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Risk factors and prediction of bleeding after gastric endoscopic submucosal dissection in patients on antithrombotic therapy: newly developed bleeding prediction application software,SAMURAI model
Authors:Akitoshi Hakoda  Toshihisa Takeuchi  Yuichi Kojima  Yasuhiro Fujiwara  Yasuaki Nagami  Yuji Naito  Shinsaku Fukuda  Tomoyuki Koike  Mitsushige Sugimoto  Kenta Hamada  Hideki Kobara  Norimasa Yoshida  Tomoki Inaba  Akihito Nagahara  Eriko Koizumi  Kazunari Murakami  Takahisa Furuta  Naotaka Ogasawara  Hajime Isomoto  Kotaro Shibagaki  Hiromi Kataoka  Hidekazu Suzuki  Kazuhide Higuchi
Abstract:
Bleeding after gastric endoscopic submucosal dissection (ESD) remains problematic, especially in patients receiving antithrombotic therapy. Therefore, this study aimed to identify the risk factors. In this retrospective study, patients (n = 1,207) who underwent gastric ESD while receiving antithrombotic therapy were enrolled at Osaka Medical and Pharmaceutical University Hospital and 18 other referral hospitals in Japan. Risks of post-ESD bleeding were calculated using multivariable logistic regression. The dataset was divided into a derivation cohort and a validation cohort. We created a prediction model using the derivation cohort. The accuracy of the model was evaluated using the validation cohort. Post-ESD bleeding occurred in 142 (11.8%) participants. Multivariable analysis yielded an odds ratio of 2.33 for aspirin, 4.90 for P2Y12 receptor antagonist, 1.79 for cilostazol, 0.95 for other antithrombotic agents, 6.53 for warfarin, 5.65 for dabigatran, 7.84 for apixaban, 10.45 for edoxaban, 6.02 for rivaroxaban, and 1.46 for heparin bridging. The created prediction model was called safe ESD management using the risk analysis of post-bleeding in patients with antithrombotic therapy (SAMURAI). This model had good predictability, with a C-statistic of 0.77. In conclusion, use of the SAMURAI model will allow proactive management of post-ESD bleeding risk in patients receiving antithrombotic therapy.
Keywords:bleeding   antithrombotic agents   multivariable analysis   prediction model   validation
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