Hospital variation of outcomes in status epilepticus.

OBJECTIVE: Understanding factors driving variation in status epilepticus outcomes would be critical to improve care. We evaluated the degree to which patient and hospital characteristics explained hospital-to-hospital variability in intubation and postacute outcomes. METHODS: This was a retrospective cohort study of Medicare beneficiaries admitted with status epilepticus between 2009 and 2019. Outcomes included intubation, discharge to a facility, and 30- and 90-day readmissions and mortality. Multilevel models calculated percent variation in each outcome due to hospital-to-hospital differences. RESULTS: We included 29 150 beneficiaries. The median age was 68 years (interquartile range [IQR] = 57-78), and 18 084 (62%) were eligible for Medicare due to disability. The median (IQR) percentages of each outcome across hospitals were: 30-day mortality 25% (0%-38%), any 30-day readmission 14% (0%-25%), 30-day status epilepticus readmission 0% (0%-3%), 30-day facility stay 40% (25%-53%), and intubation 46% (20%-61%). However, after accounting for many hospitals with small sample size, hospital-to-hospital differences accounted for 2%-6% of variation in all unadjusted outcomes, and approximately 1%-5% (maximally 8% for 30-day readmission for status epilepticus) after adjusting for patient, hospitalization, and/or hospital characteristics. Although many characteristics significantly predicted outcomes, the largest effect size was cardiac arrest predicting death (odds ratio = 10.1, 95% confidence interval = 8.8-11.7), whereas hospital characteristics (e.g., staffing, accreditation, volume, setting, services) all had lesser effects. SIGNIFICANCE: Hospital-to-hospital variation explained little variation in studied outcomes. Rather, certain patient characteristics (e.g., cardiac arrest) had greater effects. Interventions to improve outcomes after status epilepticus may be better focused on individual or prehospital factors, rather than at the inpatient systems level.

Current state of the epilepsy drug and device pipeline.

The field of epilepsy has undergone substantial advances as we develop novel drugs and devices. Yet considerable challenges remain in developing broadly effective, well-tolerated treatments, but also precision treatments for rare epilepsies and seizure-monitoring devices. We summarize major recent and ongoing innovations in diagnostic and therapeutic products presented at the seventeenth Epilepsy Therapies & Diagnostics Development (ETDD) conference, which occurred May 31 to June 2, 2023, in Aventura, Florida. Therapeutics under development are targeting genetics, ion channels and other neurotransmitters, and many other potentially first-in-class interventions such as stem cells, glycogen metabolism, cholesterol, the gut microbiome, and novel modalities for delivering electrical neuromodulation.

Challenges and directions in epilepsy diagnostics and therapeutics: Proceedings of the 17th Epilepsy Therapies and Diagnostics Development conference.

Substantial efforts are underway toward optimizing the diagnosis, monitoring, and treatment of seizures and epilepsy. We describe preclinical programs in place for screening investigational therapeutic candidates in animal models, with particular attention to identifying and eliminating drugs that might paradoxically aggravate seizure burden. After preclinical development, we discuss challenges and solutions in the design and regulatory logistics of clinical trial execution, and efforts to develop disease biomarkers and interventions that may be not only seizure-suppressing, but also disease-modifying. As disease-modifying treatments are designed, there is clear recognition that, although seizures represent one critical therapeutic target, targeting nonseizure outcomes like cognitive development or functional outcomes requires changes to traditional designs. This reflects our increasing understanding that epilepsy is a disease with profound impact on quality of life for the patient and caregivers due to both seizures themselves and other nonseizure factors. This review examines selected key challenges and future directions in epilepsy diagnostics and therapeutics, from drug discovery to translational application.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults.

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication withdrawal and develop and validate predictive models. We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard ratio (aHR) 5.5, 95% confidence interval (CI) 2.7-11.1], history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8-0.9) and number of antiseizure medications at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models. We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.

Lamotrigine and exogenous estrogen among females with epilepsy: A retrospective analysis of administrative claims data.

OBJECTIVE: Exogenous estrogen reduces lamotrigine serum concentrations. Little is known about whether providers adjust lamotrigine doses for addition of exogenous estrogen among people with epilepsy, despite expert recommendations. We determined the incidence of dose increases in lamotrigine following incident prescription of estrogen among females with epilepsy (FWE) in claims data. METHODS: We used Optum's de-identified Clinformatics® Data Mart Database to create a cohort of U.S. FWE prescribed lamotrigine at a stable dose, with a subsequent prescription for estrogen from 2011 to 2021. We calculated cumulative incidence functions of dose increases in lamotrigine following prescription of exogenous estrogen. We performed a Cox proportional hazards model for multiple candidate predictors of a lamotrigine dose increase. RESULTS: The cohort included 643 FWE, with median age of 31 (interquartile ratio [IQR] 20-42). The cumulative incidence of any lamotrigine increase was 28% (95% confidence interval [CI] 25%-32%). The median number of days after the first estrogen fill until the first lamotrigine adjustment was 118 (IQR 48-188). In unadjusted Cox models, older age, use of estrogen in hormone replacement therapy as opposed to contraception, and annual household income of $50,000-$99,999 (compared with <$50,000) were significant negative predictors of a dose adjustment in lamotrigine with hazard ratios (HRs) of 0.82 (95% CI 0.72-0.92), 0.63 (95% CI 0.42-0.95), and 0.62 (95% CI 0.40-0.95). In the adjusted Cox model, age and income remained significant predictors with HRs of 0.79 (95% CI 0.66-0.94) and 0.59 (95% CI 0.36-0.95). CONCLUSION: Dose increase of lamotrigine following addition of exogenous estrogen is rare among U.S. FWE, with potential disparities based on age and income level. More guidance may be needed for providers on this topic.

Antiseizure medication treatment pathways for US Medicare beneficiaries with newly treated epilepsy.

OBJECTIVE: This study was undertaken to characterize antiseizure medication (ASM) treatment pathways in Medicare beneficiaries with newly treated epilepsy. METHODS: This was a retrospective cohort study using Medicare claims. Medicare is the United States' federal health insurance program for people aged 65 years and older plus younger people with disabilities or end-stage renal disease. We included beneficiaries with newly treated epilepsy (International Classification of Diseases codes for epilepsy/convulsions 2014-2017, no ASM in the previous 2 years). We displayed the sequence of ASM fills using sunburst plots overall, then stratified by mood disorder, age, and neurologist prescriber. We tabulated drug costs for each pathway. RESULTS: We included 21 458 beneficiaries. Levetiracetam comprised the greatest number of pill days (56%), followed by gabapentin (11%) and valproate (8%). There were 22 288 unique treatment pathways. The most common pathways were levetiracetam monotherapy (43%), gabapentin monotherapy (10%), and valproate monotherapy (5%). Gabapentin was the most common second- and third-line ASM. Whereas only 2% of pathways involved first-line lacosamide, those pathways accounted for 19% of cost. Gabapentin and valproate use was increased and levetiracetam use was decreased in beneficiaries with mood disorders compared to beneficiaries without mood disorders. Levetiracetam use was increased and gabapentin, valproate, lamotrigine, and topiramate use was decreased in beneficiaries aged >65 years compared with those aged 65 years or less. Lamotrigine, levetiracetam, and lacosamide use was increased and gabapentin use was decreased in beneficiaries whose initial prescriber was a neurologist compared to those whose prescriber was not a neurologist. SIGNIFICANCE: Levetiracetam monotherapy was the most common pathway, although substantial heterogeneity existed. Lacosamide accounted for a small percentage of ASMs but a disproportionately large share of cost. Neurologists were more likely to prescribe lamotrigine compared with nonneurologists, and lamotrigine was prescribed far less frequently than may be endorsed by guidelines. Future work may explore patient- and physician-driven factors underlying ASM choices.

Reappraisal of the Medical Research Council Antiepileptic Drug Withdrawal Study: Contamination-adjusted and dose-response re-analysis.

OBJECTIVE: The 1991 Medical Research Council (MRC) Study compared seizure relapse for seizure-free patients randomized to withdraw vs continue of antiseizure medications (ASMs). We re-analyzed this trial to account for crossover between arms using contamination-adjusted intention to treat (CA ITT) methods, to explore dose-response curves, and to validate predictions against external data. ITT assesses the effect of being randomized to withdraw, as-treated analysis assesses the confounded effect of withdrawing, but CA ITT assesses the unconfounded effect of actually withdrawing. METHODS: CA ITT involves two stages. First, we used randomized arm to predict whether patients withdrew their ASM (logistic) or total daily ASM dose (linear). Second, we used those values to predict seizure occurrence (logistic). RESULTS: The trial randomized 503 patients to withdraw and 501 patients to continue ASMs. We found that 316 of 376 patients (88%) who were randomized to withdraw decreased their dose at every pre-seizure visit, compared with 35 of 424 (8%) who were randomized to continue (p < .01). Adjusted odds ratios of a 2-year seizure for those who withdrew vs those who did not was 1.3 (95% confidence interval [CI] 0.9-1.9) in the as-treated analysis, 2.5 (95% CI 1.9-3.4) comparing those randomized to withdraw vs continue for ITT, and 3.1 (95% CI 2.1-4.5) for CA ITT. Probabilities (withdrawal vs continue) were 28% vs 24% (as-treated), 40% vs 22% (ITT), and 43% vs 21% (CA ITT). Differences between ITT and CA ITT were greater when varying the predictor (reaching zero ASMs) or outcome (1-year seizures). As-treated dose-response curves demonstrated little to no effects, but larger effects in CA ITT analysis. MRC data overpredicted risk in Lossius data, with moderate discrimination (areas under the curve ~0.70). SIGNIFICANCE: CA ITT results (the effect of actually withdrawing ASMs on seizures) were slightly greater than ITT effects (the effect of recommend withdrawing ASMs on seizures). How these findings affect clinical practice must be individualized.

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.

BACKGROUND: For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal. METHODS: This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions. RESULTS: Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44). CONCLUSIONS: Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

Polypharmacy composition and patient- and provider-related variation in patients with epilepsy.

OBJECTIVE: To describe polypharmacy composition, and the degree to which patients versus providers contribute to variation in medication fills, in people with epilepsy. METHODS: We performed a retrospective study of Medicare beneficiaries with epilepsy (antiseizure medication plus diagnostic codes) in 2014 (N = 78,048). We described total number of medications and prescribers, and specific medications. Multilevel models evaluated the percentage of variation in two outcomes (1. number of medications per patient-provider dyad, and 2. whether a medication was filled within thirty days of a visit) due to patient-to-patient differences versus provider-to-provider differences. RESULTS: Patients filled a median of 12 (interquartile range [IQR] 8-17) medications, from median of 5 (IQR 3-7) prescribers. Twenty-two percent filled an opioid, and 61% filled at least three central nervous system medications. Levetiracetam was the most common medication (40%), followed by hydrocodone/acetaminophen (27%). The strongest predictor of medications per patient was Charlson comorbidity index (7.5 [95% confidence interval (CI) 7.2-7.8] additional medications for index 8+ versus 0). Provider-to-provider variation explained 36% of variation in number of medications per patient, whereas patient-to-patient variation explained only 2% of variation. Provider-to-provider variation explained 57% of variation in whether a patient filled a medication within 30 days of a visit, whereas patient-to-patient variation explained only 30% of variation. CONCLUSION: Patients with epilepsy fill a large number of medications from a large number of providers, including high-risk medications. Variation in medication fills was substantially more related to provider-to-provider rather than patient-to-patient variation. The better understanding of drivers of high-prescribing practices may reduce avoidable medication-related harms.

Inpatient long-term video-electroencephalographic monitoring event capture audiovisual diagnostic quality.

OBJECTIVES: Long-term video-electroencephalographic monitoring (LTVEM) represents the gold-standard method to evaluate whether events represent electrographic seizures, but limited work has evaluated the quality of inpatient event capture. We evaluated the frequency of audiovisual factors impairing the ideal electroclinical correlation of seizure-like episodes during LTVEM. METHODS: We retrospectively reviewed consecutive inpatient LTVEM studies (11/2019-12/2019) from three academic epilepsy centers. We evaluated all pushbutton events for audiovisual characteristics such as whether the event was narrated, whether the patient was blocked on camera, and what diagnostic challenges impaired the electroencephalographer's ability to understand either the reason the event button was pushed or clinical semiology ("electroclinical correlation"). We determined the percent of events and studies with each outcome. RESULTS: There were 154 studies with 520 pushbutton events. The pushbutton was most commonly activated by patients (41%), followed by nurses (31%) or family (17%). Twenty-nine percent of events represented electrographic seizures, and 78% occurred in the Epilepsy Monitoring Unit. The reason for the push was not stated in 45% of events, and inadequate narration impaired electroclinical correlation in 19% of events. At least one relevant part of the patient's body was blocked during 12% of events, but this impaired electroclinical correlation in only 1% of events. There was at least one factor impairing electroclinical correlation in 21% of events, most commonly due to incomplete narration (N = 99), lights off (N = 15), or blankets covering the patient (N = 15). At least one factor impaired electroclinical correlation for any event in 36% of studies. CONCLUSION: Audiovisual factors impairing the electroencephalographer's ability to render an electroclinical correlation were common, particularly related to inadequate narration from bedside observers to explain the reason for pushing the button or event semiology. Future efforts to develop targeted countermeasures should address narration challenges and improve inpatient seizure monitoring quality metrics.

Antiseizure medication adherence trajectories in Medicare beneficiaries with newly treated epilepsy.

OBJECTIVE: This study was undertaken to characterize trajectories of antiseizure medication (ASM) adherence in adults with newly treated epilepsy and to determine predictors of trajectories. METHODS: This was a retrospective cohort study using Medicare. We included beneficiaries with newly treated epilepsy (one or more ASM and none in the preceding 2 years, plus International Classification of Diseases codes) in 2010-2013. We calculated the proportion of days covered (proportion of total days with any ASM pill supply) for 8 quarters or until death. Group-based trajectory models characterized and determined predictors of trajectories. RESULTS: We included 24 923 beneficiaries. Models identified four groups: early adherent (60%), early nonadherent (18%), late adherent (11%), and late nonadherent (11%). Numerous predictors were associated with being in the early nonadherent versus early adherent group: non-White race (e.g., Black, odds ratio [OR] = 1.7, 95% confidence interval [CI] = 1.5-1.8), region (e.g., South vs. Northeast: OR = 1.2, 95% CI = 1.1-1.4), and once daily initial medication (OR = 1.1, 95% CI = 1.0-1.3). Predictors associated with decreased odds of being in the early nonadherent group included older age (OR = .9 per decade, 95% CI = .9-.9), female sex (OR = .9, 95% CI = .8-1.0), full Medicaid eligibility (OR = .6, 95% CI = .4-.8), neurologist visit (OR = .6, 95% CI = .6-.7), and initial older generation ASM (OR = .6, 95% CI = .6-.7). SIGNIFICANCE: We identified four ASM adherence trajectories in individuals with newly treated epilepsy. Whereas risk factors for early nonadherence such as race or geographic region are nonmodifiable, our work highlighted a modifiable risk factor for early nonadherence: lacking a neurologist. These data may guide future interventions aimed at improving ASM adherence, in terms of both timing and target populations.

Cardiovascular disease risk, awareness, and treatment in people with epilepsy.

OBJECTIVE: To evaluate whether cardiovascular risk, risk awareness, and guideline concordant treatment differ in individuals with versus without epilepsy. METHODS: This was a retrospective cross-sectional study using the National Health and Nutrition Examination Survey. We included participants ≥18 years for 2013-2018. We classified participants as having epilepsy if reporting ≥1 medication treating seizures. We calculated 10-year atherosclerotic cardiovascular disease (ASCVD) risk using the revised pooled cohort equation. We compared unadjusted and adjusted risk for participants with versus without epilepsy. We then assessed hypertension and diabetes disease awareness and control, plus statin guideline-concordance. We assessed mediators for both ASCVD risk and cardiovascular disease awareness. RESULTS: Of 17,961 participants, 154 (0.9%) had epilepsy. Participants with epilepsy reported poorer diet (p = 0.03), fewer minutes of moderate-vigorous activity per day (p < 0.01), and increased frequency of cardiovascular conditions (e.g. coronary heart disease, myocardial infarction, stroke). There was no difference in control of individual examination and laboratory risk factors between groups (A1c, systolic blood pressure, diastolic blood pressure, high-density lipoprotein, low-density lipoprotein, total cholesterol). However, epilepsy was associated with 52% (95% confidence interval [CI]: 0-130%) increase in ASCVD risk, which became nonsignificant after adjusting for health behaviors. No single studied variable (income, Patient Health Questionnaire-9 (PHQ-9), diet, smoking) had a significant indirect effect. Participants with epilepsy reported increased hypertension awareness which was trivially but significantly mediated by having a routine place of healthcare (indirect effect: 1% absolute increase (95% CI: 0-1%), and they reported increased rates of hypertension treatment and guideline-concordant statin therapy. Participants with versus without epilepsy reported similar rates of blood pressure control and diabetes awareness, treatment, and control. CONCLUSIONS: Participants with epilepsy had increased ASCVD risk, despite similar or better awareness, treatment, and control of individual risk factors such as diabetes and hypertension. Our results suggest that epilepsy is associated with numerous health behaviors leading to cardiovascular disease, though the causal pathway is complex as these variables (income, depression, diet, exercise, smoking) generally served as confounders rather than mediators.

Disability in people with epilepsy: A nationally representative cross-sectional study.

OBJECTIVE: The objective of this study was to explore the prevalence and predictors of limitations causing disability in patients treated for seizures or epilepsy compared with patients without epilepsy. METHODS: This was a retrospective cross-sectional study using the National Health and Nutrition Examination Survey (NHANES). We included all participants ≥20 years old for 2013-2018. We classified patients as having epilepsy if they reported taking at least one prescription medication to treat seizures or epilepsy. Physical, mental, and social limitations were determined from interview questions. We report the prevalence of any limitation and total number of limitations for participants without vs. with epilepsy using serial negative binomial regressions and severity of individual limitations according to epilepsy status. RESULTS: We included 17,057 participants, of whom 148 (0.8%) had epilepsy. Overall, 80% (95% confidence interval [CI]: 73%-86%) with epilepsy vs. 38% (95% CI: 36%-39%) without epilepsy reported at least 1 limitation (p < 0.01). The mean number of limitations was 7.5 (95% CI: 6.2-8.8) for those with epilepsy vs. 2.4 (95% CI: 2.3-2.6) for those without epilepsy (p < 0.01). Epilepsy was associated with an incidence rate ratio (IRR) of 3.1 (95% CI: 2.6-3.7) in an unadjusted negative binomial regression. After adjusting for demographics and comorbidities, this association was no longer significant (IRR: 1.2, 95% CI: 0.9-1.7). Limitations cited by 40-50% of participants with epilepsy included stooping/kneeling/crouching, standing for long periods of time, and pushing/pulling objects. Limitation severity was consistently higher in patients with epilepsy. CONCLUSIONS: Patients with epilepsy had 3.1 times as many physical, mental, or social limitations compared with those without epilepsy, and disability severity was consistently higher. This effect was attenuated after considering baseline variables such as smoking and depression severity. Our work implies the importance of structured mental health screening and self-management programs targeting mood, weight, and lifestyle as potential leverage points towards alleviating epilepsy-related disability.

Polypharmacy in patients with epilepsy: A nationally representative cross-sectional study.

OBJECTIVE: The objective of the study was to characterize the prevalence of polypharmacy and central nervous system (CNS)-acting medications in patients with epilepsy, and particular types of medications. METHODS: This was a retrospective cross-sectional study using data from the nationally representative National Health and Nutrition Examination Survey (NHANES). We included patients who reported taking at least one prescription medication in order to treat seizures or epilepsy during NHANES survey years 2013-2016. We assessed the number and types of drugs and predictors of total number of medications using a negative binomial regression. We then assessed prevalence of polypharmacy (≥5 medications), CNS polypharmacy (≥3 CNS-acting medications) and additional CNS-acting medications, and drugs that lower the seizure threshold (i.e., bupropion and tramadol), and extrapolated prevalence to estimated affected US population. RESULTS: The NHANES contained 20,146 participants, of whom 135 reported taking ≥1 antiseizure medication (ASM) for seizures or epilepsy representing 2,399,520 US citizens using NHANES's sampling frame. Patients reported taking a mean 5.3 (95% confidence interval (CI): 4.3-6.3) prescription medications. Adjusting for race, sex, and uninsurance, both age and number of chronic conditions predicted increased number of medications (incident rate ratio (IRR) per decade: 1.16, 95% CI: 1.04-1.28; IRR per chronic condition: 1.19, 95% CI: 1.11-1.27). Polypharmacy was reported by 47% (95% CI: 38%-57%) of patients, CNS polypharmacy by 34% (23%-47%), benzodiazepine use by 21% (14%-30%), opioid use by 16% (11%-24%), benzodiazepine plus opioid use by 6% (3%-14%), and 6% (2%-15%) reported a drug that lowers the seizure threshold. Twelve percent (7%-20%) took an opioid with either a benzodiazepine or gabapentinoid. CONCLUSIONS: Polypharmacy is common in patients with epilepsy. Patients taking ASMs frequently reported also taking other CNS-acting medications (i.e., opioids, benzodiazepines, seizure threshold-lowering medications), and medication combinations with black box warnings. Central nervous system polypharmacy poses health risks. Future research is needed to explore drivers of polypharmacy and strategies to help mitigate potentially harmful prescription use in this high-risk population.

Impact of presenting rhythm on short- and long-term neurologic outcome in comatose survivors of cardiac arrest treated with therapeutic hypothermia.

OBJECTIVES: To compare short- and long-term neurologic outcomes in comatose survivors of out-of-hospital cardiac arrest treated with mild therapeutic hypothermia presenting with nonshockable versus shockable initial rhythms. DESIGN: Retrospective cohort study. SETTING: Emergency department and ICU of an academic hospital. PATIENTS: One hundred twenty-three consecutive post-out-of-hospital cardiac arrest adults (57 nonshockable rhythms, 66 shockable rhythms) treated with therapeutic hypothermia between 2006 and 2012. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data were collected from electronic health records. Neurologic outcomes were dichotomized by Cerebral Performance Category at discharge and 6- to 12-month follow-up and analyzed via multivariable logistic regressions. Groups were similar, except nonshockable rhythm patients were more likely to have a history of diabetes mellitus (p = 0.01), be dialysis dependent (p = 0.01), and not have bystander cardiopulmonary resuscitation (p = 0.05). At discharge, 3 of 57 patients (5%) with nonshockable rhythm versus 28 of 66 (42%) with shockable rhythm had a favorable outcome (unadjusted odds ratio, 0.08; 95% CI, 0.02-0.3; adjusted odds ratio, 0.1; 95% CI, 0.03-0.4). At follow-up, 4 of 55 patients (7%) versus 29 of 60 (48%) with nonshockable rhythm and shockable rhythm, respectively, had a favorable Cerebral Performance Category (odds ratio, 0.08; 95% CI, 0.03-0.3; adjusted odds ratio, 0.09; 95% CI, 0.09-0.3). Among those surviving hospitalization, favorable neurologic outcome was more likely at long-term follow-up than at hospital discharge for both groups (odds ratio, 2.5; 95% CI, 1.3-4.7; adjusted odds ratio, 2.9; 95% CI, 1.4-6.2). No significant interaction between changes in neurologic status over time and presenting rhythm was seen (p = 0.93). CONCLUSIONS: These data indicate an association between initial nonshockable rhythm and significantly worse short- and long-term outcomes in patients treated with mild therapeutic hypothermia. Among survivors, neurologic status significantly improved over time for all patients and shockable rhythm patients and tended to improve over time for the small number of nonshockable rhythm patients who survived beyond hospitalization. No significant interaction between changes in neurologic status over time and presenting rhythm was seen.

Risk factors for the development of deformity in patients with spinal infection.

OBJECT: Bacterial spinal infections are infrequent but may lead to significant morbidity and death. Apart from neurological complications, infections may also lead to bone destruction resulting in deformity of the spine. However, the incidence of spinal deformities and risk factors is not well characterized in the literature. METHODS: A retrospective cohort study was conducted using electronic medical records at a single institution. All patients were over 18 years of age and had a clinically and radiologically documented spinal infection that was treated surgically during the period 2006-2013. Infections were classified according to anatomical location including disc, bone, and/or epidural space. Deformities included kyphosis and/or subluxation. The authors analyzed risk factors for developing at least 1 deformity between the time of infection and operation using the Fisher exact test and chi-square test. Change in visual analog scale (VAS) scores preoperatively versus postoperatively was also analyzed using the paired t-test. RESULTS: The study included 48 patients. The most common types of spinal infections were osteomyelitis and discitis (31%); osteomyelitis, discitis, and spinal epidural abscess (SEA; 27%); SEA only (15%); and osteomyelitis only (13%). Overall, 21 (44%) of 48 patients developed a spinal deformity. Anatomical location of infection (bone and/or disc and/or epidural space) was significantly associated with development of deformity (p < 0.001). In particular, patients with SEA had lower odds of deformity compared with patients without SEA (odds ratio 0.2, 95% confidence interval 0.05-0.9; p < 0.001). No other factor was significantly associated with deformity. Pain measured by VAS score tended to improve by a mean of 1.7 ± 2.7 points (p < 0.001) when comparing preoperative to postoperative scores. CONCLUSIONS: In this cohort of patients, 44% developed at least 1 deformity, predominantly kyphosis. The only variable significantly associated with deformity was infection location. Patients with SEA alone demonstrated lower odds of developing a deformity compared with patients without SEA. Other analyzed variables, including age, body mass index, time from initial diagnosis to surgery, and comorbidities, were not found to be associated with development of deformity. Surgical intervention resulted in pain improvement.

Exit Strategy: Balancing the Risks and Rewards of Antiseizure Medication Withdrawal.

The majority of people with epilepsy achieves long-term seizure-freedom and may consider withdrawal of their anti-seizure medications (ASMs). Withdrawal of ASMs can yield substantial benefits but may be associated with potential risks. This review critically examines the existing literature on ASM withdrawal, emphasizing evidence-based recommendations, where available. Our focus encompasses deprescribing strategies for individuals who have attained seizure freedom through medical treatment, those who have undergone successful epilepsy surgery, and individuals initiated on ASMs following acute symptomatic seizures. We explore state-of-the-art prognostic models in these scenarios that could guide the decision-making process. The review underscores the importance of a collaborative shared-decision approach between patients, caregivers, and physicians. We describe the subjective and objective factors influencing these decisions and illustrate how trade-offs may be effectively managed in practice.

Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: A pooled analysis.

OBJECTIVE: Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients. METHODS: We pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions. RESULTS: We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs. SIGNIFICANCE: No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation. PLAIN LANGUAGE SUMMARY: Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.