QUALITY OF LIFE OUTCOMES >= 5 YRS POST HEART TRANSPLANT

这项为期5年的前瞻性纵向研究的目的是确定 与成人的六个结果相关并预测其结果的变量 心脏移植(HT)后5~10年。六人组 结果是生存，功能能力，情绪状态，工作能力， 对HT的满意度，以及对生活质量的感知。具体的研究目标是 (1)确定人口、生理和心理社会方面的差异 随着时间的推移，因素同时与以下六个结果的差异有关 时间(2)确定人口统计、生理和心理社会预测因素 六种结果(3)检查身体和心理社会因素是如何 与六个结果相关的纵向变化(4)，以检查影响 年龄、性别、种族/民族背景和心脏移植术后并发症对预后的影响 随着时间的推移和(5)检查使用各种统计方法的效果 用于处理丢失的数据，以提高预测的准确性 结果。 将采用前瞻性的纵向设计。数据将是 从5年开始每6个月收集一次，至移植后10年。 入选标准是(1)=5年后(2)年龄=21岁(3)能够 读写英语，以及(4)身体上能够参与。患者会 完成一本仪器手册，就可以收集海图数据。变量 要衡量的因素包括人口统计变量(例如年龄、性别、种族和 婚姻状况)、身体变量(例如病史，用药，锻炼 测试和并发症)，以及心理社会变量(例如感知健康 状态、压力、应对和社会支持)和六个结果变量 (在压力、评估和应对模式下)。统计分析将 包括用于重复测量纵向、多变量回归方法 以及结果的参数建模。与健康相关的影响。 这些数据将提供有关(1)长期收益与风险的信息 高血压，(2)有不良预后风险的患者，(3)和干预的目标 改善结果。

The purpose of this 5 years prospective, longitudinal study is to identify variables that are associated with and predict six outcomes of adult patients at 5 years to 10 years after heart transplantation (HT). The six outcomes are survival, functional ability, emotional status, work ability, satisfaction with HT, and perceived quality of life. Specific study aims are (1) to determine how variance in demographic, physical, and psychosocial factors over time is concurrently related to variance in the six outcomes over time (2) to identify demographic, physical, and psychosocial predictors of the six outcomes (3) to examine how physical and psychosocial factors that are related to the six outcomes change longitudinally (4) to examine the impact of age, gender, racial / ethnic background, and complications after HT on outcomes over time and (5) to examine the effect of using various statistical methods for handling missing data in order to improve the accuracy of prediction of outcomes. A prospective, longitudinal design will be used. Data will be collected every 6 months beginning at 5 years through 10 years after HT. Inclusion criteria are (1) >= 5 years post HT (2) age >= 21 years (3) able to read and write English, and (4) physically able to participate. Patients will complete a booklet of instruments, and chart data will be gathered. Variables to be measured include demographic variables (ex. age, gender, race, and marital status), physical variables (ex. medical history, medications, exercise testing, and complications), and psychosocial variables (ex. perceived health status, stress, coping, and social support), and the six outcome variables (within a stress, appraisal, and coping model). Statistical analyses will include longitudinal, multi-variable regression methods for repeated measures and parametric modeling of outcomes. Health-Related Implications. These data will provide information regarding (1) long-term benefits versus risks of HT, (2) patients at risk for poor outcomes, (3) and targets for interventions to improve outcomes.