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Background and Objectives: EUS-guided biliary drainage (EUS-BD) offers minimally invasive decompression when conventional endoscopic retrograde cholangiopancreatography fails. Stents can be placed from the intrahepatic ducts into the stomach (hepaticogastrostomy [HG]) or from the extrahepatic bile duct into the small intestine (choledochoduodenostomy [CCD]). Long-term patency of these stents is unknown. In this study, we aim to compare long-term patency of CCD versus HG. Methods: Consecutive patients from 12 centers were included in a registry over 14 years. Demographics, procedure info, adverse events, and follow-up data were collected. Student's t -test, Chi–square, and logistic regression analyses were conducted. Only patients with at least 6-month follow-up or who died within 6-month postprocedure were included. Results: One-hundred and eighty-two patients were included (93% male; mean age: 70; HG n = 95, CCD n = 87). No significant difference in indication, diagnosis, dissection instrument, or stent type was seen between the two groups. Technical success was 92% in both groups. Clinical success was achieved in 75/87 (86%) in the HG group and 80/80 (100%) in the CCD group. A trend toward higher adverse events was seen in the CCD group. A total of 25 patients out of 87 needed stent revision in the HG group (success rate 71%), while eight out of 80 were revised in the CCD group (success rate 90%). Chi square shows CCD success higher than HG (90% vs . 71%, P = 0.010). After adjusting for diagnosis, jaundice or cholangitis presentation, instrument used for dissection, and gender, CCD was 4.5 times more likely than HG to achieve longer stent patency or manage obstruction (odds ratio 4.5; 95% 1.1548–17.6500, P = 0.0302). Conclusion: CCD is associated with superior long-term patency than HG but with a trend toward higher adverse events. This is particularly important in patients with increased survival. Additional studies are required before recommending a change in practice.

test pool where the rest of them (80%) were considered as the trained data. Results: The final results showed that the artificial neural network achieves an R 2 ¼82%, while ANFIS succeeded to a higher correlation of about 85%, as the estimation markers of correlation between observed and predicted hemodialysis chance in methanol poisoned patients. This shows that, as an artificial model ANFIS is more reliable than the artificial neural network for predicting hemodialysis in methanol poisoning.(Figures-1,2) Conclusions: Artificial intelligent model ANFIS is a better predictor of hemodialysis chance in methanol poisoning, when compared with artificial neural network model.

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