基于药物坚持数据,对2型糖尿病患者进行分析
Rene Markovič1,2, Vladimir Grubelnik2, Tadej Završnik3,4
1Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia.
Frontiers in public health
|July 24, 2023
概括
针对2型糖尿病 (T2DM) 的患者概况显示了不同年龄组的不同药物使用模式. 早期和晚年年龄组表现出简单的个人资料,而中年人表现出与T2DM并发症相关的复杂模式.
科学领域:
- 内分泌学和糖尿病学
- 医疗信息学 医疗信息学
- 数据挖掘 数据挖掘
背景情况:
- 2型糖尿病 (T2DM) 是一种复杂的慢性疾病,影响多个器官.
- 患者分析对于识别有不良疾病进展的个体和量身定制疗法至关重要.
- 了解疾病阶段和药物使用是管理T2DM的关键.
研究的目的:
- 利用药物摄入量和实验室数据,发现不同的T2DM患者个人资料.
- 分析糖尿病患者在不同疾病阶段的进展情况.
- 为了确定个性化治疗策略的患者子组.
主要方法:
- 利用了大学医疗中心的20年的医疗记录.
- 使用ATC分类创建了针对患者的药物配置文件.
- 应用自然语言处理,数据挖掘和层次聚类.
主要成果:
- 确定了跨年龄组的结构良好的个人资料分布.
- 早期 (40-50岁) 和晚期 (80岁以上) 的年龄组显示只有两个不同的药物使用情况.
- 中年人群 (55-75) 呈现出与T2DM并发症相关的几个复杂的特征.
结论:
- 开发的分析方法可以广泛实施,并且具有成本效益.
- 随时可用的治疗和药物使用数据有助于获得全球分析的洞察力.
- 整合来自其他专业的数据可以提高T2DM患者个人资料的复杂性.
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