Quantitative EEG analysis for automated detection of nonconvulsive seizures in intensive care units.
Quantitative EEG analysis for automated detection of nonconvulsive seizures in intensive care units.
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DOI：
10.1016/j.yebeh.2011.08.028
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发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
Kelly KM
中科院分区：
文献类型：
--
作者：
Sackellares JC;Shiau DS;Halford JJ;LaRoche SM;Kelly KM
由于对重症患者非惊厥性癫痫发作（NCS）高患病率的认识不断提高，ICU中连续EEG监测（cEEG）的使用正在迅速增加。然而，cEEG监测是劳动密集型的; EEG的手动审查和解释在大多数ICU中是不切实际的。有效的方法来帮助快速准确地检测NCS将大大降低cEEG的成本，提高病人的护理质量。在这项研究中，我们报告了一个新的ICU脑电图分析和癫痫发作检测算法的初步调查。本研究包括24个长时间cEEG记录。评估了新算法和两种商业癫痫发作检测软件系统的癫痫发作检测灵敏度和特异性。新算法的平均灵敏度为90.4%，平均误检率为0.066/h。两种商业检测产品的灵敏度较低（12.9%和10.1%），错误检测率分别为1.036/h和0.013/h。这些研究结果表明，新的算法有可能成为临床有用的软件，可以帮助ICU工作人员及时识别NCS的基础。这项研究还表明，目前可用的癫痫发作检测软件没有足够的性能来检测危重患者的NCS。
Due to increased awareness of the high prevalence of nonconvulsive seizures (NCSs) in critically ill patients, continuous EEG monitoring (cEEG) in ICUs is rapidly increasing in use. However, cEEG monitoring is labor intensive; manual review and interpretation of the EEG are impractical in most ICUs. Effective methods to assist in rapid and accurate detection of NCSs would greatly reduce the cost of cEEG and enhance the quality of patient care. In this study, we report a preliminary investigation of a novel ICU EEG analysis and seizure detection algorithm. Twenty-four prolonged cEEG recordings were included in this study. Seizure detection sensitivity and specificity were assessed for the new algorithm and for the two commercial seizure detection software systems. The new algorithm performed a mean sensitivity of 90.4% and a mean false detection rate of 0.066/h. The two commercial detection products performed with low sensitivities (12.9% and 10.1%) and false detection rates of 1.036/h and 0.013/h, respectively. These findings suggest that the novel algorithm has potential to be the basis of clinically useful software that can assist ICU staff in timely identification of NCSs. This study also suggests that currently available seizure detection software does not have sufficient performance for the detection of NCSs in critically ill patients.
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影响因子：
0.5
作者：
Shiau DS;Halford JJ;Kelly KM;Kern RT;Inman M;Chien JH;Pardalos PM;Yang MC;Sackellares JC
通讯作者：
Sackellares JC
影响因子：
4.1
作者：
Vespa, PM;Nuwer, MR;Becker, DP
通讯作者：
Becker, DP
影响因子：
--
作者：
Jette, Nathalie;Claassen, Jan;Hirsch, Lawrence J.
通讯作者：
Hirsch, Lawrence J.
DOI：
10.1097/01.wcb.0000076701.45782.ef
发表时间：
2003-07-01
影响因子：
6.3
作者：
Vespa, PM;McArthur, D;Hovda, DA
通讯作者：
Hovda, DA
影响因子：
--
作者：
Pandian, JD;Cascino, GD;Fulgham, JR
通讯作者：
Fulgham, JR