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Group-Based Trajectory Models to Identify Sociodemographic and Clinical Predictors of Adherence Patterns to Statin Therapy Among Older Adults

机译:基于组的轨迹模型来识别老年人的他汀类药物治疗依从性的社会人口统计学和临床​​预测指标

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摘要

BackgroundThe benefits of statins in the prevention of primary and secondary atherosclerotic cardiovascular (CV) disease events have been well documented. Suboptimal adherence is a persistent problem associated with increased CV events and increased healthcare utilization. Proportion of days covered (PDC) is widely used to measure medication adherence, and provides a single value that does not adequately depict different adherence behavior patterns. Group-based trajectory modeling has been used to identify adherence patterns (or trajectories) over time. The identification of characteristics unique to each pattern can help in the early identification of patients who are likely to be poor adherents and can inform the development of interventions.
机译:背景他汀类药物在预防原发性和继发性动脉粥样硬化性心血管(CV)疾病中的益处已得到充分证明。不理想的依从性是一个持续存在的问题,与简历事件增加和医疗保健利用率增加有关。覆盖天数比例(PDC)被广泛用于衡量药物依从性,并且提供的单个值不足以描述不同的依从行为模式。基于组的轨迹建模已用于识别随时间推移的依从性模式(或轨迹)。识别每种模式独特的特征可以帮助及早发现依从性差的患者,并有助于制定干预措施。

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