Data-driven discovery of a novel sepsis pre-shock state predicts impending septic shock in the ICU
Data-driven discovery of a novel sepsis pre-shock state predicts impending septic shock in the ICU
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DOI：
10.1038/s41598-019-42637-5
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发表时间：
2019-04-16
影响因子：
4.6
通讯作者：
Winslow, Raimond L.
中科院分区：
文献类型：
--
作者：
Liu, Ran;Greenstein, Joseph L.;Winslow, Raimond L.
感染性休克是一种危及生命的疾病，及时治疗可大大降低死亡率。因此，对脓毒症患者进行可靠的识别，这些患者发生脓毒性休克的风险升高，有可能通过打开早期干预窗口来挽救生命。我们假设存在一种新的脓毒症临床状态，称为“休克前”状态，并且进入这种状态的脓毒症患者极有可能在未来某个时间发展为脓毒性休克。我们将三种不同的机器学习技术应用于MIMIC-III数据库中15，930名患者的电子健康记录数据，以验证这一假设。这种新的范例在识别将进展为脓毒性休克的脓毒症患者方面产生了改进的性能，如脓毒症-3标准所定义的，最佳方法实现了0.93的受试者工作曲线下面积，88%的灵敏度，84%的特异性和7小时的中位预警时间。此外，我们引入了患者特异性阳性预测值的概念，为个体预测分配置信度，并实现高达91%的值。这项研究表明，早期预测即将发生的脓毒性休克，从而早期干预，是可能的提前数小时。
Septic shock is a life-threatening condition in which timely treatment substantially reduces mortality. Reliable identification of patients with sepsis who are at elevated risk of developing septic shock therefore has the potential to save lives by opening an early window of intervention. We hypothesize the existence of a novel clinical state of sepsis referred to as the "pre-shock" state, and that patients with sepsis who enter this state are highly likely to develop septic shock at some future time. We apply three different machine learning techniques to the electronic health record data of 15,930 patients in the MIMIC-III database to test this hypothesis. This novel paradigm yields improved performance in identifying patients with sepsis who will progress to septic shock, as defined by Sepsis- 3 criteria, with the best method achieving a 0.93 area under the receiver operating curve, 88% sensitivity, 84% specificity, and median early warning time of 7 hours. Additionally, we introduce the notion of patient-specific positive predictive value, assigning confidence to individual predictions, and achieving values as high as 91%. This study demonstrates that early prediction of impending septic shock, and thus early intervention, is possible many hours in advance.