急性下部消化管出血における出血所見同定の予測モデル構築：全国多施設共同研究

Objectives: Stigmata of recent hemorrhage (SRH) directly indicate a need for endoscopic therapy in acute lower gastrointestinal bleeding (LGIB). Colonoscopy would be prioritized for patients with highly suspected SRH, but the predictors of colonic SRH remain unclear. We aimed to construct a predictive model for the efficient detection of SRH using a nationwide cohort. Methods: We retrospectively analyzed 8360 patients admitted through hospital emergency departments for acute LGIB in the CODE BLUE-J Study (49 hospitals throughout Japan). All patients underwent inpatient colonoscopy. To develop an SRH predictive model, 4863 patients were analyzed. Baseline characteristics, colonoscopic factors (timing, preparation, and devices), and computed tomography (CT) extravasation were extensively assessed. The performance of the model was externally validated in 3497 patients. Results: Colonic SRH was detected in 28% of patients. A novel predictive model for detecting SRH (CS-NEED score: Colono Scopic factors, No abdominal pain, Elevated PT-INR, Extravasation on CT, and DOAC use) showed high performance (area under the receiver operating characteristic curve [AUC] 0.74 for derivation and 0.73 for external validation). This score was also highly predictive of active bleeding (AUC 0.73 for derivation and 0.76 for external validation). Patients with low (0-6), intermediate (7-8), and high (9-12) scores in the external validation cohort had SRH identification rates of 20%, 31%, and 64%, respectively (P < 0.001 for trend). Conclusions: A novel predictive model for colonic SRH identification (CS-NEED score) can specify colonoscopies likely to achieve endoscopic therapy in acute LGIB. Using the model during initial management would contribute to finding and treating SRH efficiently.