Cardiac Health Risk Stratification System (CHRiSS): a Bayesian-based decision support system for left ventricular assist device (LVAD) therapy.
Cardiac Health Risk Stratification System (CHRiSS): a Bayesian-based decision support system for left ventricular assist device (LVAD) therapy.
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DOI：
10.1371/journal.pone.0111264
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Antaki JF
中科院分区：
文献类型：
--
作者：
Loghmanpour NA;Druzdzel MJ;Antaki JF
本研究调查了贝叶斯网络（BN）用于左心室辅助装置（LVAD）治疗的使用;在过去十年中，这种治疗终末期心力衰竭的方法一直在稳步增长。尽管有这种增长，每年进行的LVAD植入的数量仍然是可能从这种治疗中受益的估计患者人群的一小部分。我们认为，这表明需要一个准确的分层工具，可以帮助确定LVAD候选人在最适当的点，在他们的疾病过程中。我们利用机械辅助循环支持跨机构登记（INTERMACS）数据库推导BN，以预测5个终点的死亡率：该数据库包含自2006年至今收集的来自153家医院研究中心的12，000多名入组患者，包括约230个植入前临床变量。采用合成少数超抽样技术（SMOTE）解决阴性结局患者比例不均的问题，并提高模型的性能。预测死亡率的准确度和ROC曲线下面积（%）为30天：94.9和92.5; 90天：84.2和73.9; 6个月：78.2和70.6; 1年：73.1和70.6; 2年：71.4和70.8。为了促进这些模型转化为临床实践，它们已被纳入基于网络的应用程序，心脏健康风险分层系统（CHRiSS）。随着LVAD治疗的临床经验不断增加，以及收集更多数据，我们的目标是不断更新这些BN模型，以提高其准确性并保持其相关性。正在进行的工作还旨在扩展BN模型，以预测LVAD植入后不良事件的风险，作为决策时考虑的额外因素。
This study investigated the use of Bayesian Networks (BNs) for left ventricular assist device (LVAD) therapy; a treatment for end-stage heart failure that has been steadily growing in popularity over the past decade. Despite this growth, the number of LVAD implants performed annually remains a small fraction of the estimated population of patients who might benefit from this treatment. We believe that this demonstrates a need for an accurate stratification tool that can help identify LVAD candidates at the most appropriate point in the course of their disease. We derived BNs to predict mortality at five endpoints utilizing the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) database: containing over 12,000 total enrolled patients from 153 hospital sites, collected since 2006 to the present day, and consisting of approximately 230 pre-implant clinical variables. Synthetic minority oversampling technique (SMOTE) was employed to address the uneven proportion of patients with negative outcomes and to improve the performance of the models. The resulting accuracy and area under the ROC curve (%) for predicted mortality were 30 day: 94.9 and 92.5; 90 day: 84.2 and 73.9; 6 month: 78.2 and 70.6; 1 year: 73.1 and 70.6; and 2 years: 71.4 and 70.8. To foster the translation of these models to clinical practice, they have been incorporated into a web-based application, the Cardiac Health Risk Stratification System (CHRiSS). As clinical experience with LVAD therapy continues to grow, and additional data is collected, we aim to continually update these BN models to improve their accuracy and maintain their relevance. Ongoing work also aims to extend the BN models to predict the risk of adverse events post-LVAD implant as additional factors for consideration in decision making.
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