I-Corps: Delirium Prediction and Screening by Non-Invasive Point-of-Care

这个i-Corps项目的更广泛的影响和商业潜力是减少与精神错乱相关的负面后果。精神错乱是一种危险的精神错乱状态，一年死亡率高达40%，是一种非常常见的疾病，普通内科占20%~50%，重症监护病房(ICU)占70%~80%，每年影响200-300万住院老年患者。精神错乱会导致住院时间延长和医疗费用增加。为了改善与精神错乱相关的预后，关键是要及早发现精神错乱，并及时开始对精神错乱和基础条件进行适当的治疗。虽然目前医院已经实施了各种形式的妄想症筛查工具和评定量表，但由于这些筛查仪需要对医院工作人员进行足够的培训，同时也存在主观性的挑战，因此对妄想症的识别仍然是极其困难的。因此，这种仪器的灵敏度很低，特别是在像ICU这样繁忙的医院环境中。随着我们生活在老龄化社会，我们需要更好的方法来更客观地进行早期检测。这个I-Corps项目是为了早期检测出精神错乱，使用一种新创建的频谱密度算法来分析由简化的双谱脑电(EEG)设备记录的患者脑波信号。尽管已有研究表明，全身性脑波减慢是精神分裂症的特征，但由于其应用的复杂性和神经科专家解释的必要性，传统的EEG不适合对大量高危老年患者进行大规模筛查。然而，功率谱分析可以在滤除伪影效应后可靠地计算出脑电信号的不同频段，并已被报道用于检测神志不清患者的特征脑电。一项初步研究的初步数据显示，区分精神错乱和正常情况的数据非常有希望。随着对该算法的验证和检验简化双谱脑电在大规模筛查精神障碍中的有效性，该项目的目标是使用简化的脑电设备来实施这种方法，以帮助医疗保健提供者在临床实践中进行精神错乱的评估和管理，从而以更低的死亡率、更短的住院时间和更低的医疗成本获得更好的结果。

The broader impacts and commercial potential of this I-Corps project is to reduce negative outcomes associated with delirium. Delirium is a dangerous state of confusion, with one year mortality as high as 40%, is very common, 20~50% among general medicine unit, and 70-80% among intensive care unit (ICU), affecting 2-3 million hospitalized elderly patients annually. Delirium can result increased hospital stay and increased healthcare costs. To improve the outcomes associated with delirium, it is critical to detect delirium early on and initiate appropriate treatment for delirium and the underlining conditions in a timely manner. Although, various screening instruments and rating scales for delirium have been implemented in the hospitals, it is still extremely difficult to identify delirium, because such instruments requires enough training for hospital staffs, and also there is a challenge of subjectivity. Thus, such instruments have been shown to have low sensitivity, especially in busy hospital settings such as ICU. As we live in an aging society, we need better methods for early detection in more objective manner.This I-Corps project is to detect delirium early on using a newly created spectral density algorithm to analyze patient's brainwave signals recorded by a simplified bispectral electroencephalography (EEG) device. Although it has been shown that generalized slowing brainwave is characteristic to delirium, due to its complexity of application and necessity of interpretation by neurology specialist, traditional EEG is not suitable for mass screening of large volume of high risk elderly patients. However, power spectrum analysis can reliably calculate different frequency bands of the EEG signals after filtering artifact effects and has been reported to detect characteristic EEGs in delirious patients. A preliminary data from a pilot study has shown very promising data differentiating delirium and normal condition. With continuing efforts to validate the algorithm and to examine the efficacy of the simplified bispectral EEG in mass screening for delirium, it is the goal of the project to implement the approach using simplified EEG device to assist healthcare providers in clinical practice of delirium assessment and management for better outcomes with less mortality, shorter lengths of hospital stay, and lower healthcare cost.