Ram Mani

American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2012 version.

Continuous EEG Monitoring is becoming a commonly used tool in assessing brain function in critically ill patients. However, there is no uniformly accepted nomenclature for EEG patterns frequently encountered in these patients such as periodic discharges, fluctuating rhythmic patterns, and combinatio

The frequency and timing of epileptiform activity on continuous electroencephalogram in comatose post-cardiac arrest syndrome patients treated with therapeutic hypothermia ,

AIM The incidence and timing of electrographic seizures and epileptiform activity in comatose, adult, post-cardiac arrest syndrome (PCAS) patients treated with therapeutic hypothermia (TH) have not been extensively investigated. We hypothesized that onset most frequently occurs within the first 24 h post-arrest and is associated with poor neurologic outcome. METHODS Single-center, retrospective analysis of a cohort of 38 comatose PCAS patients treated with TH and continuous-EEG-monitoring (cEEG), initiated as soon as possible after ICU admission. All raw cEEG waveform records were cleared of annotations and clinical information and classified by two fellowship-trained electroencephalographers. RESULTS Twenty-three percent (9/38) of patients had electrographic seizures (median onset 19 h post-arrest); 5/9 (56%) had seizure-onset prior to rewarming; 7/9 (78%) had status epilepticus. Forty-five percent (17/38) had evidence of epileptiform activity (electrographic seizures or interictal epileptiform discharges), typically occurring during first 24 h post-arrest. Interictal epileptiform activity was highly associated with later detection of electrographic seizures (6/14, 43%, p=0.001). Ninety-four percent (16/17) of patients with epileptiform activity had poor neurologic outcome or death at discharge (Cerebral Performance Category scale 3-5; p=0.002) as did all (9/9) patients with electrographic seizures (p=0.034). CONCLUSIONS Electrographic seizures and epileptiform activity are common cEEG findings in comatose, PCAS patients treated with TH. In this preliminary study, most seizures were status epilepticus, had onset prior to rewarming, evolved from prior interictal epileptiform activity, and were associated with short-term mortality and poor neurologic outcome. Larger, prospective studies are needed to further characterize seizure activity in comatose post-arrest patients.

Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement.

Clinical electroencephalography (EEG) records vast amounts of human complex data yet is still reviewed primarily by human readers. Deep belief nets (DBNs) are a relatively new type of multi-layer neural network commonly tested on two-dimensional image data but are rarely applied to times-series data such as EEG. We apply DBNs in a semi-supervised paradigm to model EEG waveforms for classification and anomaly detection. DBN performance was comparable to standard classifiers on our EEG dataset, and classification time was found to be 1.7-103.7 times faster than the other high-performing classifiers. We demonstrate how the unsupervised step of DBN learning produces an autoencoder that can naturally be used in anomaly measurement. We compare the use of raw, unprocessed data--a rarity in automated physiological waveform analysis--with hand-chosen features and find that raw data produce comparable classification and better anomaly measurement performance. These results indicate that DBNs and raw data inputs may be more effective for online automated EEG waveform recognition than other common techniques.

Human clinical trails in antiepileptogenesis.

Blocking the development of epilepsy (epileptogenesis) is a fundamental research area with the potential to provide large benefits to patients by avoiding the medical and social consequences that occur with epilepsy and lifelong therapy. Human clinical trials attempting to prevent epilepsy (antiepileptogenesis) have been few and universally unsuccessful to date. In this article, we review data about possible pathophysiological mechanisms underlying epileptogenesis, discuss potential interventions, and summarize prior antiepileptogenesis trials. Elements of ideal trials designs for successful antiepileptogenic intervention are suggested.

Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets

Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as signatures of abnormal brain. These pathologic EEG waveforms, once detected, often necessitate accute clinincal interventions, but these events are typically rare, highly variable between patients, and often hard to separate from background, making them difficult to reliably detect. We show that Deep Belief Nets (DBNs), a type of multi-layer generative neural network, can be used effectively for such EEG anomaly detection. We compare this technique to the state-of-the-art, a one-class Support Vector Machine (SVM), showing that the DBN outperforms the SVM by the F1 measure for our EEG dataset. We also show how the outputs of a DBN-based detector can be used to aid visualization of anomalies in large EEG data sets and propose a method for using DBNs to gain insight into which features of signals are characteristically anomalous. These findings show that Deep Belief Nets can facilitate human review of large amounts of clinical EEG as well as mining new EEG features that may be indicators of unusual activity.

Sensitivity of quantitative EEG for seizure identification in the intensive care unit

Objective: To evaluate the sensitivity of quantitative EEG (QEEG) for electrographic seizure identification in the intensive care unit (ICU). Methods: Six-hour EEG epochs chosen from 15 patients underwent transformation into QEEG displays. Each epoch was reviewed in 3 formats: raw EEG, QEEG + raw, and QEEG-only. Epochs were also analyzed by a proprietary seizure detection algorithm. Nine neurophysiologists reviewed raw EEGs to identify seizures to serve as the gold standard. Nine other neurophysiologists with experience in QEEG evaluated the epochs in QEEG formats, with and without concomitant raw EEG. Sensitivity and false-positive rates (FPRs) for seizure identification were calculated and median review time assessed. Results: Mean sensitivity for seizure identification ranged from 51% to 67% for QEEG-only and 63%–68% for QEEG + raw. FPRs averaged 1/h for QEEG-only and 0.5/h for QEEG + raw. Mean sensitivity of seizure probability software was 26.2%–26.7%, with FPR of 0.07/h. Epochs with the highest sensitivities contained frequent, intermittent seizures. Lower sensitivities were seen with slow-frequency, low-amplitude seizures and epochs with rhythmic or periodic patterns. Median review times were shorter for QEEG (6 minutes) and QEEG + raw analysis (14.5 minutes) vs raw EEG (19 minutes; p = 0.00003). Conclusions: A panel of QEEG trends can be used by experts to shorten EEG review time for seizure identification with reasonable sensitivity and low FPRs. The prevalence of false detections confirms that raw EEG review must be used in conjunction with QEEG. Studies are needed to identify optimal QEEG trend configurations and the utility of QEEG as a screening tool for non-EEG personnel. Classification of evidence review: This study provides Class II evidence that QEEG + raw interpreted by experts identifies seizures in patients in the ICU with a sensitivity of 63%–68% and FPR of 0.5 seizures per hour.

Apparent dose-dependent levetiracetam-induced de novo major depression with suicidal behavior☆☆

Levetiracetam (LEV) is a novel antiepileptic drug (AED) approved for the adjunctive treatment of generalized and partial seizures. LEV has no clinically significant drug interactions and has limited adverse effects. The psychiatric adverse effects of LEV include de novo psychosis, affective disorder, and aggression. LEV-induced suicidal behavior has been reported infrequently with a past history of affective disorders. The authors report an apparent dose/concentration-dependent LEV-induced de novo major depression with near fatal suicide attempt in a patient without prior history of affective disorder. Psychiatric evaluation with emphasis on historic/current affective disorders, impulsive–aggressive behaviors, and assessment of risk factors for suicidal behaviors is indicated in treating patients with epilepsy with LEV. Clinicians should consider therapeutic drug monitoring to optimize therapeutic LEV treatment.

Epilepsy Surgery: Factors That Affect Patient Decision-Making in Choosing or Deferring a Procedure

Surgical resection for well-selected patients with refractory epilepsy provides seizure freedom approximately two-thirds of the time. Despite this, many good candidates for surgery, after a presurgical workup, ultimately do not consent to a procedure. The reasons why patients decline potentially effective surgery are not completely understood. We explored the socio cultural, medical, personal, and psychological differences between candidates who chose (n = 23) and those who declined surgical intervention (n = 9). We created a novel questionnaire addressing a range of possible factors important in patient decision making. We found that patients who declined surgery were less bothered by their epilepsy (despite comparable severity), more anxious about surgery, and less likely to listen to their doctors (and others) and had more comorbid psychiatric disease. Patients who chose surgery were more embarrassed by their seizures, more interested in being “seizure-free”, and less anxious about specific aspects of surgery. Patient attitudes, beliefs, and anxiety serve as barriers to ideal care. These results can provide opportunities for education, treatment, and intervention. Additionally, patients who fit a profile of someone who is likely to defer surgery may not be appropriate for risky and expensive presurgical testing.

Anterior temporal lobectomy compared with laser thermal hippocampectomy for mesial temporal epilepsy: A threshold analysis study

PURPOSE Anterior Temporal Lobectomy (ATL) is the gold standard surgical treatment for refractory temporal lobe epilepsy (TLE), but it carries the risks associated with invasiveness, including cognitive and visual deficits and potential damage to eloquent structures. Laser thermal hippocampectomy (LTH) is a new procedure that offers a less invasive alternative to the standard open approach. In this decision analysis, we determine the seizure freedom rate at which LTH would be equivalent to ATL. METHODS MEDLINE searches were performed for studies of ATL from 1995 to 2014. Using complication and success rates from the literature, we constructed a decision analysis model for treatment with ATL and LTH. Quality-adjusted life years (QALYs) were derived from examining patient preferences in similar clinical conditions. LTH data were obtained from a preliminary multicenter study report following patients for 6-12 months. A sensitivity analysis in which major parameters were systematically varied within their 95% CIs was used. RESULTS 350 studies involving 25,144 cases of ATL were included. Outcomes of LTH were taken from a recently presented multicenter series of 68 cases. Over a 10-year postoperative modeling period, LTH value was 5.9668 QALYs and ATL value was 5.8854. Sensitivity analysis revealed that probabilities of seizure control and late morbidity of LTH are most likely to affect outcomes compared to ATL. We calculated that LTH would need to stop disabling seizures (Engel class I) in at least 43% of cases and have fewer than 40% late mortality/morbidity to result in quality of life at least as good as that after ATL. CONCLUSIONS This decision analysis based on early follow-up data suggests LTH has similar utility to ATL. These early data support LTH as a potentially comparable less invasive alternative to ATL in refractory TLE. LTH utility may remain comparable to ATL even if long-term seizure control is less than that of ATL. Larger prospective studies with long-term follow up will be needed to validate the true role of LTH in the refractory epilepsy patient population.

Low-dose lacosamide-induced atrial fibrillation: Case analysis with literature review

Lacosamide (LCM) is a novel antiepileptic drug (AED) approved by the FDA for adjunctive treatment of partial epilepsy with and without secondary generalization. Lacosamide dose-dependent dysrhythmias (PR-interval prolongation, AV block, and atrial fibrillation/flutter) have been reported. This case represents the first instance of LCM-induced atrial fibrillation following a low loading dose (200 mg). Risk factors for atrial fibrillation are addressed and discussed in the context of this case. Full cardiac history is recommended prior to patients being initiated on LCM. Cardiac monitoring may be required for at-risk patients on LCM. Clinicians need to be cognizant of this potential adverse effect.