Early Epileptiform Discharges and Clinical Signs Predict Nonconvulsive Status Epilepticus on Continuous EEG
Critical care continuous electroencephalography (CCEEG) represents the gold standard for detection of nonconvulsive status epilepticus (NCSE) in neurological critical care patients. It is unclear which findings on short-term routine EEG and which clinical parameters predict NCSE during subsequent CCEEG reliably. The aim of the present study was to assess the prognostic significance of changes within the first 30 min of EEG as well as of clinical parameters for the occurrence of NCSE during subsequent CCEEG.
Systematic analysis of the first 30 min and the remaining segments of prospective CCEEG recordings according to the ACNS Standardized Critical Care EEG Terminology and according to recently proposed NCSE criteria as well as review of clinical parameters of 85 consecutive neurological critical care patients. Logistic regression and binary classification tests were used to determine the most useful parameters within the first 30 min of EEG predicting subsequent NCSE.
The presence of early sporadic epileptiform discharges (SED) and early rhythmic or periodic EEG patterns of “ictal–interictal uncertainty” (RPPIIIU) (OR 15.51, 95% CI 2.83–84.84, p = 0.002) and clinical signs of NCS (OR 18.43, 95% CI 2.06–164.62, p = 0.009) predicted NCSE on subsequent CCEEG. Various combinations of early SED, early RPPIIIU, and clinical signs of NCS showed sensitivities of 79–100%, specificities of 49–89%, and negative predictive values of 95–100% regarding the incidence of subsequent NCSE (p < 0.001).
Early SED and early RPPIIIU within the first 30 min of EEG as well as clinical signs of NCS predict the occurrence of NCSE during subsequent CCEEG with high sensitivity and high negative predictive value and may be useful to select patients who should undergo CCEEG.
KeywordsEarly epileptiform discharges Ictal–interictal continuum Nonconvulsive status epilepticus Standardized Critical Care EEG Terminology EEG in critical care patients
American Clinical Neurophysiology Society
Critical care continuous electroencephalography
Glasgow Coma Scale
Intensive care unit
Nonconvulsive status epilepticus
Negative predictive value
Rhythmic delta activity
Rhythmic and periodic EEG patterns of “ictal–interictal uncertainty”
Standardized Critical Care EEG Terminology
Sporadic epileptiform discharges
We thank the attending physicians and neurology residents of the Neurological Department, General Hospital Hietzing with Neurological Center Rosenhuegel, for their overall support of this project. We like to thank Sofija Kopitovic, Ingeborg Moser, and Sandra Zeckl for their contribution and help during EEG data acquisition and processing.
JK participated in study idea, clinical and EEG data analysis, statistical analysis, preparing and modifying manuscript. JH participated in study idea, clinical and EEG data analysis, and modifying manuscript. SD, GP participated in clinical data analysis and modifying manuscript. FF, MH, CB participated in study idea, EEG data analysis, and modifying manuscript. TK, AG participated in study idea and modifying manuscript.
Johannes Koren had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Source of Support
This study was supported by the FFG—Austrian Research Promotion Agency grant 826816 (EpiMon). Johannes Koren and Johannes Herta were both partially supported by the FFG grant.
Compliance with Ethical Standards
Conflict of interest
All listed authors do not have any conflict of interest in regard to the content of this study. We confirm that we have read the Journal’s position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
The study protocol was approved by the institutional ethics commission. Patients included in the present study were mainly not able to give consent during EEG recordings. Therefore, the ethics commission requested that all patients that were not able to give consent and their relatives receive a written patient information and/or were informed about the study and the possibility to withdraw their personal data in the future.
- 23.Calculation for the Chi square test: an interactive calculation tool for Chi square tests of goodness of fit and independence [Computer software]. Available from http://quantpsy.org. 2017.