Department of Clinical Neurophysiology, Stichting Epilepsie Instellingen Nederland, the Netherlands.
Department of Clinical Neurophysiology, Stichting Epilepsie Instellingen Nederland, the Netherlands.
Seizure. 2022 Mar;96:13-17. doi: 10.1016/j.seizure.2022.01.009. Epub 2022 Jan 13.
We assessed whether automated detection software, combined with live observation, enabled reliable seizure detection using three commercial software packages: Persyst, Encevis and BESA.
Two hundred and eighty-six prolonged EEG records of individuals aged 16-86 years, collected between August 2019 and January 2020, were retrospectively processed using all three packages. The reference standard included all seizures mentioned in the clinical report supplemented with true detections made by the software and not previously detected by clinical physiologists. Sensitivity was measured for offline review by clinical physiologists and software seizure detection, both in combination with live monitoring in an EMU setting, for all three software packages at record and seizure level.
The database contained 249 seizures in 64 records. The sensitivity of seizure detection was 98% for Encevis and Persyst, and 95% for BESA, when a positive results was defined as detection at least one of the seizures occurring within an individual record. When positivity was defined as recognition of all seizures, sensitivity was 93% for Persyst, 88% for Encevis and 84% for BESA. Clinical physiologists' review had a sensitivity of 100% at record level and 98% at seizure level. The median false positive rate per record was 1.7 for Persyst, 2.4 for BESA and 5.5 for Encevis per 24 h.
Automated seizure detection software does not perform as well as technicians do. However, it can be used in an EMU setting when the user is aware of its weaknesses. This assessment gives future users helpful insight into these strengths and weaknesses. The Persyst software performs best.
我们评估了自动化检测软件结合实时观察是否能够使用三种商业软件包（Persyst、Encevis 和 BESA）可靠地检测癫痫发作。
我们回顾性地处理了 2019 年 8 月至 2020 年 1 月期间收集的 286 份年龄在 16 至 86 岁之间的长时间脑电图记录。所有三种软件包均使用所有记录进行离线处理。参考标准包括临床报告中提到的所有癫痫发作，以及软件检测到的真实发作，但临床生理学家以前未检测到。我们在 EMU 设置中结合实时监测，评估了离线回顾和软件癫痫发作检测的敏感性，所有三种软件包均在记录和癫痫发作水平上进行评估。
数据库包含 64 份记录中的 249 次癫痫发作。当阳性结果定义为在个体记录中检测到至少一次发生的癫痫发作时，Encevis 和 Persyst 的检测敏感性为 98%，BESA 的检测敏感性为 95%。当阳性结果定义为识别所有癫痫发作时，Persyst 的敏感性为 93%，Encevis 的敏感性为 88%，BESA 的敏感性为 84%。临床生理学家的回顾在记录水平上的敏感性为 100%，在癫痫发作水平上的敏感性为 98%。每记录的平均假阳性率为 Persyst 为 1.7，BESA 为 2.4，Encevis 为 5.5/24 小时。
自动化癫痫发作检测软件的性能不如技术人员。然而，当用户了解其弱点时，它可以在 EMU 设置中使用。这种评估为未来的用户提供了有关这些优势和弱点的有用见解。Persyst 软件的性能最佳。
