ICP Elevation Alerting Based on a Predictive Model Hosting Platform

描述(由申请人提供)：在重型脑损伤患者中，反复发生的急性颅内压升高是频繁且不可预测的。如果不治疗，颅内压升高可能会导致脑缺血，并导致致命的脑突出症。因此，及时认识和处理颅内压升高对重型颅脑损伤患者的治疗至关重要。然而，大多数神经重症监护病房的现有方案是反应性的，床边护士在开始治疗之前，必须检查监护仪上的ICP数字显示，以手动确定警报是否为真的。急性颅内压升高伴有明显的颅内压脉搏形态改变。通过使用颅内压脉搏形态指标作为输入，我们可以准确地识别颅内压升高的前兆，以提醒护士，并将他们从确定一致的颅内压升高是否触发警报的认知要求的过程中解放出来。因此，我们建议在一个开源模型托管平台上部署一个先前开发的准确的颅内压升高预测模型，以监测连续的颅内压信号并提醒床边护士。利用这个警报系统，我们将进一步研究与急性颅内压升高相关的主要生理异常，在升高开始之前表现出不同的前驱颅内压模式。我们将追求以下三个目标：1)开发一个基于模型托管平台的颅内压升高警报系统；2)调查该警报系统是否有助于护士更有效地管理颅内压。3)检测与急性颅内压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，以便充分挖掘来自监护仪的连续信号，将其与电子病历(EMR)系统中的其余临床数据集成，以增强临床决策。该项目代表了一项努力，即试行基于平台的方法，以克服阻碍在护理点提供高级预测分析的过程中的翻译障碍。因此，该项目的广泛影响与利用这一开放模型托管平台促进其他ICU中其他预测模型的翻译的未来努力有关。

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.