Development and Validation of a Risk Scoring System for Severe Acute Lower Gastrointestinal Bleeding

We aimed to develop and validate a risk scoring system to determine the risk of severe lower gastrointestinal bleeding (LGIB) and predict patient outcomes.

We first performed a retrospective analysis of data from 439 patients emergently hospitalized for acute LGIB at the National Center for Global Health and Medicine in Japan, from January 2009 through December 2013. We used data on comorbidities, medication, presenting symptoms, and vital signs, and laboratory test results to develop a scoring system for severe LGIB (defined as continuous and/or recurrent bleeding). We validated the risk score in a prospective study of 161 patients with acute LGIB admitted to the same center from April 2014 through April 2015. We assessed the system's accuracy in predicting patient outcome using area under the receiver operating characteristics curve (AUC) analysis. All patients underwent colonoscopy.

In the first study, 29% of the patients developed severe LGIB. We devised a risk scoring system based on nonsteroidal anti-inflammatory drugs use, no diarrhea, no abdominal tenderness, blood pressure of 100 mm Hg or lower, antiplatelet drugs use, albumin level less than 3.0 g/dL, disease scores of 2 or higher, and syncope (NOBLADS), which all were independent correlates of severe LGIB. Severe LGIB developed in 75.7% of patients with scores of 5 or higher compared with 2% of patients without any of the factors correlated with severe LGIB (P < .001). The NOBLADS score determined the severity of LGIB with an AUC value of 0.77. In the validation (second) study, severe LGIB developed in 35% of patients; the NOBLADS score predicted the severity of LGIB with an AUC value of 0.76. Higher NOBLADS scores were associated with a requirement for blood transfusion, longer hospital stay, and intervention (P < .05 for trend).

We developed and validated a scoring system for risk of severe LGIB based on 8 factors (NOBLADS score). The system also determined the risk for blood transfusion, longer hospital stay, and intervention. It might be used in decision making regarding intervention and management.