The milestone for preventing post-ERCP pancreatitis using novel simplified predictive scoring system: a propensity score analysis

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.

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.

Development and external validation of a nomogram for prediction of post-endoscopic retrograde cholangiopancreatography pancreatitis

BACKGROUND AND AIMS

Endoscopic retrograde cholangiopancreatography (ERCP) is widely performed for management of pancreatobiliary diseases; however, post-ERCP pancreatitis (PEP) remains as an unsolved problem. Although various risk factors for PEP have been reported, the prediction of PEP remains controversial. This study aimed to develop a predictive model for PEP.

METHODS

Consecutive patients undergoing ERCP for biliary indications at two centers were retrospectively studied. Using data from a training cohort, we utilized a multivariable model to select five variables to construct a nomogram. The predictive model was internally and externally validated. Based on the nomogram, the patients were categorized into low-, moderate-, and high-risk groups.

RESULTS

Using the data of 2224 patients in the training cohort, five variables were selected to generate a nomogram: 1) sex, 2) indication for ERCP, 3) difficult cannulation, 4) guidewire insertion into the pancreatic duct, and 5) endoscopic sphincterotomy or sphincteroplasty. The most significant risk factor was endoscopic papillary balloon dilation such as endoscopic sphincterotomy or sphincteroplasty. The bias-corrected concordance index was 0.72 in the training cohort and 0.72 in the validation cohort. Calibration curves for both cohorts demonstrated good agreement between the predicted and observed frequencies of the actual outcome. In the validation cohort, PEP developed in 5.0% and 14% of patients in the moderate- and high-risk groups, respectively.

CONCLUSIONS

We successfully developed a good predictive model for PEP. The prevention of PEP in high risk patients should be investigated further.

Potential significance of uncovered self‐expandable metal stents for distal malignant biliary obstruction: A propensity score‐adjusted competing risk regression analysis

Objectives

Selection criteria for self‐expandable metal stents (SEMSs) with or without cover during palliative treatment of distal malignant biliary obstruction (DMBO) remain unclear. We evaluated factors associated with time to recurrent biliary obstruction (TRBO) in fully covered SEMSs (FCSEMSs) and uncovered SEMSs (UCSEMSs).

Methods

We retrospectively analyzed consecutive patients with DMBO who received a SEMS. TRBO was determined using the Kaplan–Meier analysis, and complications were compared between the FCSEMS and UCSEMS groups. After TRBO‐associated factors were extracted using multivariate competing‐risks regression (CRR), propensity score‐adjusted CRRs were performed to verify their robustness.

Results

There were 180 patients (66 FCSEMSs and 114 UCSEMSs) enrolled in this study. There was no significant difference between median TRBO in the FCSEMS and UCSEMS groups (275 vs. 255 days, p = 0.67). Complications were more frequent in the FCSEMS than UCSEMS group (21.2% vs. 8.8%; p = 0.023). Multivariate CRR for TRBO‐associated factors revealed that “pancreatic ductal carcinoma (PDAC) treated with UCSEMS” was the only independent predictor of TRBO (p = 0.03). Similarly, the propensity score‐adjusted CRRs showed no significant difference in TRBO in “FCSEMS” vs “UCSEMS” (p = 0.96); however, there was a significant difference in “PDAC using UCSEMS” vs “other” (p = 0.043). In the palliative care group including any DMBO without chemotherapy, the first quartile of the TRBO of UCSEMS was 100 days.

Conclusions

UCSEMSs are a possible option for both patients with DMBO arising from PDAC and for patients with any DMBO receiving palliative care who should avoid SEMS‐related complications.

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.

Rectal administration of low-dose diclofenac does not reduce post-endoscopic retrograde cholangiopancreatography pancreatitis: a propensity score matching analysis

BACKGROUND

Endoscopic retrograde cholangiopancreatography (ERCP) is a popular technique; however, post-ERCP pancreatitis (PEP) remains a major adverse event. The administration of rectal nonsteroidal anti-inflammatory drugs (NSAIDs) is reportedly effective in preventing PEP. However, the recommended dose varies and the efficacy of low-dose rectal NSAIDs remains unclear. Therefore, we decided to investigate the effectiveness of low-dose rectal diclofenac on PEP prevention, using propensity score matching.

METHODS

This single-center retrospective study included 401 patients who underwent ERCP between July 2015 and March 2020. After December 2016, we administered rectal diclofenac within 30 min before the ERCP procedure as widely as possible. Patients were divided into those who did (diclofenac group) and did not (control group) receive rectal diclofenac. Patients weighing ≥ 50 kg were administered a 50 mg dose, while those weighing < 50 kg were administered a 25 mg dose. The incidence and severity of PEP in the two groups were assessed by propensity score matching analysis.

RESULTS

Among 401 patients undergoing ERCP, 367 fulfilled the inclusion criteria. Overall, 187 patients received rectal diclofenac (diclofenac group) and 180 did not (control group). After propensity score matching, 105 pairs were selected for evaluation. Overall, seven (6.7%) patients in the diclofenac group and 10 (9.5%) in the control group developed PEP (P = 0.45). Moderate or severe PEP occurred in four (3.8%) patients in the diclofenac group and six (5.7%) in the control group (P = 0.52).

CONCLUSIONS

The administration of low-dose rectal diclofenac could not reduce the incidence and severity of PEP.

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.

Diagnostic Dilemma of Biliopancreatic Contrast-Enhanced Harmonic Endoscopic Ultrasonography

Background: The utility of contrast-enhanced harmonic endoscopic ultrasonography (CH-EUS) alone in the biliopancreatic region appears to be limited because it is highly dependent on the experience and skill of the endoscopist. Therefore, the present study aimed to validate the efficacy of CH-EUS in clinical practice. Methods: Between January 2018 and March 2019, 301 consecutive patients who underwent CH-EUS were prospectively enrolled in this study. The diagnostic performance of CH-EUS was compared with that of dynamic computed tomography (CT), magnetic resonance imaging (MRI), and all combinations (i.e., CH-EUS, dynamic CT, and MRI) using a Bonferroni correction. A multiple logistic regression analysis was performed to extract each disease that allowed the CH-EUS diagnosis to be consistent with the final diagnosis. Results: In multiple comparisons of diagnostic performance, no significant differences were observed among dynamic CT, MRI, and CH-EUS (p = 1.00), but the diagnostic performance was significantly higher when all modalities were combined (p < 0.001). Moreover, only intraductal papillary mucinous neoplasm comprising adenoma or carcinoma (IPMN, n = 161) showed significance with respect to the agreement with the final diagnosis (p = 0.006). Conclusions: Our results showed that CH-EUS-based diagnosis of IPMN may be possible in clinical practice. On the contrary, to accurately diagnose biliopancreatic diseases other than IPMN, comprehensive diagnosis using multiple modalities may be necessary, rather than relying on CH-EUS alone.

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.