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预测基于中心的心脏康复项目使用情况的因素

Factors Predicting the Utilization of Center-Based Cardiac Rehabilitation Program.

作者信息

Young Lufei, Zhang Qi, Lian Eric, Roberts Kimberly, Weintraub Neal, Dong Yanbin, Zhu Haidong, Xu Hongyan, Schafer Pascha, Dunlap Stephanie

机构信息

College of Nursing, Augusta University, Augusta, GA 30912, USA.

The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China.

出版信息

Geriatrics (Basel). 2020 Sep 28;5(4):66. doi: 10.3390/geriatrics5040066.

Abstract

Although cardiac rehabilitation (CR) is clearly beneficial to improving patients' physical functioning and reducing heart disease progression, significant proportions of patients do not complete CR programs. To evaluate the prevalence and predictors of completion of a center-based CR program in eligible cardiac patients, existing data collected from electronic medical records were used. To identify the predictors of CR completion, we used principal components analysis (PCA) and an artificial neural network (ANN) module. Among 685 patients, 61.4% ( = 421) completed the program, 31.7% ( = 217) dropped out, and 6.9% ( = 47) were referred but failed to initiate the program. PCA was conducted to consolidate baseline data into three factors-(1) psychosocial factors (depression, anxiety, and quality of life), (2) age, and (3) BMI, which explained 66.8% of the total variance. The ANN model produced similar results as the PCA. Patients who completed CR sessions had greater extremity strength and flexibility, longer six-minute walk distance, more CR knowledge, and a better quality of life. The present study demonstrated that patients who were older, obese, and who had depression, anxiety, or a low quality of life were less likely to complete the CR program.

摘要

尽管心脏康复(CR)对改善患者身体机能和减缓心脏病进展显然有益,但仍有相当比例的患者未完成CR项目。为评估符合条件的心脏病患者完成基于中心的CR项目的患病率及预测因素,我们使用了从电子病历中收集的现有数据。为确定CR完成情况的预测因素,我们采用了主成分分析(PCA)和人工神经网络(ANN)模块。在685例患者中,61.4%(n = 421)完成了该项目,31.7%(n = 217)退出,6.9%(n = 47)被转诊但未启动该项目。进行主成分分析以将基线数据整合为三个因素:(1)心理社会因素(抑郁、焦虑和生活质量)、(2)年龄和(3)体重指数,这三个因素解释了总方差的66.8%。人工神经网络模型得出了与主成分分析相似的结果。完成CR疗程的患者四肢力量和灵活性更强,6分钟步行距离更长,对CR的了解更多,生活质量更高。本研究表明,年龄较大、肥胖以及患有抑郁、焦虑或生活质量较低的患者完成CR项目的可能性较小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32b6/7709641/158afc61f6e7/geriatrics-05-00066-g001.jpg

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