Direct-Acting Oral Anticoagulants and Antiseizure Medications for Atrial Fibrillation and Epilepsy and Risk of Thromboembolic Events.

Importance: Direct-acting oral anticoagulants (DOACs) are commonly prescribed with antiseizure medications (ASMs) due to concurrency of and the association between atrial fibrillation (AF) and epilepsy. However, enzyme-inducing (EI) ASMs may reduce absorption and accelerate metabolism of DOACs, potentially lowering DOAC levels and elevating thromboembolism risk. Objective: To assess the rates of thromboembolic and major bleeding events in adults with AF and epilepsy dispensed DOACs and EI ASMs vs DOACs with non-EI ASMs. Design, Setting, and Participants: This active-comparator, new-user cohort study included US health care data from the Clinformatics Data Mart database from October 2010 to September 2021 for a nationally representative population of adults with AF and epilepsy. Exposure: Evaluations included episodes of contiguous coadministration of DOACs for AF with EI ASMs (exposed) or non-EI ASMs (referent) for epilepsy. Main Outcomes and Measures: Thromboembolic events (primary outcome) and major bleeding events (secondary outcome) were identified based on a series of validated, diagnosis-based coding algorithms. Data-adaptive, high-dimensional propensity score matching was used to control for observed confounders and proxies for unobserved confounders. Adjusted hazard ratios (AHRs) were estimated using Cox proportional hazards regression models with robust variance estimators to account for clustering within matched pairs. Results: This study included 14 078 episodes (median age, 74 [IQR, 67-81]; 52.4% female) and 14 158 episodes (median age, 74 [IQR, 67-81]; 52.4% female) of incident DOAC and ASM use that met eligibility criteria for assessment of thromboembolic and major bleeding outcomes, respectively. Incidence was 88.5 per 1000 person-years for thromboembolic events and 68.3 per 1000 person-years for bleeding events. Compared with use of non-EI ASMs, use of EI ASMs with DOACs was not associated with a difference in risk of thromboembolic events (AHR, 1.10; 95% CI, 0.82-1.46) but was associated with a reduction in risk of major bleeding events (AHR, 0.63; 95% CI, 0.44-0.89). Conclusions and Relevance: In this cohort study, EI ASMs were not associated with alteration in DOAC efficacy. Further research is needed on the reduction in bleeding risk associated with EI ASMs, as this may suggest that pharmacokinetic interactions are associated with lowering DOAC levels without negating therapeutic effects.

Thinking Three-Dimensionally: A Self- and Externally-Controlled Approach to Screening for Drug-Drug-Drug Interactions Among High-Risk Populations.

The global rise in polypharmacy has increased both the necessity and complexity of drug-drug interaction (DDI) assessments, given the growing potential for interactions involving more than two drugs. Leveraging large-scale healthcare claims data, we piloted a semi-automated, high-throughput case-crossover-based approach for drug-drug-drug interaction (3DI) screening. Cases were direct-acting oral anticoagulant (DOAC) users with either a major bleeding event during ongoing dispensings for potentially interacting, enzyme-inhibiting antihypertensive drugs (AHDs) (Study 1), or a thromboembolic event during ongoing dispensings for potentially interacting, enzyme-inducing antiseizure medications (ASMs) (Study 2). 3DI detection was based on screening for additional drug exposures that served as acute outcome triggers. To mitigate direct effects and confounding by concomitant drugs, self-controlled estimates were adjusted using negative cases (external "control" DOAC users with the same outcomes but co-dispensings for non-interacting AHDs or ASMs). Signal thresholds were set based on P-values and false discovery rate q-values to address multiple comparisons. Study 1: 285 drugs were examined among 3,306 episodes. Self-controlled assessments with q-value thresholds yielded 9 3DI signals (cases) and 40 DDI signals (negative cases). External adjustment generated 10 3DI signals from the P-value threshold and no signals from the q-value threshold. Study 2: 126 drugs were examined among 604 episodes. Assessments with P-value thresholds yielded 3 3DI and 26 DDI signals following self-control, as well as 4 3DI signals following adjustment. No 3DI signals met the q-value threshold. The presented self- and externally-controlled approach aimed to advance paradigms for real-world higher order drug interaction screening among high-susceptibility populations with pre-existent DDI risk.

Smartphone use in Neurology: a bibliometric analysis and visualization of things to come.

Background and objectives: Smartphones are a ubiquitous part of society with increasing use as a healthcare tool. We aimed to analyze the published literature on smartphone usage within the field of Neurology to define the scientific landscape and forecast future research initiatives. Methods: We performed a bibliometric review of smartphone uses in Neurology based on a search of two Web of Science databases from inception through September 16, 2022. This librarian-guided review was conducted using Bibliometrix for data assessment and visualization. Temporal trends in publications, citation counts, collaborations, and author affiliations were among key metrics evaluated. VOS viewer identified hot spots based on generating co-occurrences and bibliographic coupling mapping. Results: Our search found 3,920 publications. The U.S. produced the most topic-based publications, collaborating most frequently with U.K., Canada, and China-based authors. The most prolific institutions included Karolinska Institute, University of Sydney, and University of Pittsburgh. Bioelectromagnetics, Stroke, and Neurology were the most cited journals. Rapid growth in scientific production occurred in recent years, including during the COVID-19 pandemic. Hotspots and keyword co-occurrence included telehealth, machine learning, and self-management. Temporal trends reflect transitioning from a focus of initial publications regarding mobile phone safety to more recent application of smartphones as "smart" tools for single modality diagnosis, monitoring, management, and treatment of neurological diseases. Discussion: There has been rapid expansion of the published literature on smartphone uses in Neurology. Initial focus on smartphones and health risk has shifted to uses for neurological disease diagnosis, detection, and management, with relevance as a global interface for collaboration and clinical practice.

Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies.

Pharmacoepidemiology has an increasingly important role in informing and improving clinical practice, drug regulation, and health policy. Therefore, unrecognized biases in pharmacoepidemiologic studies can have major implications when study findings are translated to the real world. We propose a simple taxonomy for researchers to use as a starting point when thinking through some of the most pervasive biases in pharmacoepidemiology. We organize this discussion according to biases best assessed with respect to the study population (including confounding by indication, channeling bias, healthy user bias, and protopathic bias), the study design (including prevalent user bias and immortal time bias), and the data source (including misclassification bias and missing data/loss to follow up). This tutorial defines, provides a curated list of recommended references, and illustrates through relevant case examples these key biases to consider when planning, conducting, or evaluating pharmacoepidemiologic studies.

Early neurologic deterioration with symptomatic isolated internal carotid artery occlusion: a cohort study, systematic review, and meta-analysis.

Background: Acute endovascular revascularization for isolated internal carotid occlusion without tandem intracranial occlusion has been proposed to prevent early neurologic deterioration (END) and improve outcome, but has not been shown to be more effective than medical therapy. We aimed to evaluate prognosis with initial medical therapy alone, and also performed a systematic review to put these results in a broader context. Methods: We performed a retrospective cohort study of patients admitted over a 2-year period with acute stroke/TIA due to isolated internal carotid artery occlusion. Subjects with tandem intracranial occlusion or ASPECTS≤5 were excluded. The primary outcome was END within 48 hours (NIHSS increase ≥4 persisting for ≥24 hours). Secondary outcomes included discharge NIHSS and disposition. We also performed a systematic review and meta-analysis of published studies along with the data from our cohort. Results: Twenty-three patients met our inclusion criteria. Median age was 69 years, initial ASPECTS 10, and NIHSS score 3. END attributed to recurrent ischemia occurred in 5/23 patients (22%, 95%CI: 7-44%). At discharge, 78% had a favorable outcome with a median NIHSS of 2 (IQR 1-3). END appeared more frequent in those with higher baseline NIHSS. In our systematic review, 7 prior studies met our inclusion criteria. END occurred in 17% (95%CI:12-23%) of patients, 18% with medical therapy versus 13% with endovascular therapy, with substantial heterogeneity among studies. Conclusions: In patients with acute stroke or TIA due to isolated internal carotid occlusion, END is relatively common (occurring in about 1 out of 6 patients). Further research is needed to evaluate the roles of maximal medical management or acute endovascular thrombectomy in these patients.

Interfacility Transfers for Seizure-Related Emergencies in the United States.

BACKGROUND AND OBJECTIVES: Interfacility transfer protocols are important for seizure-related emergencies, the cause of approximately 1% of all emergency department (ED) visits in the U.S., but data on current practices are lacking. We assessed the prevalence, temporal trends, and patterns of interfacility transfers following seizure-related ED visits. METHODS: We performed a retrospective longitudinal cross-sectional analysis of ED dispositions for seizure-related emergencies among adult and pediatric populations using the Nationwide Emergency Department Sample (NEDS). We used joinpoint regression to analyze annual trends in ED visits and transfer rate from 2007-2018. Logistic regression models using data from 2016-2018 explored the patient- and hospital-level factors associated with transfer versus admission. Sampling weights were applied to account for the complex survey design of NEDS. RESULTS: Using nationally representative data from 2007-2018, there were 7,372,065 weighted ED visits for seizure-related emergencies, including 419,368 (5.6%) visits for a primary diagnosis of status epilepticus. We found that 2.3%-5.6% of all these seizure-related ED visits resulted in an interfacility transfer, and that the rate of transfer increased significantly over time. Among ED visits specifically for status epilepticus, interfacility transfers resulted from 19.8%-23.24% of visits, which also increased over time. Multivariable logistic regression of adult and pediatric visits for status epilepticus revealed transferring hospitals were more likely to be non-metropolitan (adjusted odds ratio (AOR) 2.2, 95% confidence interval (CI) 1.6-2.9), and less likely to have continuous electroencephalography (cEEG) capabilities (AOR 0.3, CI 0.3-0.4). Transferred patients were more likely to be children (AOR 1.5 CI 1.3-1.6 for those 1-4 years old; AOR 1.5 (1.3-1.7) for ages 5-14), have acute cerebrovascular disease (AOR 1.4, CI 1.1-1.8) and have received mechanical ventilation (AOR 1.5, CI 1.4-1.7). DISCUSSION: By 2018, approximately 1 in 19 seizure-related and 1 in 5 status epilepticus ED visits resulted in interfacility transfers. In order of strength of association, illness severity, ED seizure volume, comorbid meningitis and traumatic brain injury, non-rural location, cEEG capabilities, and pediatric age favored admission. Rural location, lack of cEEG capabilities, and comorbid stroke favored transfer. Thoughtful deployment of novel EEG technologies and tele-neurology tools may help optimize triage and prevent unnecessary ED transfers.

Population-based screening to detect benzodiazepine drug-drug-drug interaction signals associated with unintentional traumatic injury.

Drug interactions involving benzodiazepines and related drugs (BZDs) are increasingly recognized as a contributor to increased risk of unintentional traumatic injury. Yet, it remains unknown to what extent drug interaction triads (3DIs) may amplify BZDs' inherent injury risk. We identified BZD 3DI signals associated with increased injury rates by conducting high-throughput pharmacoepidemiologic screening of 2000-2019 Optum's health insurance data. Using self-controlled case series design, we included patients aged ≥ 16 years with an injury while using a BZD + co-dispensed medication (i.e., base pair). During base pair-exposed observation time, we identified other co-dispensed medications as candidate interacting precipitants. Within each patient, we compared injury rates during time exposed to the drug triad versus to the base pair only using conditional Poisson regression, adjusting for time-varying covariates. We calculated rate ratios (RRs) with 95% confidence intervals (CIs) and accounted for multiple estimation via semi-Bayes shrinkage. Among the 65,123 BZD triads examined, 79 (0.1%) were associated with increased injury rates and considered 3DI signals. Adjusted RRs for signals ranged from 3.01 (95% CI = 1.53-5.94) for clonazepam + atorvastatin with cefuroxime to 1.42 (95% CI = 1.00-2.02, p = 0.049) for alprazolam + hydrocodone with tizanidine. These signals may help researchers prioritize future etiologic studies to investigate higher-order BZD interactions.

Identifying Clinically Relevant Drug-Drug Interactions With Methadone and Buprenorphine: A Translational Approach to Signal Detection.

Methadone and buprenorphine have pharmacologic properties that are concerning for a high risk of drug-drug interactions (DDIs). We performed high-throughput screening for clinically relevant DDIs with methadone or buprenorphine by combining pharmacoepidemiologic and pharmacokinetic approaches. We conducted pharmacoepidemiologic screening via a series of self-controlled case series studies (SCCS) in Optum claims data from 2000 to 2019. We included persons 18 years or older who experienced an outcome of interest during target drug treatment. Exposures were all overlapping medications (i.e., the candidate precipitants) during target drug treatment. Outcomes were opioid overdose, non-overdose adverse effects, and cardiac arrest. We used conditional Poisson regression to calculate rate ratios, accounting for multiple comparisons with semi-Bayes shrinkage. We explored the impact of key study design choices in analyses that varied the exposure definitions of the target drugs and the candidate precipitant drugs. Pharmacokinetic screening was conducted by incorporating published data on CYP enzyme metabolism into an equation-based static model. In SCCS analysis, 1,432 events were included from 248,069 new users of methadone or buprenorphine. In the primary analysis, statistically significant DDIs included gabapentinoids with either methadone or buprenorphine; baclofen with methadone; and benzodiazepines with methadone. In sensitivity analysis, additional statistically significant DDIs included methocarbamol, quetiapine, or simvastatin with methadone. Pharmacokinetic screening identified two moderate-to-strong potential DDIs (clonidine and fluconazole with buprenorphine). The combination of clonidine and buprenorphine was also associated with a significantly increased risk of opioid overdose in pharmacoepidemiologic screening. These DDI signals may be the most important targets for future confirmation studies.

Opioid Drug-Drug-Drug Interactions and Unintentional Traumatic Injury: Screening to Detect Three-Way Drug Interaction Signals.

Growing evidence suggests that drug interactions may be responsible for much of the known association between opioid use and unintentional traumatic injury. While prior research has focused on pairwise drug interactions, the role of higher-order (i.e., drug-drug-drug) interactions (3DIs) has not been examined. We aimed to identify signals of opioid 3DIs with commonly co-dispensed medications leading to unintentional traumatic injury, using semi-automated high-throughput screening of US commercial health insurance data. We conducted bi-directional, self-controlled case series studies using 2000-2015 Optum Data Mart database. Rates of unintentional traumatic injury were examined in individuals dispensed opioid-precipitant base pairs during time exposed vs unexposed to a candidate interacting precipitant. Underlying cohorts consisted of 16-90-year-olds with new use of opioid-precipitant base pairs and ≥1 injury during observation periods. We used conditional Poisson regression to estimate rate ratios adjusted for time-varying confounders, and semi-Bayes shrinkage to address multiple estimation. For hydrocodone, tramadol, and oxycodone (the most commonly used opioids), we examined 16,024, 8185, and 9330 drug triplets, respectively. Among these, 75 (0.5%; hydrocodone), 57 (0.7%; tramadol), and 42 (0.5%; oxycodone) were significantly positively associated with unintentional traumatic injury (50 unique base precipitants, 34 unique candidate precipitants) and therefore deemed potential 3DI signals. The signals found in this study provide valuable foundations for future research into opioid 3DIs, generating hypotheses to motivate crucially needed etiologic investigations. Further, this study applies a novel approach for 3DI signal detection using pharmacoepidemiologic screening of health insurance data, which could have broad applicability across drug classes and databases.

Skeletal muscle relaxant drug-drug-drug interactions and unintentional traumatic injury: Screening to detect three-way drug interaction signals.

AIM: The aim of this study was to identify skeletal muscle relaxant (SMR) drug-drug-drug interaction (3DI) signals associated with increased rates of unintentional traumatic injury. METHODS: We conducted automated high-throughput pharmacoepidemiologic screening of 2000-2019 healthcare data for members of United States commercial and Medicare Advantage health plans. We performed a self-controlled case series study for each drug triad consisting of an SMR base-pair (i.e., concomitant use of an SMR with another medication), and a co-dispensed medication (i.e., candidate interacting precipitant) taken during ongoing use of the base-pair. We included patients aged ≥16 years with an injury occurring during base-pair-exposed observation time. We used conditional Poisson regression to calculate adjusted rate ratios (RRs) with 95% confidence intervals (CIs) for injury with each SMR base-pair + candidate interacting precipitant (i.e., triad) versus the SMR-containing base-pair alone. RESULTS: Among 58 478 triads, 29 were significantly positively associated with injury; confounder-adjusted RRs ranged from 1.39 (95% CI = 1.01-1.91) for tizanidine + omeprazole with gabapentin to 2.23 (95% CI = 1.02-4.87) for tizanidine + diclofenac with alprazolam. Most identified 3DI signals are new and have not been formally investigated. CONCLUSION: We identified 29 SMR 3DI signals associated with increased rates of injury. Future aetiologic studies should confirm or refute these SMR 3DI signals.

Population-based signals of benzodiazepine drug interactions associated with unintentional traumatic injury.

Benzodiazepine receptor agonists and related medications, such as Z-drugs and dual orexin receptor antagonists (BZDs), have been associated with unintentional traumatic injury due to their central nervous system (CNS)-depressant effects. Drug-drug interactions (DDIs) may contribute to the known relationship between BZD use and unintentional traumatic injury, yet evidence is still lacking. We conducted high-throughput pharmacoepidemiologic screening using the self-controlled case series design in a large US commercial health insurance database to identify potentially clinically relevant DDI signals among new users of BZDs. We used conditional Poisson regression to estimate rate ratios (RRs) between each co-exposure (vs. not) and unintentional traumatic injury (primary outcome), typical hip fracture (secondary outcome), and motor vehicle crash (secondary outcome). We identified 48 potential DDI signals (1.1%, involving 39 unique co-dispensed drugs), i.e., with statistically significant elevated adjusted RRs for injury. Signals were strongest for DDI pairs involving zolpidem, lorazepam, temazepam, alprazolam, eszopiclone, triazolam, and clonazepam. We also identified four potential DDI signals for typical hip fracture, but none for motor vehicle crash. Many signals have biologically plausible explanations through additive or synergistic pharmacodynamic effects of co-dispensed antidepressants, opioids, or muscle relaxants on CNS depression, impaired psychomotor and cognitive function, and/or somnolence. While other signals that lack an obvious mechanism may represent true associations that place patients at risk of injury, it is also prudent to consider the roles of chance, reverse causation, and/or confounding by indication, which merit further exploration. Given the high-throughput nature of our investigation, findings should be interpreted as hypothesis generating.

Signals of Muscle Relaxant Drug Interactions Associated with Unintentional Traumatic Injury: A Population-Based Screening Study.

BACKGROUND: Use of muscle relaxants is rapidly increasing in the USA. Little is understood about the role of drug interactions in the known association between muscle relaxants and unintentional traumatic injury, a clinically important endpoint causing substantial morbidity, disability, and death. OBJECTIVE: We examined potential associations between concomitant drugs (i.e., precipitants) taken with muscle relaxants (affected drugs, i.e., objects) and hospital presentation for unintentional traumatic injury. METHODS: In a series of self-controlled case series studies, we screened to identify drug interaction signals for muscle relaxant + precipitant pairs and unintentional traumatic injury. We used Optum's de-identified Clinformatics® Data Mart Database, 2000-2019. We included new users of a muscle relaxant, aged 16-90 years, who were dispensed at least one precipitant drug and experienced an unintentional traumatic injury during the observation period. We classified each observation day as precipitant exposed or precipitant unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to estimate rate ratios adjusting for time-varying confounders and then accounted for multiple estimation via semi-Bayes shrinkage. RESULTS: We identified 74,657 people who initiated muscle relaxants and experienced an unintentional traumatic injury, in whom we studied concomitant use of 2543 muscle relaxant + precipitant pairs. After adjusting for time-varying confounders, 16 (0.6%) pairs were statistically significantly and positively associated with injury, and therefore deemed signals of a potential drug interaction. Among signals, semi-Bayes shrunk, confounder-adjusted rate ratios ranged from 1.29 (95% confidence interval 1.04-1.62) for baclofen + sertraline to 2.28 (95% confidence interval 1.14-4.55) for methocarbamol + lamotrigine. CONCLUSIONS: Using real-world data, we identified several new signals of potential muscle relaxant drug interactions associated with unintentional traumatic injury. Only one among 16 signals is currently reported in a major drug interaction knowledge base. Future studies should seek to confirm or refute these signals.

Statins for the Prevention of Post-Stroke Seizure and Epilepsy Development: A Systematic Review and Meta-Analysis.

OBJECTIVES: Cerebrovascular disease is the leading cause of seizures and incident epilepsy of known etiology in older adults. Statins have increasingly garnered attention as a potential preventive strategy due to their pleiotropic effects beyond lipid-lowering, which may include neuroprotective and anti-epileptogenic properties. We aim to assess the evidence on statin use for prevention of post-stroke early-onset seizures and post-stroke epilepsy. MATERIALS AND METHODS: We conducted a systematic review and meta-analysis in accordance with PRISMA guidelines, which was prospectively registered with PROSPERO (CRD42019144916). PubMed and Embase were searched from database inception to 05/2020 for English-language, full-text studies examining the association between statin use in adults and development of early-onset seizures (≤7 days post-stroke) or post-stroke epilepsy. Pooled analyses were based on random-effects models using the inverse-variance method. RESULTS: Of 182 citations identified, 175 were excluded due to duplication or ineligibility. The 7 eligible publications were all cohort studies from East Asia or South America, with a total of 53,579 patients. Pre-stroke statin use was not associated with post-stroke epilepsy (3 studies pooled: OR 1.14, CI 0.91-1.42). However, post-stroke statin use was associated with lower risk of both early-onset seizures (3 studies pooled: OR 0.36, CI 0.25-0.53), and post-stroke epilepsy (6 studies pooled: OR 0.64, CI 0.46-0.88). CONCLUSIONS: Review of 7 cohort studies suggested post-stroke, but not pre-stroke, statin use may be associated with reduced risk of early-onset seizures and post-stroke epilepsy. Further research is warranted to validate these findings in broader populations and better parse the temporal components of the associations.

Use of prescription drug samples in the US and implications for pharmacoepidemiologic research: a systematic search of the literature.

INTRODUCTION: Free drug samples are not captured in the pharmacy claims databases used in many pharmacoepidemiologic studies, which could lead to misclassification of drug exposure status and thus bias study results. AREAS COVERED: We systematically searched the literature in PubMed/MEDLINE, Embase, and Scopus from database inception to August 2020 for studies assessing the magnitude of exposure misclassification in pharmacy claims data associated with uncaptured drug sample utilization. Our review identified five US-based studies with substantially different characteristics, contexts, methods, and results. Taken together, these studies suggest that the risk of sample-related bias may be higher for (1) studies of newly approved, patented brand-only drugs in specific classes and contexts; (2) studies of populations where sample use is common and the unexposed cohort is small; and (3) studies where the outcomes of interest are expected to be early-onset or acute, with non-constant hazards. EXPERT OPINION: In light of declining overall trends in sample use, future research on sample-related exposure misclassification should focus on delineating bias across those modern contexts where sample use remains high and optimizing bias quantification methods to create a more standardized approach. Additionally, further assessment is warranted for other sources of misclassified exposure status in claims-based pharmacoepidemiology research.

Population-Based Signals of Antidepressant Drug Interactions Associated With Unintentional Traumatic Injury.

Antidepressants are very widely used and associated with traumatic injury, yet little is known about their potential for harmful drug interactions. We aimed to identify potential drug interaction signals by assessing concomitant medications (precipitant drugs) taken with individual antidepressants (object drugs) that were associated with unintentional traumatic injury. We conducted pharmacoepidemiologic screening of 2000-2015 Optum Clinformatics data, identifying drug interaction signals by performing self-controlled case series studies for antidepressant + precipitant pairs and injury. We included persons aged 16-90 years codispensed an antidepressant and ≥ 1 precipitant drug(s), with an injury during antidepressant therapy. We classified antidepressant person-days as either precipitant-exposed or precipitant-unexposed. The outcome was an emergency department or inpatient discharge diagnosis for unintentional traumatic injury. We used conditional Poisson regression to calculate confounder adjusted rate ratios (RRs) and accounted for multiple estimation via semi-Bayes shrinkage. We identified 330,884 new users of antidepressants who experienced an injury. Among such persons, we studied concomitant use of 7,953 antidepressant + precipitant pairs. Two hundred fifty-six (3.2%) pairs were positively associated with injury and deemed potential drug interaction signals; 22 of these signals had adjusted RRs > 2.00. Adjusted RRs ranged from 1.06 (95% confidence interval: 1.00-1.12, P = 0.04) for citalopram + gabapentin to 3.06 (1.42-6.60) for nefazodone + levonorgestrel. Sixty-five (25.4%) signals are currently reported in a seminal drug interaction knowledgebase. We identified numerous new population-based signals of antidepressant drug interactions associated with unintentional traumatic injury. Future studies, intended to test hypotheses, should confirm or refute these potential interactions.

Video quality using outpatient smartphone videos in epilepsy: Results from the OSmartViE study.

BACKGROUND AND PURPOSE: The aim of this study was to evaluate the quality of smartphone videos (SVs) of neurologic events in adult epilepsy outpatients. The use of home video recording in patients with neurological disease states is increasing. Experts interpretation of outpatient smartphone videos of seizures and neurological events has demonstrated similar diagnostic accuracy to inpatient video-electroencephalography (EEG) monitoring. METHODS: A prospective, multicenter cohort study was conducted to evaluate SV quality in patients with paroxysmal neurologic events from August 15, 2015 through August 31, 2018. Epileptic seizures (ESs), psychogenic nonepileptic attacks (PNEAs), and physiologic nonepileptic events (PhysNEEs) were confirmed by video-EEG monitoring. Experts and senior neurology residents blindly viewed cloud-based SVs without clinical information. Quality ratings with regard to technical and operator-driven metrics were provided in responses to a survey. RESULTS: Forty-four patients (31 women, age 45.1 years [r = 20-82]) were included and 530 SVs were viewed by a mean of seven experts and six residents; one video per patient was reviewed for a mean of 133.8 s (r = 9-543). In all, 30 patients had PNEAs, 11 had ESs, and three had PhysNEEs. Quality was suitable in 70.8% of SVs (375/530 total views), with 36/44 (81.8%) patient SVs rated as adequate by the majority of reviewers. Accuracy improved with the presence of convulsive features from 72.4% to 98.2% in ESs and from 71.1% to 95.7% in PNEAs. An accurate diagnosis was given by all reviewers (100%) in 11/44 SVs (all PNEAs). Audio was rated as good by 86.2% of reviewers for these SVs compared with 75.4% for the remaining SVs (p = 0.01). Lighting was better in SVs associated with high accuracy (p = 0.06), but clarity was not (p = 0.59). Poor video quality yielded unknown diagnoses in 24.2% of the SVs reviewed. Features hindering diagnosis were limited interactivity, restricted field of view and short video duration. CONCLUSIONS: Smartphone video quality is adequate for clinical interpretation in the majority of patients with paroxysmal neurologic events. Quality can be optimized by encouraging interactivity with the patient, adequate duration of the SV, and enlarged field of view during videography. Quality limitations were primarily operational though accuracy remained for SV review of ESs and PNEAs.

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.

Inconsistent reporting of drug-drug interactions for hormonal contraception and antiepileptic drugs - Implications for reproductive health for women with epilepsy.

Drug compendia are the source of safety prescribing information. We assessed the reporting concordance of drug-drug interactions between hormonal contraception and antiepileptic drugs (AEDs) among eight leading international drug compendia. Antiepileptic drugs reported to interact with ≥1 form of hormonal contraception were reviewed. Scaled concordance was quantified using linearly weighted percent agreement (wPA). Differences in interaction severity rankings between hormonal contraception forms were evaluated using the Wilcoxon signed-rank test. There was high agreement among compendia for interactions of combined hormonal contraception interactions with AEDs (wPA = 0.82-0.84), especially potent enzyme-inducing AEDs (wPA = 0.89). However, concordance was reduced for AED interactions with progestin-only contraception (wPA = 0.69-0.81). Extreme interaction reporting discrepancies were found for less potent enzyme-inducing AEDs. The greatest variability in interaction reporting was observed for injectable and intrauterine contraception (wPA = 0.69 and 0.70, respectively), which are the only hormonal contraception options currently classified as not interacting with enzyme-inducing AEDs. Drug-drug interaction reporting variability can have major clinical implications and highlights critical knowledge gaps in the care of women with epilepsy of childbearing age. Further research on AED-contraceptive interactions is needed to standardize compendia reporting and enhance evidence-based clinical guidelines for women with epilepsy.