%) and controls (P=0.42). Groups receiving feedback had higher accuracy of exact polyp size (inmm) and higher peak learning curves. Polyps were more likely to be overestimated than underestimated, and 29.3% of size inaccuracies impacted recommended surveillance intervals. CONCLUSIONS: Our online educational module significantly improved polyp size classification. Real-time feedback appeared to be a critical component in improving accuracy. This scalable and no-cost educational module could significantly decrease under- and overutilization of colonoscopy, improving patient outcomes while increasing colonoscopy access.

Safety and feasibility of establishing an adjuvant hepatic artery infusion program.

BACKGROUND: Hepatic artery infusion (HAI) is less frequently used in the adjuvant setting for resectable colorectal liver metastasis (CRLM) due to concerns regarding toxicity. Our objective was to evaluate the safety and feasibility of establishing an adjuvant HAI program. METHODS: Patients who underwent HAI pump placement between January 2019 and February 2023 for CRLM were identified. Complications and HAI delivery were compared between patients who received HAI in the unresectable and adjuvant settings. RESULTS: Of 51 patients, 23 received HAI for unresectable CRLM and 28 in the adjuvant setting. Patients with unresectable CRLM more commonly had bilobar disease (n = 23/23 vs n = 18/28, p < 0.01) and more preoperative liver metastases (median 10 [IQR 6-15] vs 4 [IQR 3-7], p < 0.01). Biliary sclerosis was the most common complication (n = 2/23 vs n = 4/28); however, there were no differences in postoperative or HAI-specific complications. In the most recent two years, 0 patients in the unresectable group vs 2 patients in the adjuvant group developed biliary sclerosis. All patients were initiated on HAI with no difference in treatment times or dose reductions. CONCLUSION: Adjuvant HAI is safe and feasible for patients with resectable CRLM. HAI programs can carefully consider including patients with resectable CRLM if managed by an experienced multidisciplinary team with quality assurance controls in place.

Assessment of colonoscopy skill using machine learning to measure quality: Proof-of-concept and initial validation.

Background and study aims Low-quality colonoscopy increases cancer risk but measuring quality remains challenging. We developed an automated, interactive assessment of colonoscopy quality (AI-CQ) using machine learning (ML). Methods Based on quality guidelines, metrics selected for AI development included insertion time (IT), withdrawal time (WT), polyp detection rate (PDR), and polyps per colonoscopy (PPC). Two novel metrics were also developed: HQ-WT (time during withdrawal with clear image) and WT-PT (withdrawal time subtracting polypectomy time). The model was pre-trained using a self-supervised vision transformer on unlabeled colonoscopy images and then finetuned for multi-label classification on another mutually exclusive colonoscopy image dataset. A timeline of video predictions and metric calculations were presented to clinicians in addition to the raw video using a web-based application. The model was externally validated using 50 colonoscopies at a second hospital. Results The AI-CQ accuracy to identify cecal intubation was 88%. IT ( P = 0.99) and WT ( P = 0.99) were highly correlated between manual and AI-CQ measurements with a median difference of 1.5 seconds and 4.5 seconds, respectively. AI-CQ PDR did not significantly differ from manual PDR (47.6% versus 45.5%, P = 0.66). Retroflexion was correctly identified in 95.2% and number of right colon evaluations in 100% of colonoscopies. HQ-WT was 45.9% of, and significantly correlated with ( P = 0.85) WT time. Conclusions An interactive AI assessment of colonoscopy skill can automatically assess quality. We propose that this tool can be utilized to rapidly identify and train providers in need of remediation.

Early Endoscopic Retrograde Cholangiopancreatography in Gallstone Pancreatitis Is Safe: Results From a Large Single-Center Retrospective Study.

OBJECTIVES: There is concern that performing early endoscopic retrograde cholangiopancreatography (ERCP) in the setting of gallstone pancreatitis (GSP) with choledocholithiasis can worsen underlying pancreatitis. This study was designed to assess outcomes of early versus delayed ERCP in patients with GSP with choledocholithiasis in the absence of cholangitis. MATERIALS AND METHODS: In this single-center retrospective study, we identified 124 patients who underwent ERCP for choledocholithiasis in the setting of GSP without cholangitis between 2012 and 2022. Timing of ERCP was categorized as early (<48 hours after time of diagnosis) versus delayed (>48 hours). Data on patient demographics, complications, length of stay (LOS), and mortality were collected. RESULTS: Cannulation success rates were similar for early and delayed ERCP (97% vs 100%). The adverse event rate for early ERCP was 15% compared to 29% for delayed ERCP. LOS for patients with predicted mild pancreatitis was shorter for early versus delayed ERCP (4.2 vs 7.1 days, P = 0.007). There were no deaths in either group. CONCLUSIONS: There was a trend toward fewer adverse events and there was a shorter LOS among patients with GSP with choledocholithiasis undergoing early versus delayed ERCP. Early ERCP should be considered, particularly in patients with predicted mild pancreatitis.

The Bethesda ERCP Skills Assessment Tool (BESAT) can reliably differentiate endoscopists of different experience levels.

Background and study aims The Bethesda ERCP Skill Assessment Tool (BESAT) is a video-based assessment tool of technical endoscopic retrograde cholangiopancreatography (ERCP) skill with previously established validity evidence. We aimed to assess the discriminative validity of the BESAT in differentiating ERCP skill levels. Methods Twelve experienced ERCP practitioners from tertiary academic centers were asked to blindly rate 43 ERCP videos using the BESAT. ERCP videos consisted of native biliary cannulation and sphincterotomy and were recorded from 10 unique endoscopists of various ERCP experience (from advanced endoscopy fellow to > 10 years of ERCP experience). Inter-rater reliability, discriminative validity, and internal structure validity were subsequently assessed. Results The BESAT was found to reliably differentiate between endoscopists of varying levels of ERCP experience with experienced ERCPists scoring higher than novice ERCPists in 11 of 13 (85%) instrument items. Inter-rater reliability for BESAT items ranged from good to excellent (intraclass correlation range: 0.86 to 0.93). Internal structure validity was assessed with item-total correlations ranging from 0.53 to 0.83. Conclusions Study findings demonstrate that the BESAT, a video-based ERCP skill assessment tool, has high inter-rater reliability and has discriminative validity in differentiating novice from expert ERCP skill. Further investigations are needed to determine the role of video-based assessment in improving trainee learning curves and patient outcomes.