Development of a hybrid decision support model for optimal ventricular assist device weaning.
Development of a hybrid decision support model for optimal ventricular assist device weaning.
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DOI：
10.1016/j.athoracsur.2010.03.073
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发表时间：
2010-09
影响因子：
4.6
通讯作者：
Antaki, James F.
中科院分区：
文献类型：
--
作者：
Santelices, Linda C.;Wang, Yajuan;Severyn, Don;Druzdzel, Marek J.;Kormos, Robert L.;Antaki, James F.
尽管接受心室辅助装置 (VAD) 支持的患者心脏恢复的证据虽少但很有希望，但识别和选择可能脱离 VAD 支持的候选人的标准尚未建立。临床决策支持系统（CDSS）是基于贝叶斯信念网络开发的，将专家知识与多变量分析相结合。专业知识来自对匹兹堡大学医学中心人工心脏项目 11 名成员的采访。 1996 年至 2004 年间所有考虑撤机的 VAD 患者 (n=19) 的回顾性临床数据对此进行了补充。采用人工神经网络和自然语言处理 (NLP) 来挖掘这些数据并提取 28 个最敏感的变量。比较了三种决策支持模型。该模型完全基于专家得出的知识，是最不准确且最保守的。它低估了心脏恢复的发生率：错误地将 4 名成功断奶的患者识别为移植候选者。该模型完全源自临床数据，表现较好，但错误地识别了两名患者：一名成功断奶，另一名最终需要心脏移植。专家数据混合模型表现最好，准确率为 94.74%，置信区间为 75.37% ~ 99.07%，仅错误识别了一名脱离支持的患者。 CDSS 可以促进和改善对适合心脏康复的 VAD 患者的识别，并可能从装置移除中受益。它有可能将活跃中心的成功转化为那些尚未建立的中心，从而扩大 VAD 疗法的利用。
Despite the small but promising body of evidence for cardiac recovery in patients that have received ventricular assist device (VAD) support, the criteria for identifying and selecting candidates who might be weaned from VAD support have not been established. A clinical decision support system (CDSS) was developed based on a Bayesian Belief Network that combined expert knowledge with multivariate analysis. Expert knowledge was derived from interviews of 11 members of the Artificial Heart Program at the University of Pittsburgh Medical Center. This was supplemented by retrospective clinical data from all VAD patients considered for weaning between 1996 and 2004 (n=19). Artificial Neural Networks and Natural Language Processing (NLP) were employed to mine these data and extract 28 most sensitive variables. Three decision support models were compared. The model, exclusively based on expert-derived knowledge, was the least accurate and most conservative. It under-estimated the incidence of heart recovery: incorrectly identifying 4 of the successfully weaned patients as transplant candidates. The model derived exclusively from clinical data performed better but mis-identified two patients: one who was successfully weaned, and one who ultimately needed a cardiac transplant. An expert-data hybrid model performed best, with 94.74% accuracy and 75.37% ~ 99.07% confidence interval, misidentifying only one patient who was weaned from support. A CDSS may both facilitate and improve the identification of VAD patients who are candidates for cardiac recovery, and may benefit from device removal. It could be potentially used to translate success of active centers to those less established and thereby expand utilization of VAD therapy.
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影响因子：
4.6
作者：
Hetzer, Roland;Potapov, Evgenij V.;Hennig, Ewald
通讯作者：
Hennig, Ewald
影响因子：
8.9
作者：
Gorcsan, J;Severyn, D;Kormos, RL
通讯作者：
Kormos, RL
影响因子：
37.8
作者：
Simon, MA;Kormos, RL;McNamara, DM
通讯作者：
McNamara, DM
影响因子：
7.5
作者：
Sakellaropoulos, GC;Nikiforidis, GC
通讯作者：
Nikiforidis, GC
DOI：
10.1197/jamia.m1184
发表时间：
2003-07-01
影响因子：
6.4
作者：
Fraser, HSF;Long, WJ;Naimi, S
通讯作者：
Naimi, S