Faculty Bibliography

Rationale: The Generalized Tonic-Clonic Convulsion (GTCC) has been described as a stereotyped seizure consisting of a symmetric tonic posture, followed by vibratory and clonic phases - defined as movements at a frequency of >5 Hz and <5 Hz respectively. We examined how frequently the classic GTCC occurs in a population and what factors, if any, contributed to deviations from this pattern. Methods: We reviewed the video EEG of 100 consecutive inpatients of the NYU Comprehensive Epilepsy Center that had bilateral limb movements as part of their seizure semiology. Each seizure was reviewed by 2 reviewers; any records in which the patient was obscured on the video were excluded from further analysis. Any seizure with bilateral symmetric tonic, vibratory and clonic phases in that order was categorized as "typical GTCC" (tGTCC), if one phase was absent, asymmetric or in the wrong order of progression it was considered "atypical GTCC" (aGTCC), if two phases were absent it was not a GTCC (nGTCC). All aGTCC were reviewed by at least 3 reviewers. Results: 104 seizures (41 from women) from 100 patients were reviewed, 2 patients were excluded due to obscured video. 45 had a tGTCC while 15 were aGTCC, and 42 were nGT

Rationale: The Generalized Tonic-Clonic Convulsion (GTCC) is often associated with post-ictal electrographic slowing, and at times suppression. The mechanism of post-ictal EEG suppression is not known but may reflect involvement of bilateral subcortical networks. We examined the electrographic activity occurring after seizures with bilateral movement to determine if there are post-ictal features unique to the GTCC. Methods: We reviewed the video EEG of 100 consecutive inpatients of the NYU Comprehensive Epilepsy Center that had bilateral movement as part of their seizure semiology. Each seizure was reviewed by 2 reviewers; any records in which the patient was obscured on the video were excluded from further analysis. Any seizure with bilateral symmetric tonic, vibratory and clonic phases (defined as bilateral movement > and < 5 Hz respectively) in that order was categorized as "typical GTCC" (tGTCC). If one phase was absent, asymmetric or the progression was different, it was considered an "atypical GTCC" (aGTCC). If two phases were absent it was not a GTCC (nGTCC). All aGTCC were reviewed by at least 3 reviewers. The post-ictal EEG was categorized as: "suppression", defined as background voltage <10uV; "slowing" defined as decreased amplitude and/or frequency compared to baseline while still >10uV; or "no change from baseline." Results: 104 seizures from 100 patients were reviewed, 5 patients were excluded due to obscured video or EEG, leaving 97 seizures reviewed. 41 were tGTCC, 14 were aGTCC and 42 were nGT

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. There is a need for a simple surgical grading scale that can be used by the referring neurologist using information obtained prior to diagnostic hospitalization. Such a tool would provide a simple, systematic method for identifying a patient's likelihood of positive outcome following surgical treatment and would offer a uniform means to improve epidemiology and tracking. Our hypothesis was that a model using interictal EEG, brain MRI, seizure semiology and IQ could stratify patients with treatment resistant epilepsy based upon their likelihood of achieving seizure freedom following assessment for resective epilepsy surgery. Methods: Chart review of patients admitted to the New York University Langone Medical Center epilepsy monitoring unit from 1/1/2007 to 7/31/2008 identified 1,105 unique patients. Of these, 455 met inclusion criteria: age >=18, focal epilepsy diagnosis >=2 years, failed >=1 medication, and >=1 seizure three months prior to admission. Calculation of the Epilepsy Surgery Grading Scale (ESGS) score was based upon MRI, EEG, semiology, IQ (Table 1). Patients with follow-up periods <6 months and those with prior resective surgeries were excluded (32 patients). Outcomes were assessed at the study's conclusion (3/31/2010); patients were classified as either seizure free following resective surgery or not seizure free following surgery/no resection. Three cohorts were used in this study: 1) the full cohort, 2) only patients undergoing surgical multidisciplinary case (MDC) conference evaluation, 3) only patients who underwent resective surgery. Results: Our data demonstrate that of 423 patients initially identified as presurgical admissions to the EMU, only 193 (45.6%) were ultimately considered for surgical management and presented in surgical MDC. Eighty-four (19.9%) then underwent resective surgery. Analysis of the MDC cohort reveals that 53.2% of ESGS Grade 1 patients, 34.1% of Grade 2 patients, and 17.2 % of Grade 3 patients became seizure free from resective surgery. For this cohort, significant differences between Grades 1 and 3 (p=0.0001), and between Grades 2 and 3 (p=0.0463) were seen, and a trend was seen between Grades 1 and 2 (p=0.0743). Analysis of the resection only cohort showed that 89.2% of ESGS Grade 1 patients, 83.3% of Grade 2 patients, and 44.8% of Grade 3 patients became seizure free from resective surgery (Table 2). Significant differences between Grades 1 and 3 (p=0.0009), and between Grades 2 and 3 (p=0.0343) were seen; the difference between Grades 1 and 2 was not statistically significant (p=0.6713). Conclusions: These results indicate that, using basic information obtainable in a doctor's office, patients with treatment resistant epilepsy may be stratified into clinically meaningful groups based upon their likelihood of achieving seizure freedom as a result of resective surgery

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. Despite the potential for seizure freedom following surgery, many patients do not progress to epilepsy surgery. It is presumed that the reasons for this are multifactorial and often stem from poor prognostic factors within the presurgical workup. This study was designed to explore potential barriers (both medical and social) to resective epilepsy surgery in a population of patients with a high likelihood of seizure freedom based upon initial MRI, EEG, and semiology data. Methods: Chart review of patients admitted to the New York University Langone Medical Center epilepsy monitoring unit from 1/1/2007 to 7/31/2008 identified 1,105 unique patients. Of these, 455 met inclusion criteria: age >=18, focal epilepsy diagnosis>=2 years, failed >=1 medication, and >=1 seizure three months prior to admission. Utilizing the Epilepsy Surgery Grading Scale (ESGS; Table 1), a score was calculated from MRI, EEG, semiology, and IQ data. Patients with scores categorizing them as Grade 1 (best likelihood of seizure freedom) were included for analysis. Patients with follow-up periods less than 6 months and those with previous resective surgeries were excluded (32 patients). Outcomes were assessed based upon last available follow-up up through June 1, 2011. Patients were classified as either seizure free or not seizure free. For patients not undergoing surgery, medical and surgical outpatient notes were reviewed to ascertain the reason(s) for not pursuing surgery. Results: Of the 423 patients, a total of 110 were Grade 1. Of all Grade 1 patients, 43 (39.1%) underwent resective epilepsy surgery. Two patients had less than one year of follow-up; 35/41 (85.4%) were seizure free. An additional 11 (10%) patients underwent intracranial EEG monitoring without resection. Of the 56 (50.9%) patients that did not undergo invasive monitoring or resective surgery within the period of follow-up, 15 (26.8%) were reported as seizure free at the time of last follow-up. For the remaining patients, multiple reasons were identified for not pursuing surgery. These findings are presented in Table 2. In brief, 2% are presently awaiting surgery, 21% the patient declined surgery, 7% reported adequate seizure control and declined surgery, 16% had no identifiable reason (unknown), 25% were lost to follow up, and 2% had insurance denials precluding surgery. Conclusions: These results indicate that multiple factors can contribute to patients failing to pursue epilepsy surgery, with over 1/2 of patients declining surgery due to seizure freedom, "adequate" seizure control or no desire to further pursue surgery despite continued seizures. In addition, 25% of patients were lost to follow-up, which does not preclude them having had resective surgery at another institution

Rationale: In patients with refractory focal epilepsy, surgery remains an important treatment option for achieving seizure freedom. However, the existing data suggest that for patients with normal neuroimaging, the likelihood of achieving seizure freedom is significantly reduced compared to patients with lesional neuroimaging. This study assesses the utilization of resective surgery versus medical management in patients with normal neuroimaging. Specifically, the study aims to determine how frequently patients with normal brain MRIs are referred for epilepsy surgery and whether there is a difference in outcome (i.e. seizure control) between medically managed and surgically managed patients. Methods: Following approval through the Institutional Review Board at New York University School of Medicine, patients were retrospectively identified by querying the surgical multidisciplinary case (MDC) conference registry. The records were reviewed from January 1, 2007 - July 31, 2008 to identify patients. Inclusion criteria were: age >=18 years, focal epilepsy diagnosis >=2 years, failed >=1 medication, and >=1 seizure three months prior to admission. Of all patients meeting these criteria, 193 were presented at the MDC conference and 33 had normal MRIs upon review. Seizure frequency data were collected by chart review, and when data were incomplete, the patient's primary epileptologist at the NYU Comprehensive Epilepsy Center was contacted. Comparisons were made between the two groups (surgical versus nonsurgical treatment) utilizing the Student's t-test and Fisher's exact test. Results: Of the 33 patients with normal neuroimaging who were presented at MDC, 19 went on to epilepsy surgery (9 women) and 14 were managed medically (7 women); all patients undergoing invasive monitoring underwent resective surgery. The mean age at the time of MDC did not differ between groups (surgery: 30.1+/-10.4, medical: 29+/-10.6; p>0.76). Although a trend for a younger mean age at seizure onset was seen for medically managed patients (surgery: 16.6+/-9.3, medical: 10.9+/-8.8; p>0.09), no significant difference was seen for duration (in years) of epilepsy at the time of MDC (surgery: 13.6+/-10.2, medical: 18.1+/-12.5; p>0.26). At the time of last follow-up, 7 (36.8%) surgical patients were seizure free and 3 (21.4%) medically managed patients were seizure free (p=0.46). Conclusions: Across one and a half years, only 33 of 193 (17.1%) patients reviewed at MDC had normal neuroimaging and focal epilepsy. Ten (30.3%) of the 33 patients were completely seizure free (Engel IA) at last follow-up (with either medical or surgical management). Nineteen of the patients with normal neuroimaging went on to resective surgery with seven (36.8%) becoming seizure free, whereas three (21.4%) of the 14 who were managed medically became seizure free. These data demonstrate that patients with normal neuroimaging represent a minority of those presented at MDC. Although not seen in the majority of cases with normal neuroimaging, seizure freedom can be achieved through either surgical or medical management

Rationale: Resective surgical treatment can be curative in a large subset of patients with treatment resistant epilepsy. There is a need for a simple surgical grading tool which can be employed by the referring neurologist, ideally utilizing information obtained prior to diagnostic hospitalization. Our hypothesis was that a model using interictal EEG, brain MRI, seizure semiology and IQ could stratify patients with treatment resistant epilepsy with respect to their likelihood of achieving seizure freedom following assessment for resective epilepsy surgery. Methods: A prospectively identified cohort of 211 patients from the University of Alabama was combined with a retrospectively identified cohort of 193 consecutive patients at New York University presented in surgical multidisciplinary conference and either proceeded to surgery or were excluded as surgical candidates. All met inclusion criteria: age e18, focal epilepsy diagnosis e2 years, failed e1 medication, e1 seizure 3 months prior to admission, follow-up>6 months. Patients were classified as seizure free following resective surgery or not seizure free following resective surgery/no surgery. Pre-operative EEG, MRI, seizure semiology and IQ data were reviewed, systematically categorized (Table 1) and were utilized in a decision tree algorithm to predict seizure freedom. When p<0.05 was utilized, a simplistic dichotomous algorithm resulted. Therefore, to further explore, a relaxed, exploratory statistical significance level of p<0.25 was used. Nodes resulting in >50% of patients becoming seizure free were considered predictive of seizure freedom. Results: The overall seizure freedom rate was 46.8%. The exploratory decision tree analysis (Figure 1) resulted in two EEG groups: F, G, H (bilateral temporal, bilateral extra-temporal, bisynchronous; node 2; N=97) versus all others (node 3; N=307). For node 3, MRI was employed for further stratification: b (unilateral mesial temporal sclerosis (MTS); node 4; N=75) versus all others (node 7; N=232). Node 4 was further stratified based upon IQ: below 70 (node 5; N=11), above 70 (node 6; N=64). Semiology had no statistically significant impact. The model correctly predicts outcome in 62% of patients, yielding a positive predictive value of 55%, and a negative predictive value of 71%, with sensitivity of 74% and specificity of 51%. Conclusions: The relatively low overall seizure freedom rate is due to the fact that patients considered for, but ultimately not undergoing, surgery were included in the analysis, which better reflects the actual decision process for patients and neurologists. Of interest, the model fails to identify the commonly considered "best surgical" group of unilateral MTS with concordant interictal activity as a unique node. Notably, the main predictive factor was interictal EEG; other factors were only statistically viable with a more exploratory statistical approach. The positive and negative predictive values in this model are probably not sufficient for clinical use