Prediction scores or gastroenterologists' Gut Feeling for triaging patients that present with acute upper gastrointestinal bleeding.

Introduction: Several prediction scores for triaging patients with upper gastrointestinal (GI) bleeding have been developed, yet these scores have never been compared to the current gold standard, which is the clinical evaluation by a gastroenterologist. The aim of this study was to assess the added value of prediction scores to gastroenterologists' Gut Feeling in patients with a suspected upper GI bleeding.

Methods: WE PROSPECTIVELY EVALUATED GUT FEELING OF SENIOR GASTROENTEROLOGISTS AND ASKED THEM TO ESTIMATE: (1) the risk that a clinical intervention is needed; (2) the risk of rebleeding; and (3) the risk of mortality in patients presenting with suspected upper GI bleeding, subdivided into low, medium, or high risk. The predictive value of the gastroenterologists' Gut Feeling was compared to the Blatchford and Rockall scores for various outcomes.

Results: We included 974 patients, of which 667 patients (68.8%) underwent a clinical intervention. During the 30-day follow up, 140 patients (14.4%) developed recurrent bleeding and 44 patients (4.5%) died. Gut Feeling was independently associated with all studied outcomes, except for the predicted mortality after endoscopy. Predictive power, based on the AUC of the Blatchford and Rockall prediction scores, was higher than the Gut Feeling of the gastroenterologists. However, combining both the Blatchford and Rockall scores and the Gut Feeling yielded the highest predictive power for the need of an intervention (AUC 0.88), rebleeding (AUC 0.73), and mortality (AUC 0.71 predicted before and 0.77 predicted after endoscopy, respectively).

Conclusions: Gut Feeling is an independent predictor for the need of a clinical intervention, rebleeding, and mortality in patients presenting with upper GI bleeding; however, the Blatchford and Rockall scores are stronger predictors for these outcomes. Combining Gut Feeling with the Blatchford and Rockall scores resulted in the most optimal prediction.