Efficacy of Decision Aids in The Use of Left Ventricular Assist Device in Patients With Advanced Heart Failure: A Systematic Review and Meta-Analysis of Randomized Control Trials

AMERICAN JOURNAL OF CARDIOLOGY(2024)

引用 0|浏览0
暂无评分
摘要
Although left ventricular assist device (LVAD) implantation can improve survival in patients with end-stage heart failure, it is not without risk. Numerous complications are possible, and durable support requires substantial lifestyle changes. The use of various knowledge-assessment tools may allow for more informed patient decisions. To synthesize the totality of the evidence, we conducted a systematic review and meta-analysis to summarize the efficacy of decision aid (DA) use in patients with advanced heart failure who are eligible for LVAD. Any randomized controlled trial (RCT) evaluating the efficacy of DAs in patients considering LVAD was eligible for inclusion. A complete search of EMBASE and PubMed was conducted from the start until June 8, 2023. The primary outcome was patients' LVAD knowledge. Data extraction was performed independently by 2 reviewers. Data were pooled using a random-effects model. Of the 575 references, 2 RCTs randomizing 490 patients were included in this study. DAs were associated with no significant change in LVAD knowledge (standardized mean difference 0.07, 95% confidence interval -0.24 to 0.39, p = 0.64) or decisional conflict (mean difference -1.48, 95% confidence interval -5.28 to 2.32, p = 0.45). The certainty of the evidence ranged from moderate to very low. The use of DAs in LVAD-eligible patients with advanced heart failure resulted in no difference in patients' knowledge of LVAD after LVAD education. The findings from this study will aid in the power analysis of a well-designed RCT to evaluate and encourage further investigation into the efficacy and relevance of DAs in preparing patients for a life with LVAD. (c) 2023 Elsevier Inc. All rights reserved. (Am J Cardiol 2024;211:255-258)
更多
查看译文
关键词
patient-centered decision-making,quality of life,LVAD,HFrEF
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要