Development and validation of a risk prediction model and scoring system for post-endoscopic retrograde cholangiopancreatography pancreatitis

Early prediction of post-endoscopic retrograde cholangiopancreatography pancreatitis via dynamic changes of leukocyte: A retrospective study

BACKGROUND

Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) remains a major concern for clinicians. Hence early identification of PEP is meaningful to minimize medical risks.

AIMS

This study aims to explore the value of dynamic leukocyte changes for early prediction of PEP.

METHODS

Patients from January 2017 to December 2018 (training set) and January 2019 to December 2022 (test set) were retrospectively reviewed. The dynamic changes of leukocyte, neutrophil, and lymphocyte were examined to evaluate the diagnostic value of PEP.

RESULTS

A total of 498 patients (36 PEP cases) in training set and 948 patients (71 PEP cases) in test set were analyzed. Four predictors were finally identified in training set containing margin and ratio of 3h-post ERCP leukocyte count (Po Leu) to pre-ERCP leukocyte count (Pr Leu), 3h post-ERCP neutrophil-to-lymphocyte ratio (NLR) and pre-ERCP fibrinogen levels. ROC analysis revealed the optimal thresholds were 2.3 (x109/L), 1.6, 4.8 and 3.1 (g/L), respectively. The sensitivity and specificity of Po Leu - Pr Leu and Po Leu/Pr Leu were 71.0%, 82.7%, 66.1% and 86.3% to diagnosis PEP in patients with hyperamylasemia.

CONCLUSIONS

For early identification of PEP, the elevation of amylase and lipase still exhibits the highest sensitivity, while the dynamic changes of leukocyte would be helpful for the different diagnosis of hyperamylasemia.

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study

BACKGROUND AND AIMS

The impact of various categories of information on the prediction of post-ERCP pancreatitis (PEP) remains uncertain. We comprehensively investigated the risk factors associated with PEP by constructing and validating a model incorporating multimodal data through multiple steps.

METHODS

Cases (n = 1916) of ERCP were retrospectively collected from multiple centers for model construction. Through literature research, 49 electronic health record (EHR) features and 1 image feature related to PEP were identified. The EHR features were categorized into baseline, diagnosis, technique, and prevention strategies, covering pre-ERCP, intra-ERCP, and peri-ERCP phases. We first incrementally constructed models 1 to 4 incorporating these 4 feature categories and then added the image feature into models 1 to 4 and developed models 5 to 8. All models underwent testing and comparison using both internal and external test sets. Once the optimal model was selected, we conducted comparisons among multiple machine learning algorithms.

RESULTS

Compared with model 2 that incorporated baseline and diagnosis features, adding technique and prevention strategies (model 4) greatly improved the sensitivity (63.89% vs 83.33%, P < .05) and specificity (75.00% vs 85.92%, P < .001). A similar tendency was observed in the internal and external tests. In model 4, the top 3 features ranked by weight were previous pancreatitis, nonsteroidal anti-inflammatory drug use, and difficult cannulation. The image-based feature has the highest weight in models 5 to 8. Finally, model 8 used a random forest algorithm and showed the best performance.

CONCLUSIONS

We first developed a multimodal prediction model for identifying PEP with a clinical-acceptable performance. The image and technique features are crucial for PEP prediction.

Duodenal papilla radiomics-based prediction model for post-ERCP pancreatitis using machine learning: a retrospective multicohort study

BACKGROUND AND AIMS

The duodenal papillae are the primary and essential pathway for ERCP, greatly determining its complexity and outcome. We investigated the association between papilla morphology and post-ERCP pancreatitis (PEP) and constructed a robust model for PEP prediction.

METHODS

We retrospectively enrolled patients who underwent ERCP in 2 centers from January 2019 to June 2022. Radiomic features of the papilla were extracted from endoscopic images with deep learning. Potential predictors and their importance were evaluated with 3 machine learning algorithms. A predictive model was developed using best subset selection by logistic regression, and its performance was evaluated in terms of discrimination, calibration, and clinical utility based on the area under curve (AUC) of the receiver-operating characteristic curve, calibration curve, and clinical decision curve, respectively.

RESULTS

From 2 centers, 2038 and 334 ERCP patients were enrolled in this study with PEP rates of 7.9% and 9.6%, respectively. The radiomic score was significantly associated with PEP and showed great diagnostic value (AUC, .755-.821). Six hub predictors were selected to conduct a predictive model. The radiomics-based model demonstrated excellent discrimination (AUC, .825-.857) and therapeutic benefits in the training, testing, and validation cohorts. The addition of the radiomic score significantly improved the diagnostic accuracy of the predictive model (net reclassification improvement, .151-.583 [P < .05]; integrated discrimination improvement, .097-.235 [P < .001]).

CONCLUSIONS

The radiomic signature of the papilla is a crucial independent predictor of PEP. The papilla radiomics-based model performs well for the clinical prediction of PEP.

Artificial intelligence in a prediction model for postendoscopic retrograde cholangiopancreatography pancreatitis

OBJECTIVES

In this study we aimed to develop an artificial intelligence-based model for predicting postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP).

METHODS

We retrospectively reviewed ERCP patients at Nagoya University Hospital (NUH) and Toyota Memorial Hospital (TMH). We constructed two prediction models, a random forest (RF), one of the machine-learning algorithms, and a logistic regression (LR) model. First, we selected features of each model from 40 possible features. Then the models were trained and validated using three fold cross-validation in the NUH cohort and tested in the TMH cohort. The area under the receiver operating characteristic curve (AUROC) was used to assess model performance. Finally, using the output parameters of the RF model, we classified the patients into low-, medium-, and high-risk groups.

RESULTS

A total of 615 patients at NUH and 544 patients at TMH were enrolled. Ten features were selected for the RF model, including albumin, creatinine, biliary tract cancer, pancreatic cancer, bile duct stone, total procedure time, pancreatic duct injection, pancreatic guidewire-assisted technique without a pancreatic stent, intraductal ultrasonography, and bile duct biopsy. In the three fold cross-validation, the RF model showed better predictive ability than the LR model (AUROC 0.821 vs. 0.660). In the test, the RF model also showed better performance (AUROC 0.770 vs. 0.663, P = 0.002). Based on the RF model, we classified the patients according to the incidence of PEP (2.9%, 10.0%, and 23.9%).

CONCLUSION

We developed an RF model. Machine-learning algorithms could be powerful tools to develop accurate prediction models.

Development and validation of a practical clinical risk prediction model for post-endoscopic retrograde cholangiopancreatography pancreatitis

Background

Pancreatitis following endoscopic retrograde cholangiopancreatography (ERCP) can lead to significant morbidity and mortality. We aimed to develop an accurate post-ERCP pancreatitis risk prediction model using easily obtainable variables.

Methods

Using prospective multi-center ERCP data, we performed logistic regression using stepwise selection on several patient-, procedure-, and endoscopist-related factors that were determined a priori. The final model was based on a combination of the Bayesian information criterion and Akaike's information criterion performance, balancing the inclusion of clinically relevant variables and model parsimony. All available data were used for model development, with subsequent internal validation performed on bootstrapped data using 10-fold cross-validation.

Results

Data from 3021 ERCPs were used to inform models. There were 151 cases of post-ERCP pancreatitis (5.0% incidence). Variables included in the final model included female sex, pancreatic duct cannulation, native papilla status, pre-cut sphincterotomy, increasing cannulation time, presence of biliary stricture, patient age, and placement of a pancreatic duct stent. The final model was discriminating, with a receiver operating characteristic curve statistic of 0.79, and well-calibrated, with a predicted risk-to-observed risk ratio of 1.003.

Conclusions

We successfully developed and internally validated a promising post-ERCP pancreatitis clinical prediction model using easily obtainable variables that are known at baseline or observed during the ERCP procedure. The model achieved an area under the curve of 0.79. External validation is planned as additional data becomes available.

Morphology of the papilla can predict procedural safety and efficacy of ERCP-a systematic review and meta-analysis

Endoscopic Retrograde Cholangiopancreatography (ERCP) is the primary therapeutic procedure for pancreaticobiliary disorders, and studies highlighted the impact of papilla anatomy on its efficacy and safety. Our objective was to quantify the influence of papilla morphology on ERCP outcomes. We systematically searched three medical databases in September 2022, focusing on studies detailing the cannulation process or the rate of adverse events in the context of papilla morphology. The Haraldsson classification served as the primary system for papilla morphology, and a pooled event rate with a 95% confidence interval was calculated as the effect size measure. Out of 17 eligible studies, 14 were included in the quantitative synthesis. In studies using the Haraldsson classification, the rate of difficult cannulation was the lowest in type I papilla (26%), while the highest one was observed in the case of type IV papilla (41%). For post-ERCP pancreatitis, the event rate was the highest in type II papilla (11%) and the lowest in type I and III papilla (6-6%). No significant difference was observed in the cannulation failure and post-ERCP bleeding event rates between the papilla types. In conclusion, certain papilla morphologies are associated with a higher rate of difficult cannulation and post-ERCP pancreatitis.

Predictive models in EUS/ERCP

Predictive models (PMs) in endoscopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS) have the potential to improve patient outcomes, enhance diagnostic accuracy, and guide therapeutic interventions. This review aims to summarize the current state of predictive models in ERCP and EUS and their clinical implications. To be considered useful in clinical practice a PM should be accurate, easy to perform, and may consider objective variables. PMs in ERCP estimate correct indication, probability of success, and the risk of developing adverse events. These models incorporate patient-related factors and technical aspects of the procedure. In the field of EUS, these models utilize clinical and imaging data to predict the likelihood of malignancy, presence of specific lesions, or risk of complications related to therapeutic interventions. Further research, validation, and refinement are necessary to maximize the utility and impact of these models in routine clinical practice.

Impact of center and endoscopist ERCP volume on ERCP outcomes: a systematic review and meta-analysis

BACKGROUND AND AIMS

Endoscopist experience and center volume might be associated with ERCP outcomes, as in other fields of endoscopy and in surgery. An effort to assess this relationship is important to improve practice. This systematic review and meta-analysis aimed to evaluate these comparative data and to assess the impact of endoscopist and center volume on ERCP procedure outcomes.

METHODS

We performed a literature search in PubMed, Web of Science, and Scopus through March 2022. Volume classification included high- and low-volume (HV and LV) endoscopists and centers. The primary outcome was the impact of endoscopist and center volume on ERCP success. Secondary outcomes were the overall adverse event (AE) rate and the specific AE rate. The quality of the studies was assessed using the Newcastle-Ottawa scale. Data synthesis was obtained by direct meta-analyses using a random-effects model; results are presented as odds ratios (ORs) with 95% confidence intervals (CIs).

RESULTS

Of 6833 relevant publications, 31 studies met the inclusion criteria. Procedure success was higher among HV endoscopists (OR, 1.81; 95% CI, 1.59-2.06; I2 = 57%) and in HV centers (OR, 1.77; 95% CI, 1.22-2.57; I2 = 67%). The overall AE rate was lower for procedures performed by HV endoscopists (OR, .71; 95% CI, .61-.82; I2 = 38%) and in HV centers (OR, .70; 95% CI, .51-.97; I2 = 92%). Bleeding was less frequent in procedures performed by HV endoscopists (OR, .67; 95% CI, .48-.95; I2 = 37%) but did not differ based on center volume (OR, .68; 95% CI, .24-1.90; I2 = 89%). No statistical differences were detected concerning pancreatitis, cholangitis, and perforation rates.

CONCLUSIONS

HV endoscopists and centers provide higher ERCP success rates with fewer overall AEs, especially bleeding, compared with respective LV comparators.

Risk factors of pancreatitis after endoscopic retrograde cholangiopancreatography in patients with biliary tract diseases

BACKGROUND

To investigate the risk factors of pancreatitis after endoscopic retrograde cholangiopancreatography (ERCP) in patients with biliary tract diseases.

METHODS

We retrospectively analyzed the clinical data of 480 patients who underwent ERCP for biliary tract diseases at the Affiliated Zhongshan Hospital of Dalian University from October 2011 to October 2016. The patients were divided into a study group (n = 75, with PEP) and a control group (n = 405, without PEP) based on whether they developed post-ERCP pancreatitis (PEP), and their clinical baseline data and intraoperative conditions were retrieved and compared. Then, factors associated with PEP were analyzed using logistic regression model, based on which a nomogram prediction model was constructed. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the performance of the prediction model.

RESULTS

Significant differences in age, sex, history of pancreatitis, history of choledocholithiasis, pancreatic duct imaging, pancreatic sphincterotomy, difficult cannulation, multiple cannulation attempts and juxtapapillary duodenal diverticula were observed between the two groups. Multivariate logistic regression analysis showed that age less than 60 years (OR, 0.477; 95% CI, 0.26-0.855), female sex (OR, 2.162; 95% CI, 1.220-3.831), history of pancreatitis (OR, 2.567; 95% CI, 1.218-5.410), history of choledocholithiasis (OR, 2.062; 95% CI, 1.162-3.658), pancreatic sphincterotomy (OR, 2.387; 95% CI, 1.298-4.390), pancreatic duct imaging (OR, 4.429; 95% CI, 1.481-13.242), multiple cannulation attempts (OR, 2.327; 95% CI, 1.205-4.493), difficult cannulation (OR, 2.421; 95% CI, 1.143-5.128), and JPD (OR, 2.002; 95% CI, 1.125-3.564) were independent risk factors for PEP. The nomogram for predicting the occurrence of PEP demonstrated an area under the ROC curve (AUC) of 0.787, and the calibration curves of the model showed good consistency between the predicted and actual probability of PEP.

CONCLUSION

Our results showed that age less than 60 years, female sex, history of pancreatitis, history of choledocholithiasis, pancreatic sphincterotomy, pancreatic duct imaging, multiple cannulation attempts, difficult cannulation and juxtapapillary duodenal diverticula were independent risk factors for PEP. In addition, the established nomogram demonstrated promising clinical efficacy in predicting PEP risk in patients who underwent ERCP for biliary tract diseases.

Prevention of post-ERCP pancreatitis: current strategies and novel perspectives

Endoscopic retrograde cholangiopancreatography (ERCP) is an advanced endoscopic procedure that might lead to severe adverse events. Post-ERCP pancreatitis (PEP) is the most common post-procedural complication, which is related to significant mortality and increasing healthcare costs. Up to now, the prevalent approach to prevent PEP consisted of employing pharmacological and technical expedients that have been shown to improve post-ERCP outcomes, such as the administration of rectal nonsteroidal anti-inflammatory drugs, aggressive intravenous hydration, and the placement of a pancreatic stent. However, it has been reported that PEP originates from a more complex interaction of procedural and patient-related factors. Appropriate ERCP training has a pivotal role in PEP prevention strategy, and it is not a chance that a low PEP rate is universally considered one of the most relevant indicators of proficiency in ERCP. Scant data on the acquisition of skills during the ERCP training are currently available, although some efforts have been recently done to shorten the learning curve by way of simulation-based training and demonstrate competency by meeting technical requirements as well as adopting skill evaluation scales. Besides, the identification of adequate indications for ERCP and accurate pre-procedural risk stratification of patients might help to reduce PEP occurrence regardless of the endoscopist's technical abilities, and generally preserve safety in ERCP. This review aims at delineating current preventive strategies and highlighting novel perspectives for a safer ERCP focusing on the prevention of PEP.

An artificial intelligence difficulty scoring system for stone removal during ERCP: a prospective validation

BACKGROUND

A computer-assisted (CAD) system was developed to assess, score, and classify the technical difficulty of common bile duct (CBD) stone removal during endoscopic retrograde cholangiopancreatography (ERCP). The efficacy of the CAD system was subsequently assessed through a multicenter, prospective, observational study.

METHOD

All patients who met the inclusion criteria were included. Based on cholangiogram images, the CAD system analyzed the level of difficulty of stone removal and classified it into "difficult" and "easy" groups. Subsequently, differences in clinical endpoints, including attempts at stone extraction, stone extraction time, total operation time, and stone clearance rates were compared between the two groups.

RESULTS

173 patients with CBD stones from three hospitals were included in the study. The group classified as difficult by CAD had more extraction attempts (7.20 vs. 4.20, P < 0.001), more frequent machine lithotripsy (30.4 % vs. 7.1 %, P < 0.001), longer stone extraction time (16.59 vs. 7.69 minutes, P < 0.001), lower single-session stone clearance rate (73.9 % vs. 94.5 %, P < 0.001), and lower total stone clearance rate (89.1 % vs. 97.6 %, P = 0.019) compared with the group classified as easy by CAD.

CONCLUSION

The CAD system effectively assessed and classified the degree of technical difficulty in endoscopic stone extraction during ERCP. In addition, it automatically provided a quantitative evaluation of CBD and stones, which in turn could help endoscopists to apply suitable procedures and interventional methods to minimize the possible risks associated with endoscopic stone removal.

The assessment of the ASGE-grading system of ERCP: a large-sample retrospective study

BACKGROUND AND AIMS

The American Society for Gastrointestinal Endoscopy (ASGE) has developed a complexity-grading system for endoscopic retrograde cholangiopancreatography (ERCP) to predict technical success and adverse events. This study aimed to assess the association between the degree of difficulty for ERCP and the rates of success and adverse event, in turn demonstrating the validity and practicality of this system.

METHODS

ERCP procedures performed in the First Affiliated Hospital of Nanchang University from January 2011 to December 2020 were retrospectively reviewed. Procedural success and adverse events were recorded based on difficulty level according to the ASGE-grading system.

RESULTS

A total of 20,652 ERCP procedures performed during the study period were analyzed, including 1908 procedures considered grade 1(9.2%), 10,170 procedures considered grade 2 (49.2%), 7764 procedures considered grade 3 (37.6%), 810 procedures considered grade 4 (3.9%). The overall success rate increased from 92.8% in 2011-2015 to 94.0% in 2016-2020, while the distribution of procedures and the incidence of complications showed little variation. The success rate revealed a significantly decreasing trend with increasing difficulty (ranging from 55.6 to 98.6%), mainly for biliary diseases. In addition, the difficulty scale was not associated with any differences in the rate of adverse event, except for the pancreatitis for grade 1 procedures, which had a low incidence.

CONCLUSIONS

The ASGE-grading system can help predict the success rate of ERCP procedures but showed poor performance in predicting adverse events. Further exploration may be required to improve the grading system by adjusting or including certain clinical parameters, and to validate the system for extrapolation to other endoscopy units.

A Risk Prediction Model for Post-endoscopic Retrograde Cholangiopancreatography Pancreatitis After Stent Insertion for Malignant Biliary Obstruction: Development and Validation

OBJECTIVES

Pancreatitis is the most common complication of post-endoscopic retrograde cholangiopancreatography (ERCP). There are currently no prediction models, particularly for post-ERCP pancreatitis (PEP) after biliary stent placement due to malignant biliary obstruction (MBO). To that end, we aim to develop and validate a predictive model for PEP.

METHODS

We retrospectively analyzed the data of patients who underwent ERCP for biliary stent placement due to MBO at the Second Affiliated Hospital of Harbin Medical University from January 1, 2014 to August 31, 2021. The eligible patients were randomly allocated to the development and validation cohorts. A prediction model was built using the development cohort, and the model's effect was validated using a validation cohort.

RESULTS

A total of 1524 patients were enrolled, including 1016 in the development cohort and 508 in the validation cohort, with an overall PEP rate of 7.1%. The model's predictors included acute pancreatitis history, the absence of pancreatic duct dilation, nonpancreatic cancer, difficult cannulation, and pancreatic injection. The area under the curve (AUC) in the development cohort was 0.810, and the incidence of PEP in the low-risk, medium-risk, and high-risk groups was 1.53%, 9.12%, and 36.36%, respectively. Meanwhile, the AUC of the validation cohort was 0.781, and the incidence of PEP in the low-risk, medium-risk, and high-risk groups was 4.17%, 8.75%, and 41.67%, respectively.

CONCLUSIONS

This study was the first to build and validate a risk prediction model, especially for PEP after biliary stent placement due to MBO. Moreover, this model might assist clinicians in identifying high-risk patients and help implement preventive measures in a more timely manner.

New practical scoring system to predict post-endoscopic retrograde cholangiopancreatography pancreatitis: Development and validation

Background and Aim

Post‐endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is the most serious adverse event of ERCP. Therefore, it is important to identify high‐risk patients who require prophylactic measures. The aim of this study was to develop a practical prediction model for PEP that identifies high‐risk patients.

Methods

Patients who underwent ERCP at three tertiary hospitals between April 2010 and September 2012 were enrolled. The dataset was divided into a training set (two centers) and validation set (one center). Using the training set, univariable and multivariable analyses were performed to identify predictive factors for PEP. We constructed a scoring system and evaluated reproducibility using the validation set.

Results

A total of 2719 ERCPs were analyzed. PEP developed in 133 cases (4.9%). Risk factors (adjusted odds ratios [OR]) in the training set were a history of PEP (OR: 4.2), intact papilla (OR: 2.4), difficult cannulation (OR: 1.9), pancreatic guidewire‐assisted biliary cannulation (OR: 2.2), pancreatic injection (OR: 2.1), pancreatic intraductal ultrasonography (IDUS)/sampling from the pancreatic duct (OR: 2.2), and biliary IDUS/sampling from the biliary tract (OR: 2.8). A scoring system was constructed using these seven clinical variables. The areas under the receiver‐operating characteristic curve of this model were 0.799 in the training set and 0.791 in the validation set. In the high‐risk group at a score of 3 or higher, the incidence of PEP was 13.4%, and all severe/fatal cases were in the high‐risk group.

Conclusions

This scoring system helps to predict each patient's risk and select preventive measures.