通过无监督集群和潜伏类分析评估严重烧伤患者的临床异质性和预测死亡率
Sungmin Kim1, Jaechul Yoon1, Dohern Kym2,3
1Department of Surgery and Critical Care, Burn Center, Hangang Sacred Heart Hospital, Hallym University Medical Center, College of Medicine, Hallym University, 12, Beodeunaru-ro 7-gil, Youngdeungpo-gu, Seoul, 07247, Korea.
Scientific reports
|August 21, 2023
概括
对烧伤患者的生物标志物分析显示,随着时间的推移,不同的死亡率预测因素. 早期的乳酸表明缺氧,而晚些时候的血小板和淋巴细胞水平表明败血症,指导个性化烧伤护理.
科学领域:
- 生物标志物 生物标志物
- 临床异质性 临床异质性
- 患者的分层是患者的分层.
背景情况:
- 严重的烧伤伤害呈现出显著的临床异质性和不良预后.
- 聚类算法可以识别具有类似疾病轨迹的患者子组.
- 了解生物标志物模式有助于预测烧伤患者的结果.
研究的目的:
- 分析常规收集的生物标志物,以预测烧伤患者的死亡率.
- 为了确定临床亚型,并为严重烧伤的治疗决策提供信息.
- 利用无监督学习来深入了解燃烧病原性.
主要方法:
- 成年烧伤患者的回顾性队列研究 (2010-2021年).
- 使用集群算法和潜在类分析分析的生物标记数据.
- 患者被分为四个每周入院的子组进行时间分析.
主要成果:
- 红细胞分布宽度,碳酸盐,pH,血小板和淋巴细胞与死亡风险相关.
- 在死亡风险最高的群体中发现的pH,血小板,淋巴细胞,乳酸和白蛋白的最低水平.
- 特定的生物标志物 (乳酸盐,pH,淋巴细胞,血小板,白蛋白) 显示了对死亡率的时间依赖预测值.
结论:
- 常规收集的生物标志物和集群分析提供了有关烧伤异质性的见解.
- 生物标志物模式可以改善预测烧伤患者的疾病进展和死亡率.
- 特定时间的生物标志物 (乳酸盐,血小板,淋巴细胞,白蛋白,pH) 可以指导量身定制的治疗策略.
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