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Copyright ©The Author(s) 2023.
World J Clin Cases. Jun 16, 2023; 11(17): 3949-3957
Published online Jun 16, 2023. doi: 10.12998/wjcc.v11.i17.3949
Table 1 Prediction models for rebleeding in small bowel bleeding
Ref.
Prediction model
Variables
Rebleeding rate
Niikura et al[38], 2016Prediction model using 5 factorsFemale sex, liver cirrhosis, use of warfarin, overt bleeding, hemoglobin below 10 g/dL, positive CE findings0% with 0 variable; 8.7% with 1 variable; 14.7% with 2 variables; 30.4% with 3 variables; 40.0% with 4 variables
Originally created by O’Brien et al[39], 2015; tested by Cúrdia Gonçalves et al[40], 2018ORBIT scoreAge ≥ 75 yr, hemoglobin (< 12 g/dL for women, < 13 g/dL for men), prior GI bleeding or intracranial hemorrhage, reduced kidney function (GFR < 60 mg/dL/1.73 m2), use of antiplatelets45% in low/intermediate risk group; 80% in high risk group; AUROC is 0.67 when cutoff value of 4
Uchida et al[37], 2018PRSBB scoreAge, sex, type of bleeding (occult or overt), transfusion requirement, cardiovascular disease, liver cirrhosis, CE findings, type of treatment3.63% in low risk group; 12.8% in intermediate risk group; 23.4% in high risk group
Ohmiya et al[41], 2019Ohmiya indexAngina pectoris, arrhythmia, congestive heart failure, chronic kidney disease, peripheral vascular disease, hemodialysis, valvular heart disease, hereditary vascular disease, portal hypertensive disease33% in small bowel vascular disease predicted by score ≥ 2
de Sousa Magalhães et al[45], 2020RHEMITT scoreRenal disease (GFR mL/min), heart failure, endoscopic findings, major bleeding, incomplete CE, tobacco consumption, treatment by endoscopy0.00% in low risk group; 25.4% in intermediate risk group; 63.8% in high risk group