Acute symptomatic seizures in patients with recurrent ischemic stroke: A multicentric study.

OBJECTIVE: Epileptic seizures occur frequently after stroke due to changes in brain function and structure, and up to around 10% of stroke patients experience stroke recurrence in the first year. We aimed to establish the risk of acute symptomatic seizures in patients with recurrent stroke. METHODS: Retrospective cohort study including consecutive admissions to a Stroke Unit due to acute ischemic stroke, during a 5-year period. Additional inclusion of patients admitted to two centers in different countries to corroborate findings (confirmatory cohort). We aimed to compare acute symptomatic seizure incidence in patients with and without previous stroke. Patients with history of epilepsy were excluded. Logistic regression modeling was performed to identify predictors in middle cerebral artery (MCA) stroke. RESULTS: We included 1473 patients (1085 with MCA stroke), of which 117 had a recurrent ischemic stroke (84 with MCA stroke). Patients with recurrent stroke had a seizure risk during hospital stay similar to that of patients with a first-ever stroke (5.1% vs. 4.5%, OR 1.15, 95% CI .48-2.71, p = .75). Risk of acute symptomatic seizures was also similar (5.0% vs. 4.1, OR 1.22, 95% CI .29-5.27, p = .78). Older age, female sex, and hemorrhagic transformation were predictors of seizures in patients with a first MCA ischemic stroke, but not in recurrent stroke patients. Electrographic characteristics were similar between the two groups in patients who had an electroencephalogram (46 with first stroke, 5 with recurrent stroke). The low rate of seizures (1.5%) in the confirmatory cohort (n = 198) precluded full comparison with the initial cohort. Nevertheless, the rate of seizures was not higher in stroke recurrence. SIGNIFICANCE: History of previous stroke was not associated with an increased risk of acute symptomatic seizures during hospital stay. Larger, prospective studies, with prospective electrophysiological evaluation, are needed to explore the impact of stroke recurrence on seizure risk.

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.

Implications for driving based on the risk of seizures after ischaemic stroke.

BACKGROUND: In addition to other stroke-related deficits, the risk of seizures may impact driving ability after stroke. METHODS: We analysed data from a multicentre international cohort, including 4452 adults with acute ischaemic stroke and no prior seizures. We calculated the Chance of Occurrence of Seizure in the next Year (COSY) according to the SeLECT2.0 prognostic model. We considered COSY<20% safe for private and <2% for professional driving, aligning with commonly used cut-offs. RESULTS: Seizure risks in the next year were mainly influenced by the baseline risk-stratified according to the SeLECT2.0 score and, to a lesser extent, by the poststroke seizure-free interval (SFI). Those without acute symptomatic seizures (SeLECT2.0 0-6 points) had low COSY (0.7%-11%) immediately after stroke, not requiring an SFI. In stroke survivors with acute symptomatic seizures (SeLECT2.0 3-13 points), COSY after a 3-month SFI ranged from 2% to 92%, showing substantial interindividual variability. Stroke survivors with acute symptomatic status epilepticus (SeLECT2.0 7-13 points) had the highest risk (14%-92%). CONCLUSIONS: Personalised prognostic models, such as SeLECT2.0, may offer better guidance for poststroke driving decisions than generic SFIs. Our findings provide practical tools, including a smartphone-based or web-based application, to assess seizure risks and determine appropriate SFIs for safe driving.

Is it Mandatory to do a 24 hour ABPM in all Patients with Moderate to Severe Obstructive Sleep Apnoea?

Background Obstructive sleep apnoea (OSA) has been described as a risk factor for arterial hypertension (HT). One of the proposed mechanisms linking these conditions is non dipping (ND) pattern in nocturnal blood pressure, however evidence is variable and based on specific populations with underlying conditions. Data for OSA and ND in subjects residing at high altitude are currently unavailable. Objective Identify the prevalence and association of moderate to severe OSA with HT and ND pattern in hypertensive and non-hypertensive otherwise healthy middle-aged individuals in residing at high altitude (Bogotá:2640 mt) Methods Adult individuals with diagnosis of moderate to severe OSA underwent 24 hour- ambulatory blood pressure monitoring (ABPM) between 2015 and 2017. Univariable and multivariable logistic regression analysis were performed to identify predictors of HT and ND pattern. Results Ninety-three (93) individuals (male 62.4% and median age 55) were included in the final analysis. Overall, 30.1% showed a ND pattern in ABPM and 14.9% had diurnal and nocturnal hypertension. Severe OSA (higher apnea-hiponea index [AHI]) was associated with HT (p = 0.006), but not with ND patterns (p = 0.54) in multivariable regression. Smoking status and lowest oxygen saturation during respiratory events where independently associated with ND pattern (p = 0.04), whereas age (p = 0.001) was associated with HT. Conclusions In our sample, one in three individuals with moderate to severe OSA have non dipping patterns suggesting lack of straight association between OSA and ND. Older individuals who have higher AHI are more likely to have HT, and those who smoke have a higher risk of ND. These findings add aditional information to the multiple mechanisms involved in the relationship between OSA and ND pattern, and questions the routine use of 24-hour ABPM, particullary in our region, with limited resources and healthcare acces. However, further work with more robust methodology is needed to draw conclusions.

Association of Mortality and Risk of Epilepsy With Type of Acute Symptomatic Seizure After Ischemic Stroke and an Updated Prognostic Model.

Importance: Acute symptomatic seizures occurring within 7 days after ischemic stroke may be associated with an increased mortality and risk of epilepsy. It is unknown whether the type of acute symptomatic seizure influences this risk. Objective: To compare mortality and risk of epilepsy following different types of acute symptomatic seizures. Design, Setting, and Participants: This cohort study analyzed data acquired from 2002 to 2019 from 9 tertiary referral centers. The derivation cohort included adults from 7 cohorts and 2 case-control studies with neuroimaging-confirmed ischemic stroke and without a history of seizures. Replication in 3 separate cohorts included adults with acute symptomatic status epilepticus after neuroimaging-confirmed ischemic stroke. The final data analysis was performed in July 2022. Exposures: Type of acute symptomatic seizure. Main Outcomes and Measures: All-cause mortality and epilepsy (at least 1 unprovoked seizure presenting >7 days after stroke). Results: A total of 4552 adults were included in the derivation cohort (2547 male participants [56%]; 2005 female [44%]; median age, 73 years [IQR, 62-81]). Acute symptomatic seizures occurred in 226 individuals (5%), of whom 8 (0.2%) presented with status epilepticus. In patients with acute symptomatic status epilepticus, 10-year mortality was 79% compared with 30% in those with short acute symptomatic seizures and 11% in those without seizures. The 10-year risk of epilepsy in stroke survivors with acute symptomatic status epilepticus was 81%, compared with 40% in survivors with short acute symptomatic seizures and 13% in survivors without seizures. In a replication cohort of 39 individuals with acute symptomatic status epilepticus after ischemic stroke (24 female; median age, 78 years), the 10-year risk of mortality and epilepsy was 76% and 88%, respectively. We updated a previously described prognostic model (SeLECT 2.0) with the type of acute symptomatic seizures as a covariate. SeLECT 2.0 successfully captured cases at high risk of poststroke epilepsy. Conclusions and Relevance: In this study, individuals with stroke and acute symptomatic seizures presenting as status epilepticus had a higher mortality and risk of epilepsy compared with those with short acute symptomatic seizures or no seizures. The SeLECT 2.0 prognostic model adequately reflected the risk of epilepsy in high-risk cases and may inform decisions on the continuation of antiseizure medication treatment and the methods and frequency of follow-up.

Antiseizure medication withdrawal risk estimation and recommendations: A survey of American Academy of Neurology and EpiCARE members.

OBJECTIVE: Choosing candidates for antiseizure medication (ASM) withdrawal in well-controlled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation ("clinician predictions") vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation. METHODS: We asked US and European neurologists to predict 2-year seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models. RESULTS: Three-hundred and forty-six neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%-100% for a 2-year seizure-free adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%-74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6-month seizure-free mean clinician 56%, 95% CI 52%-60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%-28%) compared with calculators (14%, 95% 13%-14%). Viewing calculated predictions slightly reduced willingness to withdraw (-0.8/10 change, 95% CI -1.0 to -0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%). SIGNIFICANCE: Clinicians overestimated the influence of abnormal EEGs particularly for low-risk patients and overestimated risk and the influence of seizure-free duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or time-based seizure-free thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities.

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.

Measurement of Midregional Pro-Atrial Natriuretic Peptide to Discover Atrial Fibrillation in Patients With Ischemic Stroke.

BACKGROUND: Midregional pro-atrial natriuretic peptide (MR-proANP) is a promising biomarker to differentiate the underlying etiology of acute ischemic stroke (AIS). OBJECTIVES: This study aimed to determine the role of MR-proANP for classification as cardioembolic (CE) stroke, identification of newly diagnosed atrial fibrillation (NDAF), and risk assessment for major adverse cardiovascular events (MACE). METHODS: This study measured MR-proANP prospectively collected within 24 hours after symptom-onset in patients with AIS from the multicenter BIOSIGNAL (Biomarker Signature of Stroke Aetiology) cohort study. Primary outcomes were CE stroke etiology and NDAF after prolonged cardiac monitoring, as well as a composite outcome of MACE (recurrent cerebrovascular events, myocardial infarction, or cardiovascular death) within 1 year. Logistic/Poisson and subproportional hazard regression were applied to evaluate the association between MR-proANP levels and outcomes. Additionally, a model for prediction of NDAF was derived and validated as a decision tool for immediate clinical application. RESULTS: Between October 1, 2014, and October 31, 2017, this study recruited 1,759 patients. Log10MR-proANP levels were associated with CE stroke (OR: 7.96; 95% CI: 4.82-13.14; risk ratio: 3.12; 95% CI: 2.23-4.37), as well as NDAF (OR: 35.3; 95% CI: 17.58-71.03; risk ratio: 11.47; 95% CI: 6.74-19.53), and MACE (subdistributional HR: 2.02; 95% CI: 1.32-3.08) during follow-up. The model to predict NDAF including only age and MR-proANP levels had a good discriminatory capacity with an area under the curve of 0.81 (95% CI: 0.76-0.86), was well calibrated (calibration in the large: -0.086; calibration slope 1.053), and yielded higher net-benefit compared with validated scores to predict NDAF (AS5F score, CHA2DS2-VASc [Congestive Heart Failure, Hypertension, Age ≥65 or ≥75, Diabetes, Prior Cardioembolic Event, (female) Sex, or Vascular Disease] score). CONCLUSIONS: MR-proANP is a valid biomarker to determine risk of NDAF and MACE in patients with AIS and can be used as a decision tool to identify patients for prolonged cardiac monitoring. (Biomarker Signature of Stroke Aetiology Study: The BIOSIGNAL study [BIOSIGNAL]; NCT02274727).

Seizures after Ischemic Stroke: A Matched Multicenter Study.

OBJECTIVE: The purpose of this study was to identify risk factors for acute symptomatic seizures and post-stroke epilepsy after acute ischemic stroke and evaluate the effects of reperfusion treatment. METHODS: We assessed the risk factors for post-stroke seizures using logistic or Cox regression in a multicenter study, including adults from 8 European referral centers with neuroimaging-confirmed ischemic stroke. We compared the risk of post-stroke seizures between participants with or without reperfusion treatment following propensity score matching to reduce confounding due to treatment selection. RESULTS: In the overall cohort of 4,229 participants (mean age 71 years, 57% men), a higher risk of acute symptomatic seizures was observed in those with more severe strokes, infarcts located in the posterior cerebral artery territory, and strokes caused by large-artery atherosclerosis. Strokes caused by small-vessel occlusion carried a small risk of acute symptomatic seizures. 6% developed post-stroke epilepsy. Risk factors for post-stroke epilepsy were acute symptomatic seizures, more severe strokes, infarcts involving the cerebral cortex, and strokes caused by large-artery atherosclerosis. Electroencephalography findings within 7 days of stroke onset were not independently associated with the risk of post-stroke epilepsy. There was no association between reperfusion treatments in general or only intravenous thrombolysis or mechanical thrombectomy with the time to post-stroke epilepsy or the risk of acute symptomatic seizures. INTERPRETATION: Post-stroke seizures are related to stroke severity, etiology, and location, whereas an early electroencephalogram was not predictive of epilepsy. We did not find an association of reperfusion treatment with risks of acute symptomatic seizures or post-stroke epilepsy. ANN NEUROL 2021;90:808-820.

The Evolution of Neurofilament Light Chain in Multiple Sclerosis.

Multiple sclerosis (MS) is an autoimmune, inflammatory neurodegenerative disease of the central nervous system characterized by demyelination and axonal damage. Diagnosis and prognosis are mainly assessed through clinical examination and neuroimaging. However, more sensitive biomarkers are needed to measure disease activity and guide treatment decisions in MS. Prompt and individualized management can reduce inflammatory activity and delay disease progression. Neurofilament Light chain (NfL), a neuron-specific cytoskeletal protein that is released into the extracellular fluid following axonal injury, has been identified as a biomarker of disease activity in MS. Measurement of NfL levels can capture the extent of neuroaxonal damage, especially in early stages of the disease. A growing body of evidence has shown that NfL in cerebrospinal fluid (CSF) and serum can be used as reliable indicators of prognosis and treatment response. More recently, NfL has been shown to facilitate individualized treatment decisions for individuals with MS. In this review, we discuss the characteristics that make NfL a highly informative biomarker and depict the available technologies used for its measurement. We further discuss the growing role of serum and CSF NfL in MS research and clinical settings. Finally, we address some of the current topics of debate regarding the use of NfL in clinical practice and examine the possible directions that this biomarker may take in the future.

Seizures and Epilepsy After Stroke: Epidemiology, Biomarkers and Management.

Stroke is the leading cause of seizures and epilepsy in older adults. Patients who have larger and more severe strokes involving the cortex, are younger, and have acute symptomatic seizures and intracerebral haemorrhage are at highest risk of developing post-stroke epilepsy. Prognostic models, including the SeLECT and CAVE scores, help gauge the risk of epileptogenesis. Early electroencephalogram and blood-based biomarkers can provide information additional to the clinical risk factors of post-stroke epilepsy. The management of acute versus remote symptomatic seizures after stroke is markedly different. The choice of an ideal antiseizure medication should not only rely on efficacy but also consider adverse effects, altered pharmacodynamics in older adults, and the influence on the underlying vascular co-morbidity. Drug-drug interactions, particularly those between antiseizure medications and anticoagulants or antiplatelets, also influence treatment decisions. In this review, we describe the epidemiology, risk factors, biomarkers, and management of seizures after an ischaemic or haemorrhagic stroke. We discuss the special considerations required for the treatment of post-stroke epilepsy due to the age, co-morbidities, co-medication, and vulnerability of stroke survivors.