Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge
Predicting acute hypotensive episodes: The 10th annual PhysioNet/Computers in Cardiology Challenge
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发表时间：
2010-04
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通讯作者：
G. Moody;LH Lehman
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作者：
G. Moody;LH Lehman
今年的心脏病学物理网络/计算机挑战赛旨在促进开发识别面临急性低血压发作(AHE)迫在眉睫风险的重症监护病房(ICU)患者的方法，以改善这些患者的护理和存活的可能性。参与者被要求在两组来自MIMIC II数据库的ICU患者记录中提前一小时预测AHE的发生，这些数据包括至少10小时的生理波形、时间序列以及在一小时预测窗口之前的伴随临床数据。在事件1中，在接受降压药物治疗的10名高危患者中，大多数参与者能够正确识别，其中5名患者在预测窗口期间经历了AHES。在事件2中，参与者能够正确地将40名患者中的多达37名(93%)进行正确分类，其中包括几乎所有经历过AHES的患者。
This year's PhysioNet/Computers in Cardiology Challenge aimed to stimulate development of methods for identifying intensive care unit (ICU) patients at imminent risk of acute hypotensive episodes (AHEs), motivated by the possibility of improving care and survival of these patients. Participants were asked to forecast the occurrence of an AHE up to an hour in advance, in two groups of ICU patient records from the MIMIC II Database, drawing on data that included at least 10 hours of physiologic waveforms, time series, and accompanying clinical data prior to the one-hour forecast window. In event 1, most participants were able to identify without errors, in a group of 10 high-risk patients receiving pressor medication, which five of the patients experienced AHEs during the forecast window. In event 2, participants were able to classify correctly as many as 37 (93%) of a diverse group of 40 patients, including nearly all of those who experienced AHEs.