Development and validation of new scoring system for predicting endoscopic failure in adult patients with upper gastrointestinal bleeding ulcer in Hospital Sultanah Aminah Johor Bahru - Jeyabalan, Krishanthini A/P R (2024)
Introduction: Upper gastrointestinal bleeding (UGIB) has an incidence of 72 per 100 000 population in Malaysia. Despite high success rates of endoscopic treatment, 6.4% to 19.2% of patients develop rebleeding which increases the risk of mortality by 4-5 times. Objective: To identify factors associated with endoscopic failure and develop a validated scoring system to predict endoscopic failure among adult patients with upper gastrointestinal bleeding ulcers in HSAJB Methodology: This is a case-control study using secondary data of 443 cases where 98 cases had rebleeding within 30 days of successful initial endoscopy and 345 were controls. Patient-related, clinical and endoscopic findings were compared. Logistic regression was used to identify factors associated with endoscopic failure, and the predictors from the final logistic regression model were used to develop the scoring system. Internal validation was done via bootstrapping and the model was presented as a score chart. Results: Logistic regression identified chronic kidney disease (CKD) (adjusted OR=2.08, 95%CI:1.09,3.88, p=0.025), duodenal ulcer (adj. OR=2.91, 95%CI:1.67,5.30, p<0.001), and ulcer size more than 2 cm (adj. OR=2.56, 95%CI:1.55,4.22, p<0.001) as significant predictors of endoscopic failure. These predictors were incorporated into a scoring system, which underwent internal validation using bootstrapping. The scoring system demonstrated an accuracy of 70.1%, with a specificity of 84% and a sensitivity of 47%, supporting its potential utility in clinical practice. Conclusion: Duodenal ulcers, ulcers more than 2cm in diameter, and CKD are significant predictors of endoscopic failure. The inclusion of both clinical and endoscopic factors in this locally developed scoring system provides for a more comprehensive risk assessment tool.