Burn Injury Severity in Adults: Proposed Definitions Based on the National Burn Research Dataset

Area of Science:

• Trauma Surgery
• Medical Informatics
• Data Science in Medicine

Background:

• Current burn severity classifications lack data-driven validation and are outdated.
• There is no established consensus on defining massive burns in medical literature.
• Existing categories, like severe burns, encompass a wide range (20%–95% total body surface area).

Purpose of the Study:

• To develop data-driven, objective categories for burn severity.
• To refine the classification of burn severity beyond traditional mild, moderate, and severe.
• To establish a more precise framework for burn patient management and research.

Main Methods:

• Latent class and hierarchical clustering analyses were performed on the American Burn Association National Burn Research Dataset.
• Clustering utilized variables such as length of stay, procedures, and complications.
• Burned total body surface area (TBSA), mortality, and other clinical factors were analyzed post-clustering.

Main Results:

• Four distinct burn severity groups were identified: minor, moderate, severe, and massive.
• Mean TBSA burned increased progressively across the groups (Minor: 4.26%, Moderate: 8.07%, Severe: 22.76%, Massive: 36.72%).
• Mortality rates were highest in the massive burn severity cluster (18.2%).

Conclusions:

• Clustering analyses provide a robust, data-informed approach to classifying burn severity.
• These new categories offer improved utility for clinical triage, data benchmarking, and targeted research.
• The findings necessitate a re-evaluation of current burn severity classifications.