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

医学 潜在类模型 总体表面积 急诊分诊台 星团(航天器) 标杆管理 重症监护医学 急诊医学 内科学 统计 数学 计算机科学 业务 营销 程序设计语言
作者
Jason Heard,Yuni Ren,Sandra L. Taylor,Soman Sen,Tina L. Palmieri,Kathleen S Romanowski,David Greenhalgh
出处
期刊:Journal of Burn Care & Research [Oxford University Press]
被引量:1
标识
DOI:10.1093/jbcr/irae186
摘要

Abstract Previous iterations of burn severity (mild, moderate, and severe) were not data-driven and were outdated. Clustering analyses have gained popularity for identifying homogenous subgroups from heterogeneous medical conditions, such as asthma, sepsis, and lung disease. There is no consensus in burn literature regarding what constitutes massive burns. The current classification includes a 20% total body surface area (TBSA) burn and a 95% TBSA burn as severe. Latent class and hierarchical clustering analyses were applied to the American Burn Association National Burn Research Dataset. Cluster variables included length of stay, length of stay, intensive care unit length of, number and type of procedures, and number and type of complications. Non-clustering variables were evaluated after clustering, including burned TBSA, inhalation injury, mortality, discharge disposition, age, sex, and race. Latent class analysis suggested three clusters. Hierarchical clustering analysis was applied to the most severe latent class, creating four total burn severity groups. In total, 112,297 patients were included in the final analysis. The mean TBSA burned for each class is 4.26±4.91 for minor, 8.07±8.39 for moderate, 22.76±17.31 for severe and 36.72±21.61 for massive. The age and sex proportions were similar among all clusters. The clustering variables steadily increased for each severity cluster. Mortality was the highest in the massive cluster (18.2%). Data informed categories of burn severity were formed using clustering analyses, which will be helpful for triage, data-benchmarking, and class-specific research.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
qly发布了新的文献求助10
1秒前
高兴采文发布了新的文献求助10
1秒前
完美世界应助lixiaofan采纳,获得10
1秒前
HRT发布了新的文献求助10
1秒前
nn完成签到 ,获得积分10
1秒前
超帅的鹏飞完成签到,获得积分10
1秒前
1秒前
xiuxiu发布了新的文献求助10
2秒前
朴素的从寒完成签到,获得积分10
2秒前
AUGKING27完成签到 ,获得积分10
2秒前
大个应助无聊的听双采纳,获得10
2秒前
JamesPei应助海带不背锅采纳,获得10
3秒前
H华ua应助fs采纳,获得10
3秒前
Soda8513完成签到,获得积分10
3秒前
周俊俊完成签到,获得积分20
4秒前
orixero应助slow采纳,获得10
4秒前
InaZheng发布了新的文献求助200
4秒前
4秒前
5秒前
5秒前
5秒前
5秒前
5秒前
lily完成签到 ,获得积分10
5秒前
那晚的风发布了新的文献求助10
6秒前
小小鱼发布了新的文献求助10
7秒前
alefa发布了新的文献求助10
8秒前
苗松完成签到,获得积分10
8秒前
doby发布了新的文献求助10
8秒前
三冬四夏完成签到,获得积分10
8秒前
guohuameike完成签到,获得积分10
9秒前
小梦给小梦的求助进行了留言
9秒前
TRIAL发布了新的文献求助10
9秒前
9秒前
温柔丹萱完成签到,获得积分10
9秒前
9秒前
清倾完成签到,获得积分10
9秒前
10秒前
nyddyy完成签到,获得积分10
10秒前
布莱德完成签到,获得积分20
10秒前
高分求助中
(应助此贴封号)【重要!!请各位详细阅读】【科研通的精品贴汇总】 10000
中国兽药产业发展报告 1000
International Finance: Theory and Policy. 12th Edition 1000
줄기세포 생물학 1000
Biodegradable Embolic Microspheres Market Insights 888
Quantum reference frames : from quantum information to spacetime 888
Pediatric Injectable Drugs 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4414309
求助须知:如何正确求助?哪些是违规求助? 3897381
关于积分的说明 12121978
捐赠科研通 3543002
什么是DOI,文献DOI怎么找? 1944334
邀请新用户注册赠送积分活动 984719
科研通“疑难数据库(出版商)”最低求助积分说明 881104