Predictive model of bleeding following endoscopic sphincterotomy for the treatment of choledocholithiasis in hemodialysis patients: A retrospective multicenter study
So Nakaji,
Yoshihiro Okawa,
Kenji Nakamura,
Masahiro Itonaga,
Masami Inase,
Harutoshi Sugiyama,
Rei Suzuki,
Kenji Yamauchi,
Hiroki Matsui,
Nobuto Hirata,
Junko Saito,
Naoki Ishii,
Toshio Tsuyuguchi,
Hironari Kato,
Masayuki Kitano,
Naoya Kato,
Hiromasa Ohira,
Hiroyuki Okada,
Takuji Torimura,
Hiroyuki Maguchi
Affiliations
So Nakaji
Department of Gastroenterology Kameda Medical Center Chiba Japan
Yoshihiro Okawa
Department of Gastroenterology Chikamori Hospital Kochi Japan
Kenji Nakamura
Department of Gastroenterology St. Luke's International Hospital Tokyo Japan
Masahiro Itonaga
Second Department of Internal Medicine Wakayama Medical University Wakayama Japan
Masami Inase
Department of Gastroenterology Ebina General Hospital Ebina Japan
Harutoshi Sugiyama
Department of Gastroenterology, Graduate School of Medicine Chiba University Chiba Japan
Rei Suzuki
Department of Gastroenterology Fukushima Medical University Fukushima Japan
Kenji Yamauchi
Department of Gastroenterology and Hepatology Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences Okayama Japan
Hiroki Matsui
Clinical Research Support Division Kameda Institute for Health Science, Kameda College of Health Sciences Chiba Japan
Nobuto Hirata
Department of Gastroenterology Kameda Medical Center Chiba Japan
Junko Saito
Department of Gastroenterology Chikamori Hospital Kochi Japan
Naoki Ishii
Division of Gastroenterology Tokyo Shinagawa Hospital Shinagawa City Japan
Toshio Tsuyuguchi
Department of Gastroenterology, Graduate School of Medicine Chiba University Chiba Japan
Hironari Kato
Department of Gastroenterology and Hepatology Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences Okayama Japan
Masayuki Kitano
Second Department of Internal Medicine Wakayama Medical University Wakayama Japan
Naoya Kato
Department of Gastroenterology, Graduate School of Medicine Chiba University Chiba Japan
Hiromasa Ohira
Department of Gastroenterology Fukushima Medical University Fukushima Japan
Hiroyuki Okada
Department of Gastroenterology and Hepatology Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences Okayama Japan
Takuji Torimura
Department of Medicine Kurume University School of Medicine Kurume Japan
Hiroyuki Maguchi
Department of Gastroenterology Kameda Medical Center Chiba Japan
Abstract Background and Aim Although hemodialysis (HD) is a strong risk factor for postendoscopic sphincterotomy (ES) bleeding, additional risk factors in HD patients remain unclear. There is no model for predicting post‐ES bleeding risk in HD patients. Therefore, we conducted a retrospective multicenter study to reveal these risk factors and develop a predictive model of post‐ES bleeding in HD patients. Methods We retrospectively reviewed the medical records of HD patients who underwent ES at eight hospitals between January 2006 and December 2016, with post‐ES bleeding as the main outcome measure. Univariate analyses were performed to extract possible risk factors for post‐ES bleeding. Factors that were clinically important and statistically significant in our univariate analyses were then included in our logistic regression analysis for the development of a multivariate predictive model of post‐ES bleeding. This predictive model was visualized using a predictive nomogram. Results Post‐ES bleeding occurred in 20 (16.3%) of 123 HD patients. Based on clinically important factors and the results of our univariate analyses, platelet count, prothrombin time (international normalized ratio), and HD duration were included in our predictive model of post‐ES bleeding. Receiver operating characteristic analysis found that this model had an area under the curve of 0.715 (95% confidence interval, 0.609–0.822). We developed a predictive nomogram based on these results. Conclusions We demonstrated that post‐ES bleeding is more common in HD patients than in the general population and succeeded in constructing a predictive model that can effectively identify HD patients at risk of post‐ES bleeding.