机器学习在患有炎症性肠病的死者中识别了多病症集群
Gemma Postill1,2,3,4,5, Vinyas Harish1,2,5, Ijeoma Uchenna Itanyi5,6
1Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
患有炎症性肠病 (IBD) 的人在死亡前会经历更复杂的多病症. 确定了三种不同的并发症集群,为IBD患者提供个性化护理策略.
科学领域:
- 医学研究 医学研究
- 公共卫生 公共卫生
- 数据科学是数据科学.
背景情况:
- 多病症,多种慢性疾病的存在,影响以患者为中心的护理.
- 了解炎症性肠病 (IBD) 中的多病态模式至关重要.
研究的目的:
- 确定IBD患者死亡前的多病症模式.
- 在临终期IBD患者中发现不同类型的并发症.
主要方法:
- 以人口为基础的回顾性队列研究,使用加拿大安大略省 (2010-2020) 的链接卫生行政数据.
- 与IBD和没有IBD的个体之间的多病性累积的比较.
- 无监督的机器学习来识别多病症集群.
主要成果:
- 患有IBD的死者表现出更高的复杂多发病率 (42%与8+条件的34%相比).
- 在IBD患者死亡时常见的并发症包括关节炎 (77%),高血压 (73%) 和情绪障碍 (69%).
- 确定了三个稳定的多发病群:情绪障碍/关节炎,癌症/低多发病率和心血管并发病.
结论:
- 研究结果突出显示,临死IBD患者复杂多病症增加.
- 已识别的集群可以指导研究,临床指导方针和针对不同IBD亚组的护理计划.
- 结果支持个性化护理方法来管理IBD的并发症.
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