Exploratory study of blood biomarkers in patients with post-stroke epilepsy.

INTRODUCTION: In addition to clinical factors, blood-based biomarkers can provide useful information on the risk of developing post-stroke epilepsy (PSE). Our aim was to identify serum biomarkers at stroke onset that could contribute to predicting patients at higher risk of PSE. PATIENTS AND METHODS: From a previous study in which 895 acute stroke patients were followed-up, 51 patients developed PSE. We selected 15 patients with PSE and 15 controls without epilepsy. In a biomarker discovery setting, 5 Olink panels of 96 proteins each, were used to determine protein levels. Biomarkers that were down-regulated and overexpressed in PSE patients, and those that showed the strongest interactions with other proteins were validated using an enzyme-linked immunosorbent assay in samples from 50 PSE patients and 50 controls. A ROC curve analysis was used to evaluate the predictive ability of significant biomarkers to develop PSE. RESULTS: Mean age of the PSE discovery cohort was 68.56 ± 15.1, 40% women and baseline NIHSS 12 [IQR 1-25]. Nine proteins were down-expressed: CASP-8, TNFSF-14, STAMBP, ENRAGE, EDA2R, SIRT2, TGF-alpha, OSM and CLEC1B. VEGFa, CD40 and CCL4 showed greatest interactions with the remaining proteins. In the validation analysis, TNFSF-14 was the single biomarker showing statistically significant downregulated levels in PSE patients (p = 0.006) and it showed a good predictive capability to develop PSE (AUC 0.733, 95% CI 0.601-0.865). DISCUSSION AND CONCLUSION: Protein expression in PSE patients differs from that of non-epileptic stroke patients, suggesting the involvement of several different proteins in post-stroke epileptogenesis. TNFSF-14 emerges as a potential biomarker for predicting PSE.

Predictive Model for Estimating the Risk of Epilepsy After Aneurysmal Subarachnoid Hemorrhage: The RISE Score.

BACKGROUND AND OBJECTIVES: The occurrence of seizures after aneurysmal subarachnoid hemorrhage (aSAH) is associated with a poorer functional and cognitive prognosis and less favorable quality of life. It would be of value to promptly identify patients at risk of epilepsy to optimize follow-up protocols and design preventive strategies. Our aim was to develop a predictive score to help stratify epilepsy risk in patients with aSAH. METHODS: This is a retrospective, longitudinal study of all adults with aSAH admitted to our center (2012-2021). We collected demographic data, clinical and radiologic variables, data on early-onset seizures (EOSs), and data on development of epilepsy. Exclusion criteria were previous structural brain lesion, epilepsy, and ≤7 days' follow-up. Multiple Cox regression was used to evaluate factors independently associated with unprovoked remote seizures (i.e., epilepsy). The best fitting regression model was used to develop a predictive score. Performance was evaluated in an external validation cohort of 308 patients using receiver-operating characteristic curve analysis. RESULTS: From an initial database of 743 patients, 419 met the inclusion criteria and were included in the analysis. The mean age was 60 ± 14 years, 269 patients (64%) were women, and 50 (11.9%) developed epilepsy within a median follow-up of 4.2 years. Premorbid modified Rankin Score (mRS) (hazard ratio [HR] 4.74 [1.8-12.4], p = 0.001), VASOGRADE score (HR 2.45 [1.4-4.2], p = 0.001), surgical treatment (HR 2.77 [1.6-4.9], p = 0.001), and presence of EOSs (HR 1.84 [1.0-3.4], p = 0.05) were independently associated with epilepsy. The proposed scale, designated RISE, scores 1 point for premorbid mRS ≥ 2 (R), VASOGRADE-Yellow (I, Ischemia), surgical intervention (S), and history of EOSs (E) and 2 points for VASOGRADE-Red. RISE stratifies patients into 3 groups: low (0-1), moderate (2-3), and high (4-5) risk (2.9%, 20.8%, and 75.7% developed epilepsy, respectively). On validation in a cohort from a different tertiary care center (N = 308), the new scale yielded a similar risk distribution and good predictive power for epilepsy within 5 years after aSAH (area under the curve [AUC] 0.82; 95% CI 0.74-0.90). DISCUSSION: The RISE scale is a robust predictor of post-SAH epilepsy with immediate clinical applicability. In addition to facilitating personalized diagnosis and treatment, RISE may be of value for exploring future antiepileptogenesis strategies.

Antiseizure medication withdrawal in adult patients with idiopathic generalized epilepsy: Performance of two seizure recurrence prediction models.

PURPOSE: Currently, there is a limited availability of tools to predict seizure recurrence after discontinuation of antiseizure medications (ASMs). This study aimed to establish the seizure recurrence rate following ASM cessation in adult patients with idiopathic generalized epilepsy (IGE) and to assess the predictive performance of the Lamberink and the Stevelink prediction models using real-world data. METHODS: Retrospective longitudinal study in IGE patients who underwent ASM withdrawal in a tertiary epilepsy clinic since June 2011, with the latest follow up in January 2024. The minimum follow-up period was 12 months. Clinical and demographic variables were collected, and the seizure recurrence prediction models proposed by Lamberink and Stevelink were applied and evaluated. RESULTS: Forty-seven patients (mean age 33.15 ± 8 [20-55] years; 72.35 % women) were included. During the follow-up period, seizures recurred in 25 patients (53.2 %). Median time to recurrence was 8 months [IQR 3-13.5 months], and 17 patients (68 %) relapsed within the first year. None of the relapsing patients developed drug-resistant epilepsy. The only significant risk factor associated with recurrence was a seizure-free period of less than 2 years before discontinuing medication (91.7 % vs 40 %, p =.005). The Stevelink prediction model at both 2 (p =.015) and 5 years (p =.020) achieved statistical significance, with an AUC of 0.72 (95 % CI 0.56-0.88), while the Lamberink model showed inadequate prognostic capability. CONCLUSION: In our real-world cohort, a seizure-free period of at least 2 years was the only factor significantly associated with epilepsy remission after ASM withdrawal. Larger studies are needed to accurately predict seizure recurrence in IGE patients.

Risk assessment of long-term epilepsy after de novo status epilepticus with clinical and electroencephalographic biomarkers: The AFTER score.

BACKGROUND: The risk of developing epilepsy after de novo status epilepticus (SE) is nonnegligible. The individualized management of patients with high risk of subsequent epilepsy could improve long-term quality of life and cognitive impairment. We aimed to ascertain potential biomarkers of subsequent epilepsy and to construct a scoring system possessing predictive value for the diagnosis of post-SE epilepsy during follow-up. METHODS: The study data were obtained from a prospective registry of all SE episodes occurring in patients over 16 years attended in our tertiary center from February 2011 to April 2022. Clinical data, electroencephalography findings, treatment, and long-term clinical data were prospectively recorded. We selected SE patients at risk of developing epilepsy (acute symptomatic and cryptogenic etiologies with no previous history of epilepsy) and analyzed the risk of developing subsequent epilepsy. RESULTS: We included 230 patients. Median age was 65 years ± 16.9 SD and 112/230 (48.7 %) were women. One-hundred ninety-eight patients (86.1 %) had an acute symptomatic SE, whereas 32 patients (13.9 %) presented with a cryptogenic SE. A total of 55 patients (23.9 %) developed an unprovoked remote seizure and were diagnosed with epilepsy. After adjusting for identifiable confounders in a multivariable Cox regression analysis cryptogenic etiology (HR 2.24 [1.13-4.46], p = 0.022), first-line treatment initiation ≥1 h (HR 2.12 [1.03-4.36], p = 0.041], RDA/LPD/GPD EEG patterns (HR 1.88 [1.07-3.32], p = 0.028), and super-refractoriness (HR 2.90 [1.40-5.99], p = 0.004) emerged as independent predictors of post-SE epilepsy. Based on these findings, we constructed the AFTER score (1 point for each item) with a robust capability to predict post-SE epilepsy at 5 years (AUC 74.3 %, 95 %CI 64.3-84.3 %, p < 0.001). CONCLUSIONS: The AFTER score is a robust predictor of the development of epilepsy after new onset SE using clinical and electroencephalographic biomarkers (such as etiology, time to first-line treatment initiation, EEG pattern and super-refractoriness). Prospective studies are warranted to validate the score in other populations.

Prediction of long-term unprovoked seizures after status epilepticus.

OBJECTIVE: Possible long-term consequences of status epilepticus (SE) include cognitive and behavioral impairment and the development of chronic epilepsy. However, these aspects have not been systematically studied in clinical practice. We aimed to evaluate long-term seizure recurrence after SE and the potential risk factors for their development. METHODS: Data were obtained from a prospective registry of all SE episodes occurring in adult patients who attended our center from February 2011 to April 2022. Clinical data, electroencephalographic findings, treatment, and long-term data were prospectively recorded. We performed a cross-sectional study of consecutive SE patients without previous epilepsy diagnosis, and analyzed the development of unprovoked remote seizures. RESULTS: A total of 849 patients were registered in the database. After excluding in-hospital mortality (198/849, 23.3%) and patients with prior epilepsy history (291/849, 44.7%), 360 patients (42.4%) with a first SE episode were included. The median age was 68 years (interquartile range [IQR] = 56-79), and 176 patients (48.9%) were women. The median time to first-line treatment initiation was 2 h (IQR = .7-7.4), and it was correlated with SE duration (R = .375, p < .001). One hundred nine patients (30.3%) presented unprovoked seizures during a median follow-up of 1.8 years (IQR = .5-4.3). After adjusting for identifiable confounders in a multivariable Cox regression analysis, progressive symptomatic etiology (hazard ratio [HR] = 1.97, 95% confidence interval [CI] = 1.17-3.33, p = .011), time to first-line treatment initiation > 1.5 h (HR = 1.89, 95% CI = 1.25-2.87, p = .003), and superrefractory SE (HR = 2.34, 95% CI = 1.26-4.33, p = .007) were independently associated with a greater risk of unprovoked seizure recurrence. In contrast, older patients (HR = .99, 95% CI = .97-.99, p = .021) and an acute symptomatic etiology (HR = .44, 95% CI .28-.68, p < .001) were at lower risk of unprovoked seizure recurrence. SIGNIFICANCE: The etiology of SE, the delay in initiating SE treatment, and the presence of superrefractoriness have been identified as potentials factors associated with unprovoked remote seizures following a new onset SE. Therefore, prompt and appropriate management should be applied to avoid seizure recurrence.

Posterior reversible encephalopathy syndrome (PRES) associated with COVID-19.

The novel human coronavirus disease (COVID-19) has been associated with vascular and thrombotic complications, some of which may result from endothelial dysfunction, including the posterior reversible encephalopathy syndrome (PRES). We report a case series of 8 patients with COVID-19 and PRES diagnosed at two academic medical centers between March and July of 2020. The clinical, laboratory and radiographic data, treatment, and short-term outcomes were retrospectively analyzed. The mean age was 57.9 ± 12 years, and 50% were women. Four patients had previous vascular comorbidities. All the patients suffered from severe pneumonia, requiring intensive care unit admission. Five patients were not hypertensive at presentation (all SBP < 127 mmHg). Neurologic symptoms included seizures in 7 patients; impaired consciousness in 5 patients; focal neurological signs in 3 patients; and visual disturbances in 1 patient. All patients underwent brain magnetic resonance imaging which indicated asymmetric T2 prolongation or diffusion changes (50%), extensive fronto-parieto-occipital involvement (25%), vascular irregularities (12.5%) and intracranial hemorrhage (25%). Four patients were treated with tocilizumab. Three patients were discharged without neurologic disability, 2 patients had persistent focal neurologic deficits and 2 expired. One patient's prognosis remains guarded. Together, these data support the relationship between PRES and endothelial dysfunction associated with severe COVID-19. In patients with severe COVID-19, PRES can be triggered by uncontrolled hypertension, or occur independently in the setting of systemic illness and certain medications. Like other infectious processes, critically ill patients with COVID-19 may be at greater risk of PRES because of impaired vasoreactivity or the use of novel agents like Tocilizumab.

Medium-term effects of COVID-19 pandemic on epilepsy: A follow-up study.

OBJECTIVE: To analyze the medium-term impact of the COVID-19 pandemic on epilepsy patients, focusing on psychological effects and seizure control. METHODS: Prospective follow-up study to evaluate the medium-term effects of the COVID-19 pandemic on a cohort of epilepsy patients from a tertiary hospital previously surveyed during the first peak of the pandemic. Between July 1, 2020, and August 30, 2020, the patients answered an online 19-item questionnaire, HADS, and PSIQ scales. Short- and medium-term effects of the pandemic confinement and the perception of telemedicine were compared. RESULTS: 153 patients completed the questionnaire, mean ± SD age, 47.6 ± 19.3 years; 49.7% women. Depression was reported by 43 patients, significantly more prevalent than in the short-term analysis (29.2% vs. 19.7%; p = .038). Anxiety (38.1% vs. 36.1%; p = 0.749) and insomnia (28.9% vs. 30.9%, p = .761) remained highly prevalent. Seventeen patients reported an increase in seizure frequency (11.1% vs. 9.1%, p = .515). The three factors independently associated with an increase in seizure frequency in the medium term were drug-resistant epilepsy (odds ratio [OR] = 8.2, 95% CI 2.06-32.52), depression (OR = 6.46, 95% CI 1.80-23.11), and a reduction in income (OR = 5.47, 95% CI 1.51-19.88). A higher proportion of patients found telemedicine unsatisfactory (11.2% vs. 2.4%), and a lower percentage (44.8% vs. 56.8%) found it very satisfactory (p = .005). CONCLUSIONS: Depression rates increased significantly after the first wave. Depression, drug-resistant epilepsy, and a reduction in family income were independent risk factors for an increased seizure frequency. Perception of telemedicine worsened, indicating need for re-adaptation.

Headache: A striking prodromal and persistent symptom, predictive of COVID-19 clinical evolution.

OBJECTIVE: To define headache characteristics and evolution in relation to COVID-19 and its inflammatory response. METHODS: This is a prospective study, comparing clinical data and inflammatory biomarkers of COVID-19 patients with and without headache, recruited at the Emergency Room. We compared baseline with 6-week follow-up to evaluate disease evolution. RESULTS: Of 130 patients, 74.6% (97/130) had headache. In all, 24.7% (24/97) of patients had severe pain with migraine-like features. Patients with headache had more anosmia/ageusia (54.6% vs. 18.2%; p < 0.0001). Clinical duration of COVID-19 was shorter in the headache group (23.9 ± 11.6 vs. 31.2 ± 12.0 days; p = 0.028). In the headache group, IL-6 levels were lower at the ER (22.9 (57.5) vs. 57.0 (78.6) pg/mL; p = 0.036) and more stable during hospitalisation. After 6 weeks, of 74 followed-up patients with headache, 37.8% (28/74) had ongoing headache. Of these, 50% (14/28) had no previous headache history. Headache was the prodromal symptom of COVID-19 in 21.4% (6/28) of patients with persistent headache (p = 0.010). CONCLUSIONS: Headache associated with COVID-19 is a frequent symptom, predictive of a shorter COVID-19 clinical course. Disabling headache can persist after COVID-19 resolution. Pathophysiologically, its migraine-like features may reflect an activation of the trigeminovascular system by inflammation or direct involvement of SARS-CoV-2, a hypothesis supported by concomitant anosmia.

Epilepsy in time of COVID-19: A survey-based study.

OBJECTIVES: Collateral damage may occur in epilepsy management during the coronavirus (COVID-19) pandemic. We aimed to establish the impact of this pandemic on epilepsy patients in terms of patient-reported seizure control and emerging symptoms. MATERIALS & METHODS: This is a cross-sectional study including consecutive patients assessed by telephone contact in an epilepsy clinic during the first month of confinement. Demographic and clinical characteristics were recorded, and a 19-item questionnaire was systematically completed. Data regarding the impact of confinement, economic effects of the pandemic, and subjective perception of telemedicine were recorded. Additional clinical data were obtained in patients with a COVID-19 diagnosis. RESULTS: Two hundred and fifty-five patients were recruited: mean age 48.2 ± 19.8 years, 121 (47.5%) women. An increase in seizure frequency was reported by 25 (9.8%) patients. Sixty-eight (26.7%) patients reported confinement-related anxiety, 22 (8.6%) depression, 31 (12.2%) both, and 72 (28.2%) insomnia. Seventy-three (28.6%) patients reported a reduction in economic income. Logistic regression analysis showed that tumor-related epilepsy etiology [OR = 7.36 (95% CI 2.17-24.96)], drug-resistant epilepsy [OR = 3.44 (95% CI 1.19-9.95)], insomnia [OR = 3.25 (95% CI 1.18-8.96)], fear of epilepsy [OR = 3.26 (95% CI 1.09-9.74)], and income reduction [OR = 3.65 (95% CI 1.21-10.95)] were associated with a higher risk of increased seizure frequency. Telemedicine was considered satisfactory by 214 (83.9%) patients. Five patients were diagnosed with COVID-19, with no changes in seizure frequency. CONCLUSIONS: The COVID-19 pandemic has effects in epilepsy patients. Patients with tumor-related, drug-resistant epilepsy, insomnia, and economic difficulties are at a higher risk of increased seizure frequency. Telemedicine represents a suitable tool in this setting.