ICP Elevation Alerting Based on a Predictive Model Hosting Platform

描述（由申请人提供）：在重度脑损伤患者中，经常发生急性颅内压升高，且不可预测。颅内压升高可引起脑缺血，如果不治疗可导致致命的脑疝。因此，及时识别和治疗颅内压升高是管理重型脑损伤患者的关键。然而，大多数神经重症监护病房中的现有协议是反应性的，其中床边护士响应于简单的阈值交叉警报，必须检查监护仪上ICP的数字显示，以在开始治疗之前手动确定警报是否为真实警报。急性ICP升高伴有独特的ICP脉冲形态学改变。通过利用ICP脉冲形态学指标作为输入，我们可以准确地识别ICP升高的前兆，以提醒护士，并使他们免于确定一致的ICP升高是否触发警报的认知要求过程。因此，我们建议在开源模型托管平台上部署先前开发的准确ICP升高预测模型，以监测连续ICP信号并提醒床边护士。使用这个警报系统，我们将进一步研究与急性ICP升高相关的主要生理异常，在升高发生之前显示不同的间接ICP模式。本研究的目的有三：1）开发一个基于模型托管平台的颅内压升高预警系统; 2）研究颅内压预警系统是否能帮助护士更有效地管理颅内压。3)检测与急性ICP升高相关的一致生理异常。我们的长期目标是推进重症监护监测，以便充分探索来自监护仪的连续信号，并将其与电子病历（EMR）系统中的其余临床数据相结合，以增强临床决策。该项目代表了一种基于平台的方法，旨在克服阻碍在护理点提供高级预测分析的转化障碍。因此，该项目的广泛影响与未来利用该开放模型托管平台以促进其他ICU中其他预测模型的翻译的努力有关。

DESCRIPTION (provided by applicant): Recurring acute ICP elevations occur frequently and unpredictably among severe brain injury patients. ICP elevation can cause cerebral ischemia and lead to deadly brain herniation if untreated. Hence, prompt recognition and treatment of rising ICP are critical in managing severe brain injury patients. However, existing protocols in most neurocritical care units are reactive where bedside nurses, in response to simple threshold-crossing alarms, have to check numerical display of ICP on monitors to manually establish whether the alarm is a true one before initiating treatment. Acute ICP elevation is accompanied by distinctive ICP pulse morphological changes. By utilizing ICP pulse morphological metrics as input, we can accurately recognize precursors to ICP elevation to alert nurses and free them from a cognitively demanding process of establishing whether a consistent ICP elevation triggers the alarm. We therefore propose to deploy a previously developed accurate ICP elevation prediction model on an open-source model hosting platform to monitor continuous ICP signals and alert bedside nurses. Using this alerting system, we will further investigate the principal physiological abnormalities associated with acute ICP elevation showing different precursory ICP patterns prior to onset of elevation. We will pursue the following three aims: 1) To develop an alerting system for ICP elevation based on a model hosting platform; 2) To investigate whether the ICP alerting system helps nurses more efficiently manage ICP. 3) To detect consistent physiological abnormalities associated with acute ICP elevation. Our long-term goal is to advance intensive care monitoring so that continuous signals from monitors are fully explored to integrate with the rest of clinical data in an electronic medical record (EMR) system to enhance clinical decision making. This project represents an effort piloting a platform-based approach towards overcoming translational barriers that impede the process of making advanced predictive analytics available at point of care. Therefore, broad impacts from this project are related to future efforts at leveraging this open model hosting platform to facilitate the translation of additional predictive models in other ICUs.