Comparison of Risk Scores for Predicting Adverse Outcomes in Acute Lower Gastrointestinal Bleeding

• Published in: Gastroenterology research and practice 2024, Vol.2024, p.3111414-7
• Main Authors: Li, Chenyang, Linghu, Enqiang, Chen, Chao
• Format: Article
• Language: English
• Subjects: Blood; Blood transfusions; Colonoscopy; Diabetes; Emergency medical care; Endoscopy; Hemorrhage; Hospitals; Hypertension; Internet resources; Intervention; Medical imaging; Mortality; Nonsteroidal anti-inflammatory drugs; Patients
• ISSN: 1687-6121; 1687-630X
• DOI: 10.1155/2024/3111414

Purpose. Acute lower gastrointestinal bleeding (ALGIB) is a common emergency in gastroenterology. Currently, there is insufficient information to predict adverse outcomes in patients with acute lower gastrointestinal bleeding. Our study is aimed at comparing the effectiveness of the clinical risk scores currently utilized and their ability to predict significant outcomes in lower gastrointestinal bleeding. Methods. We conducted a retrospective observational study of patients who were admitted to ALGIB and underwent colonoscopy or angiography at a single center between January 2018 and December 2022. Adverse outcomes associated with ALGIB included rebleeding, blood transfusion, hemostatic interventions, and in-hospital death. We calculated six risk scores at admission (Oakland, Birmingham, SHA2PE, Ramaekers, SALGIB, and CNUH-5). We measured the accuracy of these scores using the area under the receiver operating characteristic curve (AUC) and compared them with DeLong’s test. Results. 123 patients with confirmed LGIB (aged 65 years, 55-75) were finally included. The most common diagnoses were colorectal cancer (25%) and hemorrhoids (14%). All scores demonstrated sufficient and comparable effectiveness for hemostatic intervention but no discrimination for rebleeding. The Oakland and SALGIB scores were superior to the other scores in predicting blood transfusion (AUC: 0.97 and 0.95, respectively; p=0.208) and any adverse outcomes (AUC: 0.78 and 0.78, respectively; p=0.854). Conclusions. The Oakland and SALGIB scores outperform the other scores in predicting the requirement for blood transfusion in ALGIB patients, but no single prediction tool had the best ability across all outcomes. Novel risk stratification scores with higher performance are needed for better risk stratification in ALGIB.