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Massive transfusion in upper gastrointestinal bleeding: a new scoring system
Yi-Chuan Chen1,2, Chen-Ju Chuang1, Kuang-Yu Hsiao1,2
1a Department of Emergency Medicine , Chang Gung Memorial Hospital , Chiayi , Taiwan.
A new scoring system accurately predicts massive transfusion needs in patients with upper gastrointestinal bleeding (UGIB). This tool aids in early identification and resource mobilization for life-saving interventions.
Area of Science:
- Gastroenterology
- Hematology
- Critical Care Medicine
Background:
- Massive transfusion protocols are crucial for managing severe upper gastrointestinal bleeding (UGIB).
- Predictive tools for identifying patients needing massive transfusion in UGIB are lacking.
- Early identification facilitates timely interventions and resource allocation.
Purpose of the Study:
- To develop and validate a scoring system for predicting massive transfusion in UGIB patients.
- To improve patient care and resource management through early risk stratification.
- To address the gap in identifying patients requiring massive transfusion.
Main Methods:
- Defined massive transfusion as ≥10 units of red blood cells within 24 hours.
- Utilized a 10-year, six-hospital database for a developmental cohort (24,736 patients) and a validation cohort (27,449 patients).
- Applied logistic regression to derive and validate a risk score, assessing accuracy using the area under the receiver operating characteristic (AUROC) curve.
Main Results:
- Five factors independently predicted massive transfusion: band form >0, INR >1.5, shock (pulse >100 or SBP <100), hemoglobin <8.0 g/dL, and endoscopic therapy.
- The scoring system demonstrated high predictive accuracy in both developmental (AUROC: 0.831) and validation (AUROC: 0.822) cohorts.
- Approximately 3.9% of UGIB patients required massive transfusion.
Conclusions:
- The developed scoring system accurately predicts the need for massive transfusion in UGIB patients.
- This tool can enhance clinical decision-making and optimize patient management.
- The findings highlight the importance of early identification for life-saving interventions in severe UGIB.
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