A Comparative Analysis of Risk Scoring Systems in Predicting Clinical Outcomes in Upper Gastrointestinal Bleed
Abhijnya K Renukaprasad1, Srikanth Narayanaswamy1, Vinay R2
1Internal Medicine, M S Ramaiah Medical College, Bangalore, IND.
This study compared risk scoring systems for upper gastrointestinal bleeds (UGIB). The Glasgow-Blatchford score (GBS) effectively predicted patient risk and need for interventions, while AIMS65 and pre-Rockall scores accurately predicted mortality.
Area of Science:
- Gastroenterology
- Clinical Medicine
- Medical Informatics
Background:
- Upper gastrointestinal bleeding (UGIB) is a critical medical emergency with varied presentations.
- Accurate risk stratification is vital for effective UGIB management and patient triage.
- Existing scoring systems aim to predict outcomes but require comparative analysis.
Purpose of the Study:
- To evaluate and compare the sensitivity and specificity of four UGIB risk scoring systems.
- To determine optimal cut-off values for these scores in predicting clinical outcomes.
- To identify the most effective scoring system for stratifying UGIB patients.
Main Methods:
- A prospective cross-sectional study involving 81 patients with acute UGIB.
- Utilized four scoring systems: Glasgow-Blatchford score (GBS), AIMS65, pre-endoscopic Rockall, and full Rockall.
- Assessed predictive accuracy for mortality, ICU admission, need for transfusion, and endoscopic intervention.
Main Results:
- AIMS65 and pre-Rockall scores demonstrated high accuracy (AUROC 0.91) in predicting mortality.
- GBS and AIMS65 showed utility in predicting the need for intensive care unit (ICU) admission.
- GBS proved superior in categorizing patients into high/low-risk groups and predicting interventions.
Conclusions:
- The Glasgow-Blatchford score (GBS) is highly effective for risk stratification and predicting interventions in UGIB.
- AIMS65 and pre-Rockall scores are comparable and reliable for predicting mortality in UGIB patients.
- Risk stratification using validated scores is crucial for optimizing UGIB patient management.
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