Association between antiseizure medications and quality of life in epilepsy: A mediation analysis

OBJECTIVE

The relationship between antiseizure medications (ASMs), which improve health outcomes by controlling seizures, and health-related quality of life (HRQOL) is poorly understood and may involve intermediate variables. We evaluated the potential mediators of the association between ASMs and HRQOL.

METHODS

Data are from an outpatient registry of adult patients with epilepsy seen at the Foothills Medical Center, Calgary, Alberta, Canada. Quality of life was measured using the 10-item Quality of Life in Epilepsy, and depression was measured using the Neurological Disorders Depression Inventory for Epilepsy. Propensity score matching was used to adjust for covariate imbalance between patients who received a single ASM (monotherapy) and those who received two or more ASMs (polytherapy) due to confounding. Mediation analysis was used to estimate the mediating effects of depression and ASM side effects on the association between patients' ASM polytherapy and HRQOL.

RESULTS

Of 778 patients included in this analysis, 274 (35.2%) were on two or more ASMs. Patient-reported depression and ASM side effects jointly mediated the association between ASMs and HRQOL; these mediators accounted for 42% of the total average effect of ASM polytherapy ( β  = -13.6, 95% confidence interval = -18.2 to -8.6) on HRQOL.

SIGNIFICANCE

These findings highlight the importance of managing depression and ASM side effects for improving health outcomes of patients requiring treatment with ASMs. Intervention programs aimed at improving HRQOL of patients with epilepsy need to target these potential mediators.

Repeated measures discriminant analysis using multivariate generalized estimation equations

Discriminant analysis procedures that assume parsimonious covariance and/or means structures have been proposed for distinguishing between two or more populations in multivariate repeated measures designs. However, these procedures rely on the assumptions of multivariate normality which is not tenable in multivariate repeated measures designs which are characterized by binary, ordinal, or mixed types of response distributions. This study investigates the accuracy of repeated measures discriminant analysis (RMDA) based on the multivariate generalized estimating equations (GEE) framework for classification in multivariate repeated measures designs with the same or different types of responses repeatedly measured over time. Monte Carlo methods were used to compare the accuracy of RMDA procedures based on GEE, and RMDA based on maximum likelihood estimators (MLE) under diverse simulation conditions, which included number of repeated measure occasions, number of responses, sample size, correlation structures, and type of response distribution. RMDA based on GEE exhibited higher average classification accuracy than RMDA based on MLE especially in multivariate non-normal distributions. Three repeatedly measured responses namely severity of epilepsy, current number of anti-epileptic drugs, and parent-reported quality of life in children with epilepsy were used to demonstrate the application of these procedures.

Association of Enzyme-Inducing Antiseizure Drug Use With Long-term Cardiovascular Disease

Importance

Enzyme-inducing antiseizure medications (eiASMs) have been hypothesized to be associated with long-term risks of cardiovascular disease.

Objective

To quantify and model the putative hazard of cardiovascular disease secondary to eiASM use.

Design, Setting, and Participants

This cohort study covered January 1990 to March 2019 (median [IQR] follow-up, 9 [4-15], years). The study linked primary care and hospital electronic health records at National Health Service hospitals in England. People aged 18 years or older diagnosed as having epilepsy after January 1, 1990, were included. All eligible patients were included with a waiver of consent. No patients were approached who withdrew consent. Analysis began January 2021 and ended August 2021.

Exposures

Receipt of 4 consecutive eiASMs (carbamazepine, eslicarbazepine, oxcarbazepine, phenobarbital, phenytoin, primidone, rufinamide, or topiramate) following an adult-onset (age ≥18 years) epilepsy diagnosis or repeated exposure in a weighted cumulative exposure model.

Main Outcomes and Measures

Three cohorts were isolated, 1 of which comprised all adults meeting a case definition for epilepsy diagnosed after 1990, 1 comprised incident cases diagnosed after 1998 (hospital linkage date), and 1 was limited to adults diagnosed with epilepsy at 65 years or older. Outcome was incident cardiovascular disease (ischemic heart disease or ischemic or hemorrhagic stroke). Hazard of incident cardiovascular disease was evaluated using adjusted propensity-matched survival analyses and weighted cumulative exposure models.

Results

Of 10 916 166 adults, 50 888 (0.6%) were identified as having period-prevalent cases (median [IQR] age, 32 [19-50] years; 16 584 [53%] female), of whom 31 479 (62%) were diagnosed on or after 1990 and were free of cardiovascular disease at baseline. In a propensity-matched Cox proportional hazards model adjusted for age, sex, baseline socioeconomic status, and cardiovascular risk factors, the hazard ratio for incident cardiovascular disease was 1.21 (95% CI, 1.06-1.39) for those receiving eiASMs. The absolute difference in cumulative hazard diverges by more than 1% and greater after 10 years. For those with persistent exposure beyond 4 prescriptions, the median hazard ratio increased from amedian (IQR) of 1.54 (1.28-1.79) when taking a relative defined daily dose of an eiASM of 1 to 2.38 (1.52-3.56) with a relative defined daily dose of 2 throughout a maximum of 25 years' follow-up compared with those not receiving an eiASM. The hazard was elevated but attenuated when restricting analyses to incident cases or those diagnosed when older than 65 years.

Conclusions and Relevance

The hazard of incident cardiovascular disease is higher in those receiving eiASMs. The association is dose dependent and the absolute difference in hazard seems to reach clinical significance by approximately 10 years from first exposure.

The use of patient-reported measures in epilepsy care: the Calgary Comprehensive Epilepsy Program experience

The regular use of patient-reported measures (PRMs) has been associated with greater patient satisfaction and outcomes. In this article, we will review the Calgary Comprehensive Epilepsy Program's successful experience with PRMs in both clinical and research settings, as well as our current challenges and future directions. Our experience will illustrate that is feasible and convenient to implement PRMs, and especially electronic PRMs (ePRMs), into epilepsy clinics. These PRMs have direct clinical and research applications. They inform clinical decision making through readily interpretable scales to which clinicians can expeditiously respond. Equally, they are increasingly forming an integral and central component of intervention and outcomes-based research. However, implementation studies are necessary to address knowledge gaps and facilitate adoption and dissemination of this approach. A natural symbiosis of the clinical and research realms is precision medicine. The foundations of precision-based interventions are now being set whereby we can maximize the quality of life and psychosocial functioning on an individual level. As illustrated in this article, this exciting prospect crucially depends on the routine use of ePRMs in the everyday care of people with epilepsy. Increasing ePRMs uptake will clearly be a catalyst propelling precision epilepsy from aspiration to clinical reality.

Epilepsy care during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has affected the care of all patients around the world. The International League Against Epilepsy (ILAE) COVID-19 and Telemedicine Task Forces examined, through surveys to people with epilepsy (PWE), caregivers, and health care professionals, how the pandemic has affected the well-being, care, and services for PWE. The ILAE included a link on their website whereby PWE and/or their caregivers could fill out a survey (in 11 languages) about the impact of the COVID-19 pandemic, including access to health services and impact on mental health, including the 6-item Kessler Psychological Distress Scale. An anonymous link was also provided whereby health care providers could report cases of new-onset seizures or an exacerbation of seizures in the context of COVID-19. Finally, a separate questionnaire aimed at exploring the utilization of telehealth by health care professionals since the pandemic began was available on the ILAE website and also disseminated to its members. Seventeen case reports were received; data were limited and therefore no firm conclusions could be drawn. Of 590 respondents to the well-being survey (422 PWE, 166 caregivers), 22.8% PWE and 27.5% caregivers reported an increase in seizure frequency, with difficulty in accessing medication and health care professionals reported as barriers to care. Of all respondents, 57.1% PWE and 21.5% caregivers had severe psychological distress (k score >13), which was significantly higher among PWE than caregivers (p<0.01). An increase in telemedicine use during the COVID-19 pandemic was reported by health care professionals, with 40% of consultations conducted by this method. Although 74.9% of health care providers thought that this impacted positively, barriers to care were also identified. As we move forward, there is a need to ensure ongoing support and care for PWE to prevent a parallel pandemic of unmet health care needs.

Comparative Effectiveness of Stereotactic Electroencephalography Versus Subdural Grids in Epilepsy Surgery

OBJECTIVE

The aim was to compare the outcomes of subdural electrode (SDE) implantations versus stereotactic electroencephalography (SEEG), the 2 predominant methods of intracranial electroencephalography (iEEG) performed in difficult-to-localize drug-resistant focal epilepsy.

METHODS

The Surgical Therapies Commission of the International League Against Epilepsy created an international registry of iEEG patients implanted between 2005 and 2019 with ≥1 year of follow-up. We used propensity score matching to control exposure selection bias and generate comparable cohorts. Study endpoints were: (1) likelihood of resection after iEEG; (2) seizure freedom at last follow-up; and (3) complications (composite of postoperative infection, symptomatic intracranial hemorrhage, or permanent neurological deficit).

RESULTS

Ten study sites from 7 countries and 3 continents contributed 2,012 patients, including 1,468 (73%) eligible for analysis (526 SDE and 942 SEEG), of whom 988 (67%) underwent subsequent resection. Propensity score matching improved covariate balance between exposure groups for all analyses. Propensity-matched patients who underwent SDE had higher odds of subsequent resective surgery (odds ratio [OR] = 1.4, 95% confidence interval [CI] 1.05, 1.84) and higher odds of complications (OR = 2.24, 95% CI 1.34, 3.74; unadjusted: 9.6% after SDE vs 3.3% after SEEG). Odds of seizure freedom in propensity-matched resected patients were 1.66 times higher (95% CI 1.21, 2.26) for SEEG compared with SDE (unadjusted: 55% seizure free after SEEG-guided resections vs 41% after SDE).

INTERPRETATION

In comparison to SEEG, SDE evaluations are more likely to lead to brain surgery in patients with drug-resistant epilepsy but have more surgical complications and lower probability of seizure freedom. This comparative-effectiveness study provides the highest feasible evidence level to guide decisions on iEEG. ANN NEUROL 2021.

Adult onset epilepsy is defined by phenotypic clusters with unique comorbidities and risks of death

OBJECTIVE

This study was undertaken to identify clusters of adult onset epilepsy with distinct comorbidities and risks of early and late death.

METHODS

This was a retrospective open cohort study that included all adults meeting a case definition for epilepsy after the Acceptable Mortality Recording date in the Health Improvement Network database for the years 2000-2012 inclusive. Unsupervised agglomerative hierarchical clustering was performed to identify unique clusters of patients based on their predicted risk of early (<4 years of epilepsy diagnosis) and late (≥4 years from diagnosis) mortality and patient-level clinical characteristics.

RESULTS

We identified 10 499 presumed incident cases of epilepsy from 11 194 182 patients. Four phenotypic clusters were identified in the early and late risk periods. Early clusters include older adults with cardiovascular disease and a high risk of death (median predicted risk = 20%, interquartile range [IQR] = 9%-31%), a group with moderate risk of death and cancer (median predicted risk = 6%, IQR = 2%-15%), a group with psychiatric disease/substance use and few somatic comorbidities (median predicted risk = 5%, IQR = 2%-9%), and one with a younger age at onset and few comorbidities (median predicted risk = 4%, IQR = 1%-11%). There was minimal movement of individuals between clusters for those surviving the early risk period. Age- and sex-standardized 3-year mortality ratios were more than sixfold higher than the general population for every cluster, even those primarily comprised of healthy younger adults.

SIGNIFICANCE

Adult onset epilepsy is marked by unique clusters of comorbid conditions and elevated risks of death that form discrete populations for targeted therapeutic interventions. These clusters remain relatively stable between the early and late mortality risk periods. Of particular interest are the clusters marked by young and otherwise healthy adults whose standardized mortality ratio is sixfold higher than general population despite few conventional risk factors for premature death.

Quality of Life in Epilepsy: Same questions, but different meaning to different people

OBJECTIVES

Patient-reported outcome measures (PROMs) are used widely to elicit patient's self-appraisal of their health status and quality of life. One fundamental assumption when measuring PROMs is that all individuals interpret questions about their health status in a consistent manner. However, subgroups of patients with a similar health condition may respond differently to PROM questions (ie, differential item functioning [DIF]), leading to biased estimates of group differences on PROM scores. Understanding these differences can help inform the clinical interpretation of PROMs. This study examined whether DIF affects 10-item Quality of Life in Epilepsy (QOLIE10) scores reported by patients with epilepsy in outpatient clinics.

METHODS

Data were from the Calgary Comprehensive Epilepsy Program, a prospective registry of patients with epilepsy in Calgary, Alberta. Latent variable mixture models (LVMMs) based on standard two-parameter graded response models with increasing numbers of latent classes were applied to QOLIE10 item data. Model fit was assessed using the Bayesian Information Criterion (BIC) and latent class model entropy. Ordinal logistic regression was used to identify QOLIE10 items that exhibited DIF.

RESULTS

In this cohort of 1143 patients, 567 (49.6%) were female and the median age was 37.0 (interquartile range [IQR] 27.0) years. A two-class LVMM, which provided the best fit to the data, identified two subgroups of patients with different response patterns to QOLIE10 items, with class proportions of 0.62 and 0.38. The two subgroups differed with respect to antiseizure polytherapy, reported medication side effects, frequency of seizures, and psychiatric comorbidities. QOLIE10 items on the physical and psychological side effects of medication exhibited large DIF effects.

SIGNIFICANCE

Our study revealed two different response patterns to quality-of-life instruments, suggesting heterogeneity in how patients interpret some of the questions. Researchers and users of PROMs in epilepsy need to consider the differential interpretation of items for various instruments to ensure valid understanding and comparisons of PROM scores.

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.

Predicting postoperative epilepsy surgery satisfaction in adults using the 19-item Epilepsy Surgery Satisfaction Questionnaire and machine learning

OBJECTIVE

The 19-item Epilepsy Surgery Satisfaction Questionnaire (ESSQ-19) is a validated and reliable post hoc means of assessing patient satisfaction with epilepsy surgery. Prediction models building on these data can be used to counsel patients.

METHODS

The ESSQ-19 was derived and validated on 229 patients recruited from Canada and Sweden. We isolated 201 (88%) patients with complete clinical data for this analysis. These patients were adults (≥18 years old) who underwent epilepsy surgery 1 year or more prior to answering the questionnaire. We extracted each patient's ESSQ-19 score (scale is 0-100; 100 represents complete satisfaction) and relevant clinical variables that were standardized prior to the analysis. We used machine learning (linear kernel support vector regression [SVR]) to predict satisfaction and assessed performance using the R² calculated following threefold cross-validation. Model parameters were ranked to infer the importance of each clinical variable to overall satisfaction with epilepsy surgery.

RESULTS

Median age was 41 years (interquartile range [IQR] = 32-53), and 116 (57%) were female. Median ESSQ-19 global score was 68 (IQR = 59-75), and median time from surgery was 5.4 years (IQR = 2.0-8.9). Linear kernel SVR performed well following threefold cross-validation, with an R² of .44 (95% confidence interval = .36-.52). Increasing satisfaction was associated with postoperative self-perceived quality of life, seizure freedom, and reductions in antiseizure medications. Self-perceived epilepsy disability, age, and increasing frequency of seizures that impair awareness were associated with reduced satisfaction.

SIGNIFICANCE

Machine learning applied postoperatively to the ESSQ-19 can be used to predict surgical satisfaction. This algorithm, once externally validated, can be used in clinical settings by fixing immutable clinical characteristics and adjusting hypothesized postoperative variables, to counsel patients at an individual level on how satisfied they will be with differing surgical outcomes.

The road to a World Health Organization global action plan on epilepsy and other neurological disorders

The World Health Organization (WHO) has recognized epilepsy as a public health imperative due to its occurrence at all ages in all regions of the world, its high impact on disability-adjusted life years and psychosocial aspects, and the accompanying stigma. The International League Against Epilepsy and the International Bureau for Epilepsy have established crucial collaborations with regional and global organizations to promote epilepsy as a treatable disease, close the treatment gap in care, education, and research, and eradicate stigma. In November 2020, the efforts of these three organizations-with support from WHO member states, the World Federation of Neurology, and the European Federation of Neurological Associations-culminated in the unanimous approval of a WHO resolution to create and implement an Intersectoral Global Action Plan on Epilepsy and Other Neurological Disorders. This unique achievement is built on more than 2 decades of collaboration and effort, and heralds extraordinary opportunities to work toward a world where no person's life is limited by epilepsy.

Automated seizure detection using wearable devices: A clinical practice guideline of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology

The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) and focal-to-bilateral tonic-clonic seizures (FBTCS) and recommend the use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found a moderate level of evidence for seizure types without GTCS or FBTCS. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.

Impact of ictal subtraction SPECT and PET in presurgical evaluation

OBJECTIVE

To assess the relative contribution of ictal subtraction single-photon emission computed tomography (ISSPECT) and ¹⁸ F-fluorodeoxyglucose positron emission tomography computed tomography (PET) in epilepsy surgery decision making.

MATERIALS AND METHODS

A retrospective 3-year study of consecutive patients with resistant focal epilepsy who underwent ISSPECT and PET to evaluate to what extent these modalities influence decisions in epilepsy surgery and outcomes. ISSPECT imaging was performed in 106 patients and 58 (55%) had PET also. The clinical consensus (ClinC) was the final arbiter for decisions. Post-surgical outcomes were collected from follow-up clinics. Non-parametric statistics were used to assess association and logistic regression to evaluate prediction of outcomes.

RESULTS

Of 106 patients, 60 were males (57%). MRI was non-lesional in 46 (43%). Concordance with ClinC was seen in 80 patients (76%) for ISSPECT, in 46 patients (79%) for PET, and in 37 patients (64%) for ISSPECT + PET. Fifty-six patients (53%) were planned for intracranial video-electroencephalography monitoring (IVEM). Those with ClinC-PET concordance were likely to proceed to IVEM (p = 0.02). ClinC-PET concordance and ClinC-ISSPECT concordance did not predict decision to proceed to surgery, but VEM-MRI concordance did in lesional cases (p = 0.018). Forty-five (42%) underwent surgery of which 29 had minimum follow-up for 1 year (mean, 20 months; SD, 8) and 22 (76%) had Engel class I outcomes. ClinC-ISSPECT concordance (p = 0.024) and VEM-MRI concordance (p = 0.016) predicted Engel class I outcomes.

CONCLUSION

Those with ClinC-PET concordance were more likely to proceed with IVEM. ClinC-ISSPECT concordance and VEM-MRI concordance predicted good surgical outcomes.

The initial impact of the SARS-CoV-2 pandemic on epilepsy research

The COVID-19 pandemic has changed the face of many practices throughout the world. Through necessity to minimize spread and provide clinical care to those with severe disease, focus has been on limiting face-to-face contact. Research in many areas has been put on hold. We sought to determine the impact of the COVID-19 pandemic on epilepsy research from international basic science and clinical researchers. Responses to five questions were solicited through a convenience sample by direct email and through postings on the ILAE social media accounts and an ILAE online platform (utilizing Slack). Information was collected from 15 respondents in 11 countries by email or via Zoom interviews between May 19, 2020, and June 4, 2020. Several themes emerged including a move to virtual working, project delays with laboratory work halted and clinical work reduced, funding concerns, a worry about false data with regard to COVID research and concern about research time lost. However, a number of positive outcomes were highlighted, not least the efficiency of online working and other adaptations that could be sustained in the future.

Complementary and alternative medicine (CAM) for epilepsy treatment in the Middle East and North Africa (MENA) region

INTRODUCTION

The aim of this study is to provide the reader with a review on Complementary and Alternative Medicine (CAM) treatment in epilepsy in the Middle East and North Africa (MENA) region, to describe the extent and factors associated with its use among patients with epilepsy (PWE), and to recommend how effectively we will be able to reduce this alarming use.

MATERIAL AND METHODS

Retrospective literature search from 1945 to December 2019, regarding CAM use in the MENA region, using electronic databases (PubMed, Scopus, Google Scholar, Web of Science).

CONCLUSION

The use of CAM and consultation of traditional healers for the treatment of epilepsy has so far been widespread practice for centuries in the MENA region. Lack of health professionals and non-adherence to conventional epilepsy treatment are strongly associated with the use of CAM. Improvement in the level of knowledge of epilepsy among PWE, healthcare professionals, including traditional healers, will educate PWE and their caregivers on potentially unsafe practices and promote adherence to Antiseizure Drugs (ASDs). Additionally, randomized controlled trials are needed to study the role and value of various CAM treatment options in PWEs.

Primary care electronic medical records can be used to predict risk and identify potentially modifiable factors for early and late death in adult onset epilepsy

OBJECTIVE

To use clinically informed machine learning to derive prediction models for early and late premature death in epilepsy.

METHODS

This was a population-based primary care observational cohort study. All patients meeting a case definition for incident epilepsy in the Health Improvement Network database for inclusive years 2000-2012 were included. A modified Delphi process identified 30 potential risk factors. Outcome was early (within 4 years of epilepsy diagnosis) and late (4 years or more from diagnosis) mortality. We used regularized logistic regression, support vector machines, Gaussian naive Bayes, and random forest classifiers to predict outcomes. We assessed model calibration, discrimination, and generalizability using the Brier score, mean area under the receiver operating characteristic curve (AUC) derived from stratified fivefold cross-validation, plotted calibration curves, and extracted measures of association where possible.

RESULTS

We identified 10 499 presumed incident cases from 11 194 182 patients. All models performed comparably well following stratified fivefold cross-validation, with AUCs ranging from 0.73 to 0.81 and from 0.71 to 0.79 for early and late death, respectively. In addition to comorbid disease, social habits (alcoholism odds ratio [OR] for early death = 1.54, 95% confidence interval [CI] = 1.12-2.11 and OR for late death = 2.62, 95% CI = 1.66-4.16) and treatment patterns (OR for early death when no antiseizure medication [ASM] was prescribed at baseline = 1.33, 95% CI = 1.07-1.64 and OR for late death after receipt of enzyme-inducing ASM at baseline = 1.32, 95% CI = 1.04-1.66) were significantly associated with increased risk of premature death. Baseline ASM polytherapy (OR = 0.55, 95% CI = 0.36-0.85) was associated with reduced risk of early death.

SIGNIFICANCE

Clinically informed models using routine electronic medical records can be used to predict early and late mortality in epilepsy, with moderate to high accuracy and evidence of generalizability. Medical, social, and treatment-related risk factors, such as delayed ASM prescription and baseline prescription of enzyme-inducing ASMs, were important predictors.

Severe hypercalcemia and a pelvic brown tumor in an adolescent with primary hyperparathyroidism: a case report

BACKGROUND

Primary hyperparathyroidism may present in a myriad of manners, varying from an incidental asymptomatic biochemical finding to gastrointestinal, psychiatric, renal, and bone manifestations. While hyperparathyroidism remains a rare diagnosis in the pediatric population, the initial approach to diagnosis and management of hypercalcemia in children is imperative for the general pediatrician. Herein, we describe an adolescent who presented with a lytic bone lesion and severe, symptomatic hypercalcemia due to primary hyperparathyroidism.

CASE PRESENTATION

A 14-year-old male presented with vomiting, constipation, abdominal pain, and lethargy. He had an elevated total corrected calcium of 4.3 mmol/L. He was found to have a large pelvic lytic tumor consistent with a brown tumor due to primary hyperparathyroidism. He received pharmacologic therapy for stabilization of his hypercalcemia, including intravenous saline, intravenous bisphosphonates, and calcitonin. He subsequently received definitive therapy via parathyroidectomy and his post-operative course was complicated by hungry bone syndrome. Long-term follow-up has found full resolution of the lytic lesion and restored calcium homeostasis.

CONCLUSIONS

We present this case to highlight the possible presentations of hypercalcemia and hyperparathyroidism that are essential for a general pediatrician to recognize to ensure prompt diagnosis and management. Evaluation for hypercalcemia should be considered in patients with suggestive symptoms and physical exam findings. To our knowledge, this patient represents the first reported pediatric case of a pelvic brown tumor in an adolescent. While the multi-systemic complications of hyperparathyroidism may be quite severe, swift and appropriate management may mitigate these clinical outcomes.

Precision Medicine: Academic dreaming or clinical reality?

Precision medicine can be distilled into a concept of accounting for an individual's unique collection of clinical, physiologic, genetic, and sociodemographic characteristics to provide patient-level predictions of disease course and response to therapy. Abundant evidence now allows us to determine how an average person with epilepsy will respond to specific medical and surgical treatments. This is useful, but not readily applicable to an individual patient. This has brought into sharp focus the desire for a more individualized approach through which we counsel people based on individual characteristics, as opposed to population-level data. We are now accruing data at unprecedented rates, allowing us to convert this ideal into reality. In addition, we have access to growing volumes of administrative and electronic health records data, biometric, imaging, genetics data, microbiome, and other "omics" data, thus paving the way toward phenome-wide association studies and "the epidemiology of one." Despite this, there are many challenges ahead. The collating, integrating, and storing sensitive multimodal data for advanced analytics remains difficult as patient consent and data security issues increase in complexity. Agreement on many aspects of epilepsy remains imperfect, rendering models sensitive to misclassification due to a lack of "ground truth." Even with existing data, advanced analytics models are prone to overfitting and often failure to generalize externally. Finally, uptake by clinicians is often hindered by opaque, "black box" algorithms. Systematic approaches to data collection and model generation, and an emphasis on education to promote uptake and knowledge translation, are required to propel epilepsy-based precision medicine from the realm of the theoretical into routine clinical practice.

Association of Levels of Specialized Care With Risk of Premature Mortality in Patients With Epilepsy

Importance

Patients with epilepsy are at an elevated risk of premature mortality. Interventions to reduce this risk are crucial.

Objective

To determine if the level of care (non-neurologist, neurologist, or comprehensive epilepsy program) is negatively associated with the risk of premature mortality.

Design, Setting, and Participants

In this retrospective open cohort study, all adult patients 18 years or older who met the administrative case definition for incident epilepsy in linked databases (Alberta Health Services administrative health data and the Comprehensive Calgary Epilepsy Programme Registry [CEP]) inclusive of the years 2002 to 2016 were followed up until death or loss to follow-up. The final analyses were performed on May 1, 2019.

Exposures

Evaluation by a non-neurologist, neurologist, or epileptologist.

Main Outcomes and Measures

The outcome was all-cause mortality. We used extended Cox models treating exposure to a neurologist or the CEP as time-varying covariates. Age, sex, socioeconomic deprivation, disease severity, and comorbid burden at index date were modeled as fixed-time coefficients.

Results

A total 23 653 incident cases were identified (annual incidence of 89 per 100 000); the mean age (SD) at index date was 50.8 (19.1) years and 12 158 (50.3%) were women. A total of 14 099 (60%) were not exposed to specialist neurological care, 9554 (40%) received care by a neurologist, and 2054 (9%) received care in the CEP. In total, 4098 deaths (71%) occurred in the nonspecialist setting, 1481 (26%) for those seen by a neurologist, and 176 (3%) for those receiving CEP care. The standardized mortality rate was 7.2% for the entire cohort, 9.4% for those receiving nonspecialist care, 5.6% for those seen by a neurologist, and 2.8% for those seen in the CEP. The hazard ratio (HR) of mortality was lower in those receiving neurologist (HR, 0.85; 95% CI, 0.77-0.93) and CEP (HR, 0.49; 95% CI, 0.38-0.62) care. In multivariable modeling, specialist care, the age at index, and disease severity were retained in the final model of the association between specialist care and mortality.

Conclusions and Relevance

Exposure to specialist care is associated with incremental reductions in the hazard of premature mortality. Those referred to a comprehensive epilepsy program received the greatest benefit.

Is bad brain worse than no brain? Salvaging the cerebral cortex in epilepsy

This scientific commentary refers to ‘Resective surgery prevents progressive cortical thinning in temporal lobe epilepsy’, by Galovic et al. (doi:10.1093/brain/awaa284).

The memory assessment clinics scale for epilepsy (MAC-E): A brief measure of subjective cognitive complaints in epilepsy

OBJECTIVE

The aim of this study was to conduct item reduction of the Memory Assessment Clinics Self-Rating Scale (MAC-S) to create a briefer measure that can be used to quickly evaluate subjective memory complaints in patients with epilepsy. Method: A total of 1333 adults with focal epilepsy completed the original 49-item MAC-S. The sample was randomly split into three subsamples, and a series of analyses (i.e. exploratory factor analysis, confirmatory factor analysis, and item response theory analyses) was conducted to identify an alternative factor structure, with a reduced number of items. A panel of 5 neuropsychologists independently reviewed the final model to assess appropriateness of each individual item as well as the factor loadings and overall factor structure. Final factor titles were subsequently decided as a group. Results: Five factors were identified: Attention, Working Memory, Retrieval, Semantic Memory, and Episodic Memory. The length of the MAC-S was reduced from 49 to 30 items, with items being removed because they failed to load onto any of the factors substantially, or because of poor item discrimination or threshold levels. Conclusions: The Memory Assessment Clinics Scale for Epilepsy (MAC-E), is an updated, brief measure of subjective memory functioning that can be used to efficiently assess relevant, every-day memory abilities in patients with epilepsy within both clinical and research settings.

Self-reported quality of life and degree of youth-parent agreement: A long-term follow-up of childhood-onset epilepsy

OBJECTIVE

To prospectively delineate self-reported health-related quality of life (HRQOL) of adolescents and young adults (AYAs) 8 and 10 years after an epilepsy diagnosis and evaluate the degree of AYA-parent agreement in ratings of AYA's HRQOL.

METHODS

Data came from the Health-Related Quality of Life in Children with Epilepsy Study (HERQULES), a 10-year longitudinal study of children, aged 4-12 years, with newly diagnosed epilepsy. Epilepsy-specific HRQOL was self-reported by AYA 8 and 10 years after diagnosis and by parents at multiple time points throughout the 10-year follow-up. Measurers of HRQOL over time were analyzed using a linear mixed-effect model approach. AYA-parent agreement was evaluated using intraclass correlation coefficient (ICC) and Bland-Altman plots.

RESULTS

A total of 165 AYAs participated at long-term follow-up. There was considerable heterogeneity among AYA's HRQOL, and as a group, there was no significant change in HRQOL from the 8- to 10-year follow-up. Household income at the time of diagnosis, seizure control at follow-up, and a history of emotional problems (anxiety/depression) were independent predictors of HRQOL at follow-up. AYA-parent agreement on AYA's HRQOL was moderate (ICC 0.62, 95% CI 0.51-0.71), although considerable differences were observed at the individual level. AYA-parent agreement varied with AYA's and parent's age, seizure control, and family environment.

SIGNIFICANCE

In the long-term after a diagnosis of epilepsy, AYAs report stable HRQOL over time at the group level, although notable individual differences exist. Seizure control, anxiety/depression, and family environment meaningfully impact AYA's long-term HRQOL. AYA and parent reports on HRQOL are similar at the group level, although they cannot be used interchangeably, given the large individual differences observed.