Use of the AIMS65 and pre-endoscopy Rockall scores in the prediction of mortality in patients with the upper gastrointestinal bleeding

Ulus Travma Acil Cerrahi Derg. 2022 Dec;29(1):100-104. doi: 10.14744/tjtes.2022.38890.


Background: Upper gastrointestinal (GI) bleeding is one of the most common reasons for emergency department (ED) visits. This study aimed to evaluate the predictive power of the AIMS65 and pre-endoscopy Rockall scores in predicting in-hospital mortality in patients that presented to ED and were diagnosed with the upper GI bleeding.

Methods: Data of patients aged 18 years and older, who visited ED of Kartal Dr. Lütfi Kırdar City Hospital during the study period and were diagnosed with upper GI bleeding, were obtained from the electronic-based hospital information system and analyzed retrospectively. Each scoring system was compared using the receiver operating characteristic (ROC) curve analysis.

Results: The study was completed with 592 patients. The mean age of the patients was 63.5±19.0 years, and 68.6% were male. The total in-hospital mortality rate was 5.2%. In the ROC analysis of the AIMS65 and pre-endoscopy Rockall scores in the prediction of in-hospital mortality, the area under the curve values was calculated as 0.822 (95% confidence interval [CI]: 0.788-0.852) and 0.777 (95% CI: 0.741-0.810), respectively. When these two scoring systems were compared, neither had statistically significant superiority over the other in predicting in-hospital mortality.

Conclusion: The AIMS65 and pre-endoscopy Rockall scores can be used to predict in-hospital mortality in patients with GI bleeding. However, since the AIMS65 score consists of only five variables that can easily be calculated in ED, we recommend its use in clinical practice.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Endoscopy, Gastrointestinal*
  • Female
  • Gastrointestinal Hemorrhage* / diagnosis
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • ROC Curve
  • Retrospective Studies
  • Risk Assessment
  • Severity of Illness Index