Prerace venous blood gases and acid-base values in Standardbred horses: effects of geography, season, prerace furosemide, gender, age, and trainer using big data analytics.

OBJECTIVE: A retrospective study was conducted to establish the prerace venous acid-base and blood gas values of Standardbred horses at rest using big data analytics. SAMPLES: Venous blood samples (73,382) were collected during seven racing seasons from 3 regional tracks in the Commonwealth of Pennsylvania. Horses were detained 2 hours prior to race time. PROCEDURES: A mixed-effects linear regression model was used for estimating the marginal model adjusted mean (marginal mean) for all major outcomes. The interaction between age and gender, track, and the interaction between month, treatment (furosemide), and year were the major confounders included in the model. Random effects were set on individual animal nested within trainer. Partial pressure of venous carbon dioxide (PVCO2), partial pressure of oxygen (PVO2), and pH were measured, and base excess (BE), total carbon dioxide (TCO2), and bicarbonate (HCO3-) were calculated. RESULTS: Significant (P < .001) geographical differences in track locations were seen. Seasonal reductions in acid-base values started in January with significant (P < .001) decreases from adjacent months seen in June, July, and August followed by a gradual return. There were significant increases (P < .001) in BE and TCO2 and decreases in PVO2 with age. Significant differences (P < .001) in acid-base values were seen when comparing genders. A population of trainers were significantly different (P < .001) from the marginal mean and considered outliers. CLINICAL RELEVANCE: In a population of horses, big data analytics was used to confirm the effects of geography, season, prerace furosemide, gender, age, and trainer influence on blood gases and the acid-base profile.

Second-line immunotherapy and functional outcomes in autoimmune encephalitis: A systematic review and individual patient data meta-analysis.

Autoimmune encephalitis (AE) is a neurological disorder caused by autoimmune attack on cerebral proteins. Experts currently recommend staged immunotherapeutic management, with first-line immunotherapy followed by second-line immunotherapy if response to first-line therapy is inadequate. Meta-analysis of the evidence base may provide higher quality evidence to support this recommendation. We undertook a systematic review of observational cohort studies reporting AE patients treated with either second-line immunotherapy or first-line immunotherapy alone, and outcomes reported using the modified Rankin Scale (mRS; search date: April 22, 2020). We performed several one-stage multilevel individual patient data (IPD) meta-analyses to examine the association between second-line immunotherapy and final mRS scores (PROSPERO ID CRD42020181805). IPD were obtained for 356 patients from 25 studies. Most studies were rated as moderate to high risk of bias. Seventy-one patients (71/356, 19%) were treated with second-line immunotherapy. We did not find a statistically significant association between treatment with second-line immunotherapy and final mRS score for the cohort overall (odds ratio [OR] = 1.74, 95% confidence interval [CI] = .98-3.08, p = .057), or subgroups with anti-N-methyl-D-aspartate receptor encephalitis (OR = 1.03, 95% CI = .45-2.38, p = .944) or severe AE (maximum mRS score > 2; OR = 1.673, 95% CI = .93-3.00, p = .085). Treatment with second-line immunotherapy was associated with higher final mRS scores in subgroups with anti-leucine-rich glioma-inactivated 1 AE (OR = 6.70, 95% CI = 1.28-35.1, p = .024) and long-term (at least 12 months) follow-up (OR = 3.94, 95% CI = 1.67-9.27, p = .002). We did not observe an association between treatment with second-line immunotherapy and lower final mRS scores in patients with AE. This result should be interpreted with caution, given the risk of bias, limited adjustment for disease severity, and insensitivity of the mRS in estimating psychiatric and cognitive disability.

The Relationship Between Lipoproteins and Insulin Sensitivity in Youth With Obesity and Abnormal Glucose Tolerance.

CONTEXT: Youth with obesity and abnormal glucose tolerance have an increased risk for atherosclerosis but the relative contributions of insulin resistance and hyperglycemia to dyslipidemia and the development of subclinical atherosclerosis are unknown. OBJECTIVE: This work aims to determine the association between insulin resistance, dyslipidemia, and carotid intimal thickness (cIMT) in adolescents with normal and abnormal glucose tolerance. METHODS: An observational cohort study in 155 youth: 44 obese insulin sensitive (OIS; fasting insulin ≤ 20 µM/mL, body mass index [BMI] ≥ 95th percentile), 35 obese insulin resistant (OIR; fasting insulin > 20 µM/mL, BMI ≥ 95th percentile), 34 obese abnormal glucose tolerant (AGT; BMI ≥ 95th percentile), and 42 Lean (BMI 5th-85th percentile). Lipids, lipoprotein particle size and concentration (-P), insulin sensitivity (SI an intravenous glucose test), and CMIT were compared using linear models adjusted for age, race/ethnicity, biological sex, and Tanner stage. Lipid/lipoprotein profile and CMIT were reevaluated in a subset after 2 years. RESULTS: Compared to OIS and Lean, OIR and AGT had elevated triglycerides and low high-density lipoprotein cholesterol (HDL-C) but similar total cholesterol and low-density lipoprotein cholesterol (LDL-C). Among OIS, OIR, AGT, lower SI was associated with atherogenic lipids (higher triglycerides, LDL-C, non-HDL-C, and lower HDL-C) and lipoproteins (higher total LDL-P and small HDL-P, and lower large HDL-P). There was a steeper decline in the association of SI with HDL-C and large HDL-P in AGT compared with OIR and OIS. cIMT was comparable across groups and inversely correlated with SI, with no change after 2 years. CONCLUSION: Among youth with obesity, insulin resistance was associated with an atherogenic lipoprotein/lipid profile and cIMT, regardless of glucose tolerance status. Insulin resistance in AGT youth was associated with a shift to smaller HDL-P compared to normoglycemic youth with obesity. Alterations in HDL-P metabolism may be early adverse manifestations of hyperglycemia in youth with obesity.

Predictive semiology of psychogenic non-epileptic seizures in an epilepsy monitoring unit.

INTRODUCTION: The diagnosis of psychogenic nonepileptic seizures (PNES) is a common clinical dilemma. We sought to assess the diagnostic value of four ictal signs commonly used in differentiating PNES from epileptic seizures (ES). METHODS: We retrospectively reviewed consecutive adult video-electroencephalogram (VEM) studies conducted at a single tertiary epilepsy center between May 2009 and August 2016. Each event was assessed by a blinded rater for the presence of four signs: fluctuating course, head shaking, hip thrusting, and back arching. The final diagnosis of PNES or ES was established for each event based on clinical and VEM characteristics. All ES were pooled regardless of focal or generalized onset. We analyzed the odds ratio of each sign in PNES in comparison to ES with adjustment for repeated measures using logistic regression. Additionally, we calculated the sensitivity, specificity, predictive values, and likelihood ratios of each sign to diagnose PNES. RESULTS: A total of 742 events from 140 VEM studies were assessed. Fluctuating course (odds ratio (OR) 37.37, 95% confidence interval (CI) 13.56-102.96, P < 0.0001), head shaking (OR 2.95, 95% CI 1.26-6.79, P = 0.012), and hip thrusting (OR 4.28, 95% CI 1.21-15.18, P = 0.02) were each significantly predictive of PNES. Fluctuating course had the highest sensitivity (76.16%). Back arching (OR 1.06, 95% CI 0.35-3.20, P = 0.92) was not significantly associated with PNES. CONCLUSION: Fluctuating course, head shaking, and hip thrusting are semiological features significantly more common in PNES than ES. Fluctuating course is the most reliable sign. Back arching does not appear to differentiate PNES from ES.

Revisiting an ancient legend: influence of the lunar cycle on occurrence of first-ever unprovoked seizures.

BACKGROUND: The mythical effect of the lunar cycle on seizures has been debated over time. Previously healthy individuals presenting with first-ever seizures in whom investigations are negative often invoke questions about potential reasons including a full moon. AIMS: To determine whether there is a temporal relationship between the occurrence of the first-ever unprovoked seizure and the lunar cycle. METHODS: We studied adults who presented with a first-ever unprovoked seizure to two tertiary centres in Australia. Seizure onset time was obtained from the emergency department and ambulance documentations. We used Poisson regression modelling and incidence rate ratios (IRR) to determine whether seizures have a preponderance for a particular lunar phase. We performed further analysis on 'first seizure epilepsy' and 'first seizure not epilepsy' subgroups based on the International League Against Epilepsy criteria for a diagnosis of epilepsy after a single unprovoked seizure. RESULTS: We analysed 1710 patients (38% females; median age 39 years), of whom 18% had epileptiform abnormalities on electroencephalogram (EEG) and potentially epileptogenic lesions were detected on neuroimaging in 28%. Based on the EEG and imaging findings, 684 (40%) patients were categorised as 'first seizure epilepsy' and 1026 (60%) 'first seizure not epilepsy'. The whole cohort and subgroup analysis demonstrated no significant difference in the seizure occurrence among the four lunar quarters. CONCLUSIONS: First unprovoked seizures are not influenced by the lunar cycle. Patients pondering the cause of their first-ever unprovoked seizure can be reassured that the full moon was not responsible.

Interictal spike localization for epilepsy surgery using magnetoencephalography beamforming.

OBJECTIVE: Magnetoencephalography (MEG) kurtosis beamforming is an automated localization method for focal epilepsy. Visual examination of virtual sensors, which are source activities reconstructed by beamforming, can improve performance but can be time-consuming for neurophysiologists. We propose a framework to automate the method and evaluate its effectiveness against surgical resections and outcomes. METHODS: We retrospectively analyzed MEG recordings of 13 epilepsy surgery patients who had one-year minimum post-operative follow-up. Kurtosis beamforming was applied and manual inspection was confined to morphological clusters. The region with the Maximum Interictal Spike Frequency (MISF) was validated against prospectively modelled sLORETA solutions and surgical resections linked to outcome. RESULTS: Our approach localized spikes in 12 out of 13 patients. In eight patients with Engel I surgical outcomes, beamforming MISF regions were concordant with surgical resection at overlap level for five patients and at lobar level for three patients. The MISF regions localized to spike onset and propagation modelled by sLORETA in two and six patients, respectively. CONCLUSIONS: Automated beamforming using MEG can predict postoperative seizure freedom at the lobar level but tends to localize propagated MEG spikes. SIGNIFICANCE: MEG beamforming may contribute to non-invasive procedures to predict surgical outcome for patients with drug-refractory focal epilepsy.

Temporal patterns in the first unprovoked seizure.

OBJECTIVE: Cyclic phenomena in epilepsy are well recognized. We investigated a multicenter cohort of unprovoked first seizure presentations to determine whether seizures have a preponderance to occur in: a particular time of the day, a particular day of the week, a particular month of the year, day time versus night time, and wakefulness versus sleep. METHODS: We retrospectively studied adults who presented with a first-ever unprovoked seizure to the First Seizure Clinic at two tertiary centers in Australia. Seizure onset time was obtained from the emergency department and ambulance documentations. Electro-clinical and neuroimaging findings were reviewed. We used histograms and Poisson regression modeling to determine whether seizures have a preponderance to occur at a particular time and calculated incidence rate ratios (IRR). We performed further analysis on patients with "first seizure epilepsy" and "first seizure not epilepsy" based on the ILAE criteria for a diagnosis of epilepsy after a single unprovoked seizure, as well as comparing patients that could be categorized as having a generalized-onset seizure versus those with focal-onset seizures. RESULTS: We analyzed 1724 patients (38% females; age range 14-97 yr, median 39 yr), of whom 18% had epileptiform abnormalities on EEG and potentially epileptogenic lesions were detected on neuroimaging in 28%. Whole cohort analysis shows the incidence rate ratios (IRR) of seizures varied significantly across the 24-hour clock-time of the day (p < 0.001), peaking at hour 12 (IRR 3.18). The first unprovoked seizure was significantly less likely to be reported during the night (IRR 0.61, p < 0.001) and during sleep (IRR 0.29, p < 0.001). Both the "first seizure epilepsy" and "first seizure not epilepsy" subgroups' analysis demonstrated similar patterns. An infraradian pattern was also noted with seizures most likely to occur in May (IRR 1.29, p = 0.02). Both "first seizure epilepsy - generalized" and "first seizure epilepsy - focal" groups had a preponderance for seizures to occur during the day versus night and wakefulness as opposed to sleep, but the association was more robust for generalized seizures. CONCLUSIONS: Our results suggest that temporal patterns are seen in patients with first-ever unprovoked seizures, including those that meet contemporary criteria for epilepsy. These results raise the possibility that first unprovoked seizures have intrinsic rhythmicity similar to epileptic seizures.

Sleep-Disordered Breathing and Free Fatty Acid Metabolism.

BACKGROUND: Sleep-disordered breathing (SDB) is independently associated with insulin resistance, glucose intolerance, and type 2 diabetes mellitus. However, data on whether SDB alters the metabolism of free fatty acids (FFAs) are lacking. RESEARCH QUESTION: The primary objective of the current study was to characterize alterations in FFA metabolism across the spectrum of SDB severity. STUDY DESIGN AND METHODS: The study sample included 118 participants with and without SDB who underwent full-montage polysomnography, the frequently sampled IV glucose tolerance test (FSIGTT), and body composition measurements including determination of percent body fat. Parameters of lipolysis suppression, time to FFA nadir, and FFA rebound after an IV glucose challenge were derived using a mathematical model. Multivariable regression analyses were used to characterize the independent associations between SDB severity and parameters of FFA metabolism. RESULTS: SDB severity, as assessed by the apnea-hypopnea index, was associated with adipocyte insulin resistance, a decrease in the glucose- and insulin-mediated suppression of lipolysis, a longer duration to reach a nadir in FFA levels during the FSIGTT, and a sluggish rebound in FFA levels after suppression. Severity of SDB-related hypoxemia was independently associated with adipocyte insulin resistance and the time to reach the FFA nadir during the FSIGTT. Finally, a higher percentage of stage N3 sleep was positively associated with greater suppression of lipolysis and a faster rebound in the FFA levels during the FSIGTT. INTERPRETATION: Independent of adiposity, SDB is associated with impairments in FFA metabolism, which may contribute to the development of glucose intolerance and type 2 diabetes in SDB.

"Sleep Surge": The impact of sleep onset and offset on epileptiform discharges in idiopathic generalized epilepsies.

OBJECTIVE: To investigate the impact of sleep onset and offset on the rate of epileptiform discharges (ED) in idiopathic generalized epilepsies (IGE). METHODS: We studied the temporal distribution of EDs with mixed-effects Poisson regression modeling in a cohort of patients diagnosed with IGE who underwent 24-hour ambulatory electroencephalography (EEG) recordings. We defined the mean number discharges per hour per subject as the mean ED rate. The association between each hour and the mean ED rate was quantified with incidence rate ratio (IRR) as the metric. We calculated the IRR of each hourly block for the total cohort in relation to sleep onset and offset. Finally, we admitted secondary risk factors into our Poisson regression model and quantified changes in IRR in order to investigate the impact of those variables on the outcome. The secondary risk factors included: epilepsy syndrome, duration of seizure freedom, duration of epilepsy, number of antiepileptic drugs (AED), type of AED, and age. RESULTS: A total of 39 patients with a mean age of 29.1 y (SD = 10.1) were studied. The distribution of ED rate demonstrated a highly significant abrupt increase in the first hour after sleep onset (IRR = 3.96; p < 0.001). On the contrary, the ED rate significantly dropped in the second hour after the sleep offset compared with the last hour block before sleep offset (IRR = 0.39; p < 0.001). None of the secondary risk factors demonstrated any significant impact on this pattern. CONCLUSIONS: Sleep onset is a very significant trigger for the generation of EDs in IGE. SIGNIFICANCE: Our results support the hypothesis that there is a "critical zone of vigilance" in the sleep-wake boundary from which generalized EDs are more likely to emerge.

Changes in soluble tumor necrosis factor receptor type 1 levels and early renal function decline in patients with diabetes.

The relationship between serial changes in soluble tumor necrosis factor receptor type 1 (TNFR1) levels and an early decline in estimated glomerular filtration rate (eGFR) decline remains to be defined. We found that in patients with an early decline in renal function (n = 30), soluble TNFR1 values increased (2,595 ± 683 vs 3,596 ± 1,203 pg/mL, P < 0.001) as eGFR decreased (89 ± 1 vs 51 ± 2 mL/min/1.73m2 , P < 0.001) over an 8-year period. In contrast, there were no significant changes in soluble TNFR1 levels in patients with stable renal function (n = 17). In a multilevel mixed effects regression model, changes in soluble TNFR1 levels were found to be independently associated with eGFR decline (Z = -4.31, P < 0.001). An early decline in eGFR is associated with an increase in soluble TNFR levels; however, the factors driving this increase and the possible pathological role that soluble TNFR1 plays in progressive diabetic kidney disease remain to be determined.

Methods for the Detection of Seizure Bursts in Epilepsy.

Background: Seizure clusters and "bursts" are of clinical importance. Clusters are reported to be a marker of antiepileptic drug resistance. Additionally, seizure clustering has been found to be associated with increased morbidity and mortality. However, there are no statistical methods described in the literature to delineate bursting phenomenon in epileptic seizures. Methods: We present three automatic burst detection methods referred to as precision constrained grouping (PCG), burst duration constrained grouping (BCG), and interseizure interval constrained grouping (ICG). Concordance correlation coefficients were used to confirm the pairwise agreement between common bursts isolated using these three automatic burst detection procedures. Additionally, three graphical methods were employed to demonstrate seizure bursts: modified scatter plots, staircase plots, and dropline plots. Burst detection procedures are demonstrated on data from continuous intracranial ambulatory EEG monitoring in a patient diagnosed with drug-refractory focal epilepsy. Results: We analyzed 1,569 seizures, from our assigned index patient, captured on ambulatory intracranial EEG monitoring. A total of 31, 32, and 32 seizure bursts were detected by the three quantitative methods (BCG, ICG, and PCG), respectively. The concordance correlation coefficient was ≥0.99 signifying considerably stronger than chance burst detector agreements with one another. Conclusions: Bursting is a quantifiable temporal phenomenon in epilepsy and seizure bursts can be reliably detected using our methodology.

Risk factors for injury in a community-treated cohort of patients with epilepsy in Australia.

OBJECTIVE: There remains a paucity of knowledge regarding specific epilepsy-related risk factors for accidents and injuries in people with epilepsy. Injury studies in people with epilepsy are overrepresented, with tertiary based populations that are prone to bias from severe disease. This study aims to assess the contribution of epilepsy-related risk factors to injuries in a community-based cohort. METHODS: We performed a retrospective nested case-control study on patients recruited into the Tasmanian Epilepsy Register (TER) from July 1, 2001 to June 30, 2002. The TER is a community-based cohort of patients with epilepsy in Tasmania, Australia, recruited from the national prescription database and interviewed for epilepsy diagnosis, injuries, and risk factors using validated questionnaires with diagnosis made by an epilepsy specialist. The primary outcome measures were lifetime and recent 12-month injury. Multivariate logistic regression with multiple imputation modeling responder nondisclosure was performed, adjusting for age, gender, region, socioeconomic status, seizure frequency, and epilepsy duration. RESULTS: A total of 819 patients with epilepsy were included in this study. Ten percent of patients experienced an injury in the preceding year. Before adjusting for seizure frequency, any seizure over the past 12 months was associated with recent injury (adjusted odds ratio [OR] = 7.90, 95% confidence interval [CI] = 4.17-14.96). Impaired awareness, cluster seizures, sleep-only seizures, and convulsive seizure were characteristics found to significantly influence injuries irrespective of seizure frequency. Although a warning appeared initially protective for recent injuries (OR = 0.39, 95% CI = 0.22-0.69), this was entirely explained by seizure frequency, with the effect becoming nonsignificant. SIGNIFICANCE: Likely due to their unpredictable nature, seizures expose patients with epilepsy to a high risk of life-threatening injury. These findings emphasize the importance of seizure freedom for maximizing the safety of patients with epilepsy.

The acute effects of dietary carbohydrate reduction on postprandial responses of non-esterified fatty acids and triglycerides: a randomized trial.

BACKGROUND: Postprandial non-esterified fatty acid (NEFA) and triglyceride (TG) responses are increased in subjects with type 2 diabetes mellitus (T2DM) and may impair insulin action and increase risk of cardiovascular disease and death. Dietary carbohydrate reduction has been suggested as non-pharmacological therapy for T2DM, but the acute effects on NEFA and TG during subsequent meals remain to be investigated. METHODS: Postprandial NEFA and TG responses were assessed in subjects with T2DM by comparing a carbohydrate-reduced high-protein (CRHP) diet with a conventional diabetes (CD) diet in an open-label, randomized, cross-over study. Each diet was consumed on two consecutive days, separated by a wash-out period. The iso-caloric CRHP/CD diets contained 31/54 E% from carbohydrate, 29/16 E% energy from protein and 40/30 E% from fat, respectively. Sixteen subjects with well-controlled T2DM (median HbA1c 47 mmol/mol, (37-67 mmol/mol) and BMI 30 ± 4.4 kg/m2) participated in the study. NEFA and TG were evaluated following breakfast and lunch. RESULTS: NEFA net area under curve (AUC) was increased by 97 ± 38 µmol/Lx270 min (p = 0.024) after breakfast but reduced by 141 ± 33 µmol/Lx180 min (p < 0.001) after lunch on the CRHP compared with CD diet. Likewise, TG net AUC was increased by 80 ± 28 µmol/Lx270 min (p = 0.012) after breakfast but reduced by 320 ± 60 µmol/Lx180 min (p < 0.001) after lunch on the CRHP compared with CD diet. CONCLUSIONS: In well-controlled T2DM a modest reduction of dietary carbohydrate with a corresponding increase in protein and fat acutely reduced postprandial serum NEFA suppression and increased serum TG responses after a breakfast meal but had the opposite effect after a lunch meal. The mechanism behind this second-meal phenomenon of CRHP diet on important risk factors for aggravating T2DM and cardiovascular disease awaits further investigation. TRIAL REGISTRATION: The study was registered at clinicaltrials.gov ID: NCT02472951. https://clinicaltrials.gov/ct2/show/NCT02472951 . Registered June 16, 2015.

Postictal suppression and seizure durations: A patient-specific, long-term iEEG analysis.

OBJECTIVE: We report on patient-specific durations of postictal periods in long-term intracranial electroencephalography (iEEG) recordings. The objective was to investigate the relationship between seizure duration and postictal suppression duration. METHODS: Long-term recording iEEG from 9 patients (>50 seizures recorded) were analyzed. In total, 2310 seizures were recorded during a total of 13.8 years of recording. Postictal suppression duration was calculated as the duration after seizure termination until total signal energy returned to background levels. The relationship between seizure duration and postictal suppression duration was quantified using the correlation coefficient (r). The effects of populations of seizures within patients, on correlations, were also considered. Populations of seizures within patients were distinguished by seizure duration thresholds and k-means clustering along the dimensions of seizure duration and postictal suppression duration. The effects of bursts of seizures were also considered by defining populations based on interseizure interval (ISI). RESULTS: Seizure duration accounted for 40% of postictal suppression duration variance, aggregated across all patients and seizures. Seizure duration accounted for more than 25% of the variance in postictal suppression duration in 2 patients and accounted for less than 25% in the remaining 7. In 3 patients, heat maps showed multiple distinct postictal patterns indicating multiple populations of seizures. When accounting for these populations, seizure duration accounted for less than 25% of the variance in postictal duration in all populations. Variance in postictal suppression duration accounted for less than 10% of ISI variance in all patients. SIGNIFICANCE: We have previously demonstrated that some patients have multiple seizure populations distinguishable by seizure duration. This article shows that different seizure populations have distinct and consistent postictal behaviors. The existence of multiple populations in some patients has implications for seizure management and forecasting, whereas the distinct postictal behaviors may have implications for sudden unexpected death in epilepsy (SUDEP) prediction and prevention.

Characteristics of Epileptiform Discharge Duration and Interdischarge Interval in Genetic Generalized Epilepsies.

We sought to investigate (1) the characteristics of epileptiform discharge (ED) duration and interdischarge interval (IDI) and (2) the influence of vigilance state on the ED duration and IDI in genetic generalized epilepsy (GGE). In a cohort of patients diagnosed with GGE, 24-h ambulatory EEG recordings were performed prospectively. We then tabulated durations, IDI, and vigilance state in relation to all EDs captured on EEGs. We used K-means cluster analysis and finite mixture modeling to quantify and characterize the groups of ED duration and IDI. To investigate the influence of sleep, we calculated the mean, median, and SEM in each population from all subjects for sleep state and wakefulness separately, followed by the Kruskal-Wallis test to compare the groups. We analyzed 4,679 EDs and corresponding IDI from 23 abnormal 24-h ambulatory EEGs. Our analysis defined two populations of ED durations and IDI: short and long. In all populations, both ED durations and IDI were significantly longer in wakefulness. Our results highlight different characteristics of ED populations in GGE and the influence by the sleep-wake cycle.

Bursts of seizures in long-term recordings of human focal epilepsy.

OBJECTIVE: We report on temporally clustered seizures detected from continuous long-term ambulatory human electroencephalographic data. The objective was to investigate short-term seizure clustering, which we have termed bursting, and consider implications for patient care, seizure prediction, and evaluating therapies. METHODS: Chronic ambulatory intracranial electroencephalography (EEG) data collected for the purpose of seizure prediction were annotated to identify seizure events. A detection algorithm was used to identify bursts of events. Burst events were compared to nonburst events to evaluate event dispersion, duration and dynamics. RESULTS: Bursts of seizures were present in 6 of 15 subjects, and detections were consistent over long-term monitoring (>2 years). Subjects with bursts of seizures had highly overdispersed seizure rates, compared to other subjects. There was a complicated relationship between bursts and clinical seizures, although bursts were associated with multimodal distributions of seizure duration, and poorer predictive outcomes. For three subjects, bursts demonstrated distinctive preictal dynamics compared to clinical seizures. SIGNIFICANCE: We have previously hypothesized that there are distinct physiologic pathways underlying short- and long-duration seizures. Herein we show that burst seizures fall almost exclusively within the short population of seizure durations; however, a short duration event was not sufficient to induce or imply bursting. We can therefore conclude that in addition to distinct mechanisms underlying seizure duration, there are separate factors regulating bursts of seizures. We show that bursts were a robust phenomenon in our patient cohort, which were consistent with overdispersed seizure rates, suggesting long-memory dynamics.

EEG correlates of seizure freedom in genetic generalized epilepsies.

BACKGROUND: We investigated the association between epileptiform EEG abnormalities and the preceding duration of seizure freedom in genetic generalized epilepsies (GGE). METHODS: We analyzed 24-hour ambulatory EEG recordings of patients with GGE diagnosed and classified according to the International League Against Epilepsy criteria. We quantified epileptiform EEG abnormalities into density scores (total duration of epileptiform discharges per hour) and estimated the preceding seizure-free duration at the time of EEG recording based on the last self-reported seizure. We then employed regression analysis to quantitate the relationship between the duration of seizure freedom and EEG variables. RESULTS: We analyzed 6,923 epileptiform discharges from 105 patients with abnormal 24-hour EEGs. In the regression analysis exploring the crude associations, we found significant correlations between 6 EEG variables and the duration of seizure freedom indicating that shorter duration of seizure freedom was associated with higher spike densities and longer paroxysms. These associations were not affected by confounders such as syndrome, age at EEG, age at epilepsy onset, sex, duration of epilepsy, or number of antiepileptic drugs. CONCLUSIONS: Higher densities and longer durations of epileptiform discharges may be retrospectively associated with a shorter duration of self-reported seizure freedom. Hence, EEG can potentially be used as a biomarker of prognosis in GGE. These findings need to be validated in a prospective study in order to define EEG markers of future seizure freedom.

Evaluation of the Biocompatibility of Polypyrrole Implanted Subdurally in GAERS.

This blinded controlled prospective randomized study investigates the biocompatibility of polypyrrole (PPy) polymer that will be used for intracranial triggered release of anti-epileptic drugs (AEDs). Three by three millimeters PPy are implanted subdurally in six adult female genetic absence epilepsy rats from Strasbourg. Each rat has a polymer implanted on one side of the cortex and a sham craniotomy performed on the other side. After a period of seven weeks, rats are euthanized and parallel series of coronal sections are cut throughout the implant site. Four series of 15 sections are histological (hematoxylin and eosin) and immunohistochemically (neuron-specific nuclear protein, glial fibrillary acidic protein, and anti-CD68 antibody) stained and evaluated by three investigators. The results show that implanted PPy mats do not induce obvious inflammation, trauma, gliosis, and neuronal toxicity. Therefore the authors conclude the PPy used offer good histocompatibility with central nervous system cells and that PPy sheets can be used as intracranial, AED delivery implant.

Temporal patterns of epileptiform discharges in genetic generalized epilepsies.

OBJECTIVE: We sought to investigate the temporal patterns and sleep-wake cycle-related epileptiform discharges (EDs) in genetic generalized epilepsies (GGEs). METHODS: We studied 24-hour ambulatory electroencephalography (EEG) recordings of patients with GGE, diagnosed and classified according to the International League against Epilepsy criteria. We manually coded the type of discharge, time of occurrence, duration, and arousal state of each ED. We employed mixed effects Poisson regression modeling to study the temporal distribution of epileptiform discharges. Additionally, we used multinomial regression analysis to explore the significance of the relationship between different states of arousal and types of epileptiform discharges. RESULTS: We analyzed 6923 EDs from 105 abnormal 24-hour EEGs. Mixed effects Poisson regression analysis demonstrated significant changes in ED counts across time blocks. This distribution was largely influenced by the state of arousal. Generalized fragments (duration<2s) and focal discharges were more frequent during non-REM sleep while paroxysms (duration≥2s) were more frequent in wakefulness. Overall, 67% of epileptiform discharges occurred in non-REM sleep and only 33% occurred in wakefulness. Twenty-four patients (23%) had ED exclusively in sleep. Epileptiform discharges peaked from 23:00 through 07:00h. SIGNIFICANCE: There is a time-of-day dependency of ED with a significant influence exerted by the state of arousal. Our observations suggest that the generation of epileptiform discharges is not a random process but is the result of complex interactions among biological rhythms such as the sleep-wake cycle and the intrinsic circadian pacemaker. High density of ED in sleep suggests that 24-hour EEG recording with the capture of natural sleep may be more useful than routine EEG to diagnose GGE.