同病症社会经济集群与通过无监督机器学习获得的晚发性的死亡率的关联
Colin B Josephson1, Arturo Gonzalez-Izquierdo2, Jordan D T Engbers3
1Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada; Centre for Health Informatics, University of Calgary, Calgary, AB, Canada.
Seizure
|August 3, 2023
概括
晚发性呈现出多样化的患者个人资料,具有不同的死亡风险. 识别这些群体,如痴呆症和脑瘤,对于理解独特的预后轨迹和改善患者的治疗结果至关重要.
科学领域:
- 神经学 神经学
- 老年病的医生 老年病的医生
- 公共卫生 公共卫生
背景情况:
- 晚发性 (LOE) 是一种复杂的疾病,原因多种多样,死亡风险增加.
- 具体的多病态社会经济特征及其对LOE预后的影响仍然未得到充分研究.
研究的目的:
- 在晚发性患者群体中识别不同的表型集群.
- 确定这些集群是否表现出独特的过早死亡风险.
主要方法:
- 使用英国电子健康记录和生命统计数据 (1998-2019) 的回顾性队列研究.
- 确定了事件LOE病例 (年龄≥65岁),并与对照进行了匹配.
- 应用了等级分类来定义多病症社会经济概况,并分析死亡风险.
主要成果:
- 确定了1048个LOE病例,并与10259个对照进行了匹配.
- LOE与1.73倍的过早死亡风险增加有关.
- 确定了十个表型集群,其中"痴呆和焦虑" (HR 5.36) 和"脑瘤" (HR 4.97) 显示出明显增加的死亡风险.
结论:
- 晚发性包括不同的表型群,具有量化可定义的形状.
- 这些群体及其并发症显著影响过早死亡率,超过了基线风险.
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