HYPERTENSION: PREDICTION OF BIOFEEDBACK SUCCESS

高血压：生物反馈成功的预测

基本信息

批准号：
6497447
负责人：
CAROLYN B YUCHA
金额：
$ 25.37万
依托单位：
UNIVERSITY OF FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2000
资助国家：
美国
起止时间：
2000-02-01 至 2004-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6497447
关键词：
alternative medicine behavior prediction behavioral /social science research tag biofeedback cardiovascular disorder therapy cardiovascular function circadian rhythms clinical research furosemide human subject hypertension locus of control muscle tension patient care planning prognosis therapy compliance

项目摘要

In the next century, our health care system will attempt to manage chronic illness in the largest aging population ever known. Non-adherence to pharmacological therapy and to non- pharmacological therapy will prove very costly. Hypertension, present in more than 50 million Americans, increases the risk of cardiovascular disease and its assoicated morbidity and mortality. Thus it is critical that adherence to treatment of hypertension be increased. While medications are effective in certain patients, their adverse effects make compliance with treatment difficult to ensure. In addition, more and more persons are turning to alternative medicine to deal with their health problems. Biofeedback offers an alternative to medical treatment, having been shown to reduce both systolic and diastolic blood pressures and/or allow the reduction of antihypertensive medications in some patients, while having no adverse effects. Yet biofeedback therapy is time-intensive and technician-intensive. Therefore, it is critical to be able to predict which patients with essential hypertension are most likely to lower his/her blood pressure using these techniques. This research proposes to test three different means of predicting whether a hypertensive subject will or will not be successful in lowering his/her blood pressure using biofeedback. Specifically, the first set of predictive criteria to be tested is that proposed by Weaver and McGrady (1995). This model is derived from five variables: heart rate, finger temperature, forehead muscle tension, plasma renin response to furosemide, and mean arterial pressure response to furosemide. The second prediction model is based on the magnitude of circadian variations in blood pressure as measured by 24-hour ambulatory blood pressure monitoring. The third prediction model is based on locus of control of behavior. A total of 60 hypertensive subjects will be studied over a three-year period. The results of this study will enable those caring for hypertensive persons to recommend treatment (i.e., biofeedback) in an individualized way, thereby promoting adherence.

在下个世纪，我们的医疗保健系统将尝试管理有史以来最大的老龄化人口中的慢性疾病。不坚持药物治疗和非药物治疗将被证明代价高昂。超过 5000 万美国人患有高血压，它增加了心血管疾病及其相关发病率和死亡率的风险。因此，提高高血压治疗的依从性至关重要。虽然药物对某些患者有效，但其副作用使得难以确保治疗的依从性。此外，越来越多的人开始寻求替代医学来解决健康问题。生物反馈提供了药物治疗的替代方案，已被证明可以降低收缩压和舒张压和/或允许减少某些患者的抗高血压药物，同时没有副作用。然而，生物反馈疗法是时间密集型和技术密集型的。因此，能够预测哪些原发性高血压患者最有可能使用这些技术降低血压至关重要。这项研究打算测试三种不同的方法来预测高血压受试者是否会利用生物反馈成功降低血压。具体来说，要测试的第一组预测标准是 Weaver 和 McGrady (1995) 提出的。该模型源自五个变量：心率、手指温度、前额肌肉张力、血浆肾素对速尿的反应以及平均动脉压对速尿的反应。第二个预测模型基于通过 24 小时动态血压监测测量的血压昼夜变化幅度。第三个预测模型基于行为控制源。将在三年内对总共 60 名高血压受试者进行研究。这项研究的结果将使高血压患者的护理人员能够以个体化的方式推荐治疗（即生物反馈），从而促进依从性。