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Integrated Compensatory Responses in a Human Model of Hemorrhage
Published on: November 20, 2016
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APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES.
Jonathan D Stallings1, Srinivas Laxminarayan, Chenggang Yu
1US Army Institute of Surgical Research, Fort Sam Houston, Texas.
Shock (Augusta, Ga.)
|June 19, 2023
Summary
An artificial intelligence algorithm, APPRAISE-Hemorrhage Risk Index (HRI), can analyze vital signs to identify trauma patients at high risk of hemorrhage. This AI tool aids medics in optimizing triage and treatment decisions for battlefield casualties.
Area of Science:
- Trauma care
- Artificial intelligence in medicine
- Emergency medicine
Background:
- Hemorrhage is a leading cause of battlefield mortality.
- Effective triage of trauma patients is critical for survival.
- Current methods may not optimally identify high-risk hemorrhage patients early.
Purpose of the Study:
- To assess an artificial intelligence (AI) algorithm for analyzing vital signs.
- To stratify hemorrhage risk in trauma patients automatically.
- To develop the APPRAISE-Hemorrhage Risk Index (HRI) algorithm.
Main Methods:
- Developed the APPRAISE-Hemorrhage Risk Index (HRI) algorithm using vital signs (heart rate, blood pressures).
- Utilized an AI-based linear regression model on preprocessed vital-sign data.
- Trained and tested the algorithm on 1,659 trauma patients (540 hours of data).
Main Results:
- The APPRAISE-HRI algorithm stratified patients into low (HRI:I), average (HRI:II), and high (HRI:III) risk categories.
- High-risk patients (HRI:III) were 5.75 times more likely to experience hemorrhage.
- Low-risk patients (HRI:I) were significantly less likely to hemorrhage compared to the average trauma population.
Conclusions:
- The APPRAISE-HRI algorithm offers a novel method for evaluating vital signs.
- It can alert medical personnel to casualties with the highest hemorrhage risk.
- Optimizes decision-making for triage, treatment, and evacuation in critical care settings.
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