在门诊护理中对SGLT-2抑制剂的坚持影响因素的预测建模:从处方索赔的洞察力 数据分析 数据分析
Nadia Khartabil1, Candis M Morello2, Etienne Macedo3
1Center of Graduate Studies, West Coast University, Los Angeles, CA 90004, USA.
Pharmacy (Basel, Switzerland)
|April 26, 2024
概括
在患有2型糖尿病,心力衰竭或慢性病的患者中,可以预测对-葡萄糖共运输体2抑制剂 (SGLT2i) 的坚持. 一个决策树模型确定了糖化血红蛋白,年龄,性别和保险作为SGLT2i坚持的关键预测因素.
科学领域:
- 药理学和治疗学 药理学和治疗学
- 慢性疾病管理中的现实世界证据
- 卫生信息学和预测建模
背景情况:
- -葡萄糖携带载体2抑制剂 (SGLT2i) 为患有2型糖尿病 (T2D),心力衰竭 (HF) 和慢性病 (CKD) 的患者提供心血管和代谢益处.
- 现实世界数据有限,可以预测SGLT2i在门诊环境中的坚持.
- 了解坚持预测因素对于优化治疗结果至关重要.
研究的目的:
- 使用电子健康记录开发和验证SGLT2i遵守的预测模型.
- 确定影响SGLT2i遵守的关键人口,临床和保险相关因素.
- 评估坚持对血糖控制和功能的影响.
主要方法:
- 在2020年1月至2021年4月期间,在加州大学圣地亚哥卫生部对174名成年患者进行了SGLT2i的回顾性研究.
- 通过覆盖日数比例 (PDC) 测量依从性.
- 采用简单的决策树模型,分析了21个变量,包括HbA1c,GFR,年龄,性别,种族/种族和保险计划.
主要成果:
- 决策树模型实现了 74% 和 82% 的曲线下面面积 (AUC) 准确度.
- 遵守的关键预测因素包括糖化血红蛋白 (HbA1c),年龄,性别和保险计划支付金额.
- 坚持是与HbA1c成反比例的,与计划支付金额成正比的. 不符合标准的患者HbA1c较高,EGFR较低.
结论:
- 一个简单的决策树模型有效预测SGLT2i在门诊患者的坚持.
- 预测模型可以帮助临床医生识别有风险的患者,并定制干预措施以改善遵守.
- 优化SGLT2i坚持对于有效管理T2D,HF和CKD至关重要.
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