Unemployment and early retirement among patients with epilepsy - A study on predictors, resilience factors and occupational reintegration measures.

The primary aim of this study was to identify predictors and resilience factors for unemployment and early retirement in patients with epilepsy of working age based on data from a multicenter German cohort study performed in 2020 (n = 456) by using multivariate binary logistic regression analysis. A second aim was to assess the assumed working ability of patients as well as the use of occupational reintegration measures. The unemployment rate was 8.3%, and 18% of patients had retired early due to epilepsy. Multivariate binary logistic regression analysis identified the presence of a relevant disability and frequent seizures as significant predictors of unemployment and early retirement, while seizures in remission were the only resilience factor associated with job retention. Regarding occupational incapacity, at the time of the survey, most of the patients in early retirement or unemployment were fit for work in their original or extended occupational setting. The proportion of patients with recent epilepsy-related occupational retraining (0.4%) or job changes (0.9%) was low, and only 2.4% reported an epilepsy-related reduction in work time. These findings underline the persistent disadvantage of patients with epilepsy in the professional field and the urgent need for effective, comprehensive work reintegration measures that must be made accessible for all patients.

Informed DEcision for cerebrospinal fluid analysis after epiLeptic seizures- the IDEAL-score: A development and validation study.

BACKGROUND: This observational study was done to develop a score based on clinical predictors that enables a guided decision for the necessity of cerebrospinal fluid (CSF) analysis after first unprovoked epileptic seizures and to validate this score in a retrospective patient cohort. METHODS: Clinical predictors were identified by two panels of epilepsy experts and selected according to content validity ratios. Based on these predictors a score was created and applied to a cohort of patients with first epileptic seizures. RESULTS: The "IDEAL score" consists of 9 items (fever, prolonged disturbance of consciousness, headache, imaging results, cognitive dysfunction, status epilepticus, malignancy, autoimmune encephalitis symptoms) that are collected at two different time points (< 3 h [A-score]; > 3 h [B-score] after hospital admittance). A CSF analysis is recommended, if at least one clinical finding is present, either one of the items evaluated during the acute phase (A-score) or later in the diagnostic process (B-score). In 41 patients (13%) CSF analysis provided essential clues to the cause of the seizure. The combined IDEAL score reached a sensitivity of 98%, a specificity of 53%, a positive predictive value of 24% and a negative predictive value of 99% in this patient cohort. CONCLUSIONS: A CSF analysis after first epileptic seizures provided decisive etiological findings in only 13% of all investigated patients. The IDEAL score offers clinicians a simple and easy-to-implement algorithm to assess the necessity of a CSF analysis, and to prevent unnecessary diagnostic procedures.

Nonlesional late-onset epilepsy: Semiology, EEG, cerebrospinal fluid, and seizure outcome characteristics.

INTRODUCTION: Incidence and prevalence of epilepsy increase with advancing age. Although the majority of late-onset epilepsies are of lesional origin, a considerable proportion of patients present with unknown etiology. The aim of this study was to evaluate the semiological, electroencephalographic (EEG), and cerebrospinal fluid (CSF) characteristics as well as the 12-month seizure outcome in a cohort of patients with nonlesional late-onset epilepsy (≥55 years). METHOD: A total of 54 patients with newly diagnosed nonlesional late-onset epilepsy (NLLOE) were retrospectively evaluated for seizure type using the most recent International League Against Epilepsy (ILAE) classification of seizure types, EEG characteristics, and CSF profile and followed-up for at least 12 months after epilepsy onset. Results were compared with a gender-matched control group of 58 patients with nonlesional early-onset epilepsy (NLEOE). RESULTS: The predominant seizure types in NLLOE were focal to bilateral tonic-clonic seizures (30%) as well as focal onset impaired awareness motor seizures (IAMS) (22%) and focal onset impaired awareness nonmotor seizures (IANMS) (22%). The predominant seizure types in NLEOE were focal to bilateral tonic-clonic seizures (43%) as well as focal onset aware nonmotor seizures (ANMS) (31%) and IAMS (31%). Focal onset impaired awareness nonmotor seizures were found to be more characteristic in patients with NLLOE (p = 0.019; α < 0.05; NLLOE: 22.2% vs. NLEOE: 8.6%). Electroencephalography revealed no significant differences between groups. Of interest, three patients with NLLOE (8%) presented with oligoclonal bands (OCB) in CSF albeit absence of antineuronal antibodies. Seizure-free rate was 70%. Adverse effects from medication leading to antiepileptic drug (AED) change were reported in 12 patients (22%), valproate was the best tolerated AED in patients with NLLOE [adverse effects in 9%, compared with 12% (gabapentin) and 26% (levetiracetam)]. CONCLUSIONS: Using the most recent classification system, different patterns of semiological characteristics were identified: NLLOE more frequently present with IANMS, whereas patients with NLEOE rather have ANMS. Oligoclonal bands were only detected in patients with NLLOE, indicating that careful exclusion of autoimmune encephalitis in this patient group is warranted. Our findings may help to more accurately identify and characterize patients with NLLOE to improve targeted diagnostics and adequate treatment in this challenging group of patients.