Decrease in mortality of adult epilepsy patients since 1980: lessons learned from a hospital-based cohort

Evidence based noninvasive presurgical evaluation for patients with drug resistant epilepsies

PURPOSE OF REVIEW

To review the current practices and evidence for the diagnostic accuracy and the benefits of presurgical evaluation.

RECENT FINDINGS

Preoperative evaluation of patients with drug-resistant focal epilepsies and subsequent epilepsy surgery leads to a significant proportion of seizure-free patients. Even those who are not completely seizure free postoperatively often experience improved quality of life with better social integration. Systematic reviews and meta-analysis on the diagnostic accuracy are available for Video-electroencephalographic (EEG) monitoring, magnetic resonance imaging (MRI), electric and magnetic source imaging, and functional MRI for lateralization of language and memory. There are currently no evidence-based international guidelines for presurgical evaluation and epilepsy surgery.

SUMMARY

Presurgical evaluation is a complex multidisciplinary and multiprofessional clinical pathway. We rely on limited consensus-based recommendations regarding the required staffing or methodological expertise in epilepsy centers.

Additional overnight video EEG for the diagnosis of epilepsy: Experiences from Western Kenya

Objective

The prolonged video EEG monitoring is widely used for the diagnosis and management of epilepsy, especially during the presurgical evaluation. The routine practice in neurology is to order a prolonged recording like an overnight EEG when the initial routine EEG is normal or unrevealing. Only few studies have evaluated this sequential approach and we aimed in this study to evaluate the added diagnostic value of a relatively brief video EEG monitoring especially in developing nations where the history of seizure semiology may be harder to obtain, and the video EEG monitoring technology is scarce.

Methods

This study analyzed retrospectively 167 overnight video EEG records in one of the secondary healthcare facilities in Western Kenya between March 2018 and March 2021. The indications were mainly further diagnosis and seizure classification. All the patients had an unrevealing routine EEG and 162 of them were normal.

Results

Additional epileptiform discharges were recorded in 91 of those 162 with initial normal routine EEG. Further classification of seizure was achieved in 67 patients among 112 with initially unclassified seizure before the overnight recording. The improvement of 68% (97 out of 143 patients without a prior epilepsy diagnosis) for the diagnosis of epilepsy in those patients without initial final diagnosis is comparable to other similar studies but mostly with a longer duration of recording. The diagnosis was changed or at least improved in 142 (85%) patients out of the 167 patients who underwent the overnight video EEG. The treatment modification was immediately considered in 116 after the prolonged recording.

Conclusions

Adding an overnight video EEG to an unrevealing routine EEG can significantly increase the likelihood of detecting additional epileptiform discharges in patients with epilepsy, thereby improving diagnostic yield and aiding in treatment adjustment for all patients suspected of having epilepsy.

Significance

The sequential approach of adding a prolonged video EEG monitoring even as brief as an overnight video EEG to an unrevealing routine EEG has a very significant impact in further classification of seizure and diagnosis of epilepsy especially in a resource limited set up.

The impact of the time to last seizure before admission to the epilepsy monitoring unit (EMU) on epilepsy classifications

INTRODUCTION AND BACKGROUND

The impact of the timing of the last seizure (TTLS) prior to admission to the epilepsy monitoring unit (EMU) on epilepsy classification is unclear for which we conducted this study.

METHODS

We reviewed patients with epilepsy admitted to EMU between January 2021 and April 2022 and identified TTLS before EMU admission. We considered EMU yield as whether; it confirmed epilepsy classification, added new knowledge to the classification, or failed to classify epilepsy.

RESULTS

We studied 156 patients. There were 72 (46%) men, with a mean age of 30. TTLS was divided according to a one- or three-month cutoff. We confirmed the pre-EMU epilepsy classification in 52 (33%) patients, learned new findings on epilepsy classification in 80 (51%) patients, and failed to classify epilepsy in 24 (15%) patients. Patients with "confirmed epilepsy classifications" reported seizures sooner to EMU admission than other groups (0.7 vs. 2.3 months, p-value = 0.02, 95% CI; -1.8, -1.3). Also, the odds of confirming epilepsy classification were more than two times in patients with TTLS within a month compared to those with TTLS of more than a month (OR = 2.4, p-value = 0.04, 95% CI; 1.1, 5.9). The odds were also higher when the 3-month TTLS cutoff was considered (OR = 6.2, p-value = 0.002, 95% CI; 1.6, 40.2). Confirming epilepsy classification was also associated with earlier seizures recorded at one- or three-month cutoff (OR = 2.1 and OR = 2.3, respectively, p-value = 0.05). We did not observe similar findings when we modified the classification or failed to reach a classification.

CONCLUSIONS

The timing of the last seizure before EMU admission appeared to influence the yield of EMU and enhanced the confirmation of epilepsy classifications. Such findings can improve the utilization of EMU in the presurgical evaluation of patients with epilepsy.

Mortality, and life expectancy in Epilepsy and Status epilepticus-current trends and future aspects

Patients with epilepsy carry a risk of premature death which is on average two to three times higher than in the general population. The risk of death is not homogenously distributed over all ages, etiologies, and epilepsy syndromes. People with drug resistant seizures carry the highest risk of death compared to those who are seizure free, whose risk is similar as in the general population. Most of the increased risk is directly related to the cause of epilepsy itself. Sudden unexplained death in epilepsy patients (SUDEP) is the most important cause of epilepsy-related deaths especially in the young and middle-aged groups. Population based studies with long-term follow up demonstrated that the first years after diagnosis carry the highest risk of death, while in the later years the mortality decreases. Improved seizure control and being exposed to a specialized comprehensive care centre may help to reduce the risk of death in patients with epilepsy. The mortality of status epilepticus is substantially increased with case fatality rates between 4.6% and 39%, depending on its cause and duration, and the age of the population studied. The epidemiological data on overall and cause specific mortality as well as their determinants and risk factors are critically reviewed and methodological issues pertinent to the studies on mortality of epilepsy and Status epilepticus are discussed.

Cause-specific mortality and life years lost in people with epilepsy: a Danish cohort study

Mortality rates are two to three times higher in people with epilepsy than in the general population. This study aimed to quantify how this increased mortality translates into reduced life expectancy and to identify the underlying causes of deaths, thereby offering suggestions for how to reduce mortality associated with epilepsy. In this population-based cohort study, we included all individuals aged 0-94 years who were living in Denmark between 2000 and 2015. Using the nationwide registers, we identified people diagnosed with epilepsy and estimated the excess of life years lost due to 13 overall and nine specific causes of death. Among 6 022 160 people, we identified 129 598 with epilepsy (52.6% males), with a mean age of epilepsy onset of 36.5 years (standard deviation = 26.3 years). During the 16 years of follow-up, 851 087 individuals died, and of these 36 923 had been diagnosed with epilepsy. The average reduction in life expectancy in people with epilepsy was 11.84 years in males (95% confidence interval: 11.66-12.00) and 10.91 years in females (95% confidence interval: 10.70-11.11) compared to the general population. Life expectancy was reduced irrespective of epilepsy aetiology (symptomatic ∼14 years; idiopathic ∼8-10 years), and in particular in people with epilepsy and psychiatric comorbidity (∼13-16 years). Excess mortality was evident across all causes of death including cardiovascular disorders, accidents, and suicide. People with epilepsy experience a substantial reduction in lifespan that can only partly be explained by underlying conditions. Prevention of epilepsy-related deaths should focus on the consequences of psychiatric comorbidity and on modifiable risk factors associated with preventable causes of death such as accidents and neurological and cardiovascular disorders.

Importance of access to epilepsy monitoring units during the COVID-19 pandemic: Consensus statement of the International League against epilepsy and the International Federation of Clinical Neurophysiology

Restructuring of healthcare services during the COVID-19 pandemic has led to lockdown of Epilepsy Monitoring Units (EMUs) in many hospitals. The ad-hoc taskforce of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) highlights the detrimental effect of postponing video-EEG monitoring of patients with epilepsy and other paroxysmal events. The taskforce calls for action to continue functioning of Epilepsy Monitoring Units during emergency situations, such as the COVID-19 pandemic. Long-term video-EEG monitoring is an essential diagnostic service. Access to video-EEG monitoring of the patients in the EMUs must be given high priority. Patients should be screened for COVID-19, before admission, according to the local regulations. Local policies for COVID-19 infection control should be adhered to during the video-EEG monitoring. In cases of differential diagnosis where reduction of antiseizure medication is not required, consider home video-EEG monitoring as an alternative in selected patients.

Neurodegenerative disease is associated with increased incidence of epilepsy: a population based study of older adults

OBJECTIVE

To determine the incidence of epilepsy among Medicare beneficiaries with a new diagnosis of Alzheimer dementia (AD) or Parkinson disease (PD).

METHODS

Retrospective cohort study of Medicare beneficiaries with an incident diagnosis of AD or PD in the year 2009. The 5-year incidence of epilepsy was examined by sociodemographic characteristics, comorbidities and neurodegenerative disease status. Cox regression models examined the association of neurodegenerative disease with incident epilepsy, adjusting for demographic characteristics and medical comorbidities.

RESULTS

We identified 178,593 individuals with incident AD and 104,157 individuals with incident PD among 34,054,293 Medicare beneficiaries with complete data in 2009. Epilepsy was diagnosed in 4.45% (7,956) of AD patients and 4.81% (5,010) of PD patients between 2009 and 2014, approximately twice as frequently as in the control sample. Minority race/ethnicity was associated with increased risk of incident epilepsy. Among individuals with AD and PD, stroke was associated with increased epilepsy risk. Traumatic brain injury (TBI) was associated with increased epilepsy risk for individuals with PD. Depression was also associated with incident epilepsy (AD adjusted hazard ratio (AHR): 1.23 (1.17-1.29), PD AHR: 1.45 (1.37-1.54)). In PD only, a history of hip fracture (AHR, 1.35 (1.17-1.57)) and diabetes (AHR, 1.11 (1.05-1.18) were also associated with increased risk of epilepsy.

CONCLUSION

Incident epilepsy is more frequently diagnosed among neurodegenerative disease patients, particularly when preceded by a diagnosis of depression, TBI or stroke. Further studies into the differences in epilepsy risk between these two populations may help elucidate different mechanisms of epileptogenesis.

Predictors of Mortality in Older Adults With Epilepsy: Implications for Learning Health Systems

OBJECTIVE

To determine the incidence of epilepsy and subsequent 5-year mortality among older adults, as well as characteristics associated with mortality.

METHODS

This was a retrospective cohort study of Medicare beneficiaries age 65 or above with at least 2 years enrollment before January 2009. Incident epilepsy cases were identified in 2009 using ICD-9-CM code-based algorithms; death was assessed through 2014. Cox regression models examined the association between 5-year mortality and incident epilepsy, and whether mortality differed by sociodemographic characteristics or comorbid disorders.

RESULTS

Among the 99,990 of 33,615,037 beneficiaries who developed epilepsy, most were White (79.7%), female (57.3%), urban (80.5%), and without Medicaid (71.3%). The 5-year mortality rate for incident epilepsy was 62.8% (62,838 deaths). In multivariable models, lower mortality was associated with female sex (adjusted hazards ratio [AHR] 0.85, 95% confidence interval [CI] 0.84-0.87), Asian race (AHR 0.82, 95% CI 0.76-0.88), and Hispanic ethnicity (AHR 0.81, 95% CI 0.76-0.84). Hazard of death increased with comorbid disease burden (per 1-point increase: AHR 1.27, 95% CI 1.26-1.27) and Medicaid coinsurance (AHR 1.17, 95% CI 1.14-1.19). Incident epilepsy was particularly associated with higher mortality when diagnosed after another neurologic condition: Parkinson disease (AHR 1.29, 95% CI 1.21-1.38), multiple sclerosis (AHR 2.13, 95% CI 1.79-2.59), dementia (AHR 1.33, 95% CI 1.31-1.36), traumatic brain injury (AHR 1.55, 95% CI 1.45-1.66), and stroke/TIA (AHR 1.20, 95% CI 1.18-1.21).

CONCLUSIONS

Newly diagnosed epilepsy is associated with high 5-year mortality among Medicare beneficiaries. Future studies that parse the interplay of effects from underlying disease, race, sex, and poverty on mortality will be critical in the design of learning health care systems to reduce premature deaths.

Overall and cause-specific premature mortality in epilepsy: A systematic review

BACKGROUND

We conducted a systematic review to ascertain the overall mortality and causes of premature mortality in epilepsy.

METHODOLOGY

We searched PubMed and Embase to identify relevant articles reporting mortality in epilepsy. An assessment of the methodological quality and overall quality of evidence of the identified studies was done using appropriate checklists. We extracted data from these studies reporting measures of overall and cause-specific mortality in epilepsy.

RESULTS

Sixty-three articles from fifty-six cohorts met the eligibility criteria, thirty-three population- or community-based and twenty-three hospital- or institutional-based studies. The majority of studies are from high-income countries (HIC). These studies reported overall excess mortality for people with epilepsy, with wide variability reported for population- or community-based studies and from low- and middle-income countries (LMIC). Twenty-seven articles from twenty-three cohorts reported measures of mortality for cause-specific mortality in epilepsy. People with epilepsy from HIC and LMIC have a higher risk of dying from various causes compared with the general population. Those in LMIC, however, have a particularly high chance of dying from external causes such as drowning and suicide. We observed a decrement over time in measures of overall and cause-specific mortality in cohorts.

CONCLUSIONS

Despite the heterogeneity in reports, our findings support the suggestions that people with epilepsy have an increased risk of premature mortality from various causes. Further work is needed to elucidate the mechanisms, to determine biomarkers for predicting those at risk, and to understand the implications of counseling and preventive strategies.

Early Seizure Detection Based on Cardiac Autonomic Regulation Dynamics

Epilepsy is a neurological disorder that causes changes in the autonomic nervous system. Heart rate variability (HRV) reflects the regulation of cardiac activity and autonomic nervous system tone. The early detection of epileptic seizures could foster the use of new treatment approaches. This study presents a new methodology for the prediction of epileptic seizures using HRV signals. Eigendecomposition of HRV parameter covariance matrices was used to create an input for a support vector machine (SVM)-based classifier. We analyzed clinical data from 12 patients (9 female; 3 male; age 34.5 ± 7.5 years), involving 34 seizures and a total of 55.2 h of interictal electrocardiogram (ECG) recordings. Data from 123.6 h of ECG recordings from healthy subjects were used to test false positive rate per hour (FP/h) in a completely independent data set. Our methodological approach allowed the detection of impending seizures from 5 min to just before the onset of a clinical/electrical seizure with a sensitivity of 94.1%. The FP rate was 0.49 h⁻¹ in the recordings from patients with epilepsy and 0.19 h⁻¹ in the recordings from healthy subjects. Our results suggest that it is feasible to use the dynamics of HRV parameters for the early detection and, potentially, the prediction of epileptic seizures.