Abstracts

EEG PREDICTORS OF ANTIEPILEPTIC DRUG ADJUSTMENTS IN CRITICALLY ILL PATIENTS - A PROSPECTIVE OBSERVATIONAL STUDY

Abstract number : 2.161
Submission category : 3. Neurophysiology
Year : 2014
Submission ID : 1868243
Source : www.aesnet.org
Presentation date : 12/6/2014 12:00:00 AM
Published date : Sep 29, 2014, 05:33 AM

Authors :
Guoqiao Wang, Ayaz Khawaja, Gary Cutter and Jerzy Szaflarski

Rationale: Continuous EEG (cEEG) has been increasingly used as part of neuromonitoring in intensive care units (ICU). Limited evidence from retrospective studies suggests that cEEG impacts antiepileptic drugs (AEDs) use and modifications. The goal of this study was to prospectively assess such modifications and how cEEG characteristics impacted AED changes in patients admitted to ICU. Methods: Data were prospectively collected from 112 ICU patients receiving cEEG and 110 patients not receiving cEEG (controls). Patients admitted because of seizures/epilepsy were excluded. Explanatory variables included age, gender, comorbidities, cEEG duration, admission Glasgow Coma Scale (GCSA), and duration of hospital and ICU stay. cEEG characteristics investigated included any interictal epileptiform discharges (EDs), periodic lateralized epileptiform discharges (PLEDs), multifocal interictal epileptiform discharges (Multi-EDs), generalized periodic epileptiform discharges (GPEDs), and seizures (Seizures). Background rhythm (BR), focal slowing (FS) and reactivity in the first and last 24 hours of cEEG monitoring were also recorded. Primary outcomes were any AED changes (nAED). Generalized linear modeling was used to identify characteristics associated with the primary outcomes. Results: After controlling for age, GCSA and seizures, use of cEEG had significant impact on nAEDs (p<0.0001). Mean (SD) count of AED changes (Mean-nAED) for cEEG patients was 2.1(2.9) compared to 0.4(0.9) for controls. For cEEG patients, 43 had any epileptiform activity detected and their mean-nAED was 1.9 times than for the rest of patients (n=69) (p=0.0063). The mean-nAED during monitoring was 4.3 times the changes made during the period both before and after cEEG for the same patients (p<0.0001). The mean-nAED for patients receiving cEEG who did not have any epileptiform activity (69/112) was 3.49 times the mean for controls (n=110) (p<0.0001) when adjusting for age, GCSA, and comorbidities. Of the 112 cEEG patients, 38 had EDs, 12 had PLEDs, 24 had multi-EDs, 8 had GPEDs and 20 had seizures at least once during monitoring (see Table 1). After controlling for age, GCSA, and comorbidities, the mean-nAED for patients with EDs was 1.89 times the mean for those without (p=0.0089); the mean-nAED for patients with PLEDs was 4.08 times than those without (p<0.0001); the mean-nAED for patients with multi-EDs was 1.96 times than those without (p=0.0095); and the mean-nAED for patients with seizures was 2.98 times than those without (p<0.0001). BR, FS, reactivity and GPEDs did not significantly impact nAED. Conclusions: The use of cEEG significantly increases the number of AED modifications. Patients who receive cEEG but have no epileptiform activity detected also have more AED changes compared to patients who do not receive any monitoring. Most AED changes occurred in patients with PLEDs, followed by detection of any seizures, multifocal EDs and any interictal discharges. Background rhythm, focal slowing, reactivity and GPEDs did not predict AED changes.
Neurophysiology