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首页> 外文期刊>Patient Preference and Adherence >Electronically monitored medication adherence predicts hospitalization in heart failure patients
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Electronically monitored medication adherence predicts hospitalization in heart failure patients

机译：电子监测的药物粘附预测心力衰竭患者的住院治疗

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Background: Hospitalization contributes enormously to health care costs associated with heart failure. Many investigators have attempted to predict hospitalization in these patients. None of these models has been highly effective in prediction, suggesting that important risk factors remain unidentified.Purpose: To assess prospectively collected medication adherence, objectively measured by the Medication Event Monitoring System, as a predictor of hospitalization in heart failure patients.Materials and methods: We used recently developed adaptive modeling methods to describe patterns of medication adherence in a sample of heart failure patients, and tested the hypothesis that poor medication adherence as determined by adaptive methods was a significant predictor of hospitalization within 6 months.Results: Medication adherence was the best predictor of hospitalization. Besides two dimensions of poor adherence (adherence pattern type and low percentage of prescribed doses taken), four other single factors predicted hospitalization: low hemoglobin, depressed ejection fraction, New York Heart Association class IV, and 12 or more medications taken daily. Seven interactions increased the predictive capability of the model: 1) pattern of poor adherence type and lower score on the Letter–Number Sequencing test, a measure of short-term memory; 2) higher number of comorbid conditions and higher number of daily medications; 3) higher blood urea nitrogen and lower percentage of prescribed doses taken; 4) lower hemoglobin and much worse perceived health compared to last year; 5) older age and lower score on the Telephone Interview of Cognitive Status; 6) higher body mass index and lower hemoglobin; and 7) lower ejection fraction and higher fatigue. Patients with none of these seven interactions had a hospitalization rate of 9.7%. For those with five of these interaction risk factors, 100% were hospitalized. The C-index (the area under the receiver-operating characteristics [ROC] curve) for the model based on the seven interactions was 0.83, indicating excellent discrimination.Conclusion: Medication adherence adds important new information to the list of variables previously shown to predict hospitalization in adults with heart failure.
机译：背景：住院治疗极大地促进与心力衰竭相关的医疗保健费用。许多调查人员试图预测这些患者的住院病。这些模型中没有一个在预测方面都是非常有效的，这表明重要的风险因素仍未确定.Purpose：评估预期收集的药物粘附，客观地由药物事件监测系统测量，作为心力衰竭患者住院治疗的预测因子。材料和方法：我们使用最近开发了适应性建模方法来描述心力衰竭患者样本中的药物粘附模式，并测试了通过自适应方法确定的糟糕药物依从性的假设是在6个月内为住院的重要预测因子。结果：药物遵守住院的最佳预测因子。除了粘附不良的两个维度（粘附模式类型和所得的规定剂量的低百分比），还有四种其他单一因素预计住院治疗：低血红蛋白，抑郁的喷射部分，纽约心脏关联等级，每日12种或更多种药物。七个相互作用提高了模型的预测能力：1）粘附型差的模式和较低分数对字母号测序试验，短期记忆的衡量标准; 2）较高数量的合并条件，每日药物数量增加; 3）血尿尿素氮和较低百分比的规定剂量; 4）与去年相比，低血红蛋白和更糟糕的感知健康; 5）老年人和电话采访认知状态的电话面试; 6）更高的体重指数和低血红蛋白; 7）降低喷射分数和更高的疲劳。患有这七个相互作用的患者的住院率为9.7％。对于其中五种互动危险因素的人，100％住院。基于七个交互的模型的模型（接收器运行特性[Roc]曲线下的区域）的C折射率为0.83，表明良好的辨别。结论：组织遵守将重要的新信息添加到先前显示的变量列表中心力衰竭的成年人住院治疗。

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