Prevalence of comorbidities, and affective disorders in epilepsy: A latent class analysis approach.

OBJECTIVE: Epilepsies are severe chronic neurological diseases that impair several domains in life and are often accompanied by various somatic and psychiatric comorbidities. Associations between epilepsy and its comorbidities remain poorly understood. As epidemiological research mainly relies on cross-sectional designs and descriptive results, homogeneities regarding comorbidities in individuals suffering from epilepsy remain uncovered. Therefore, we aimed to identify clusters of individuals based on selected seizure-related variables and somatic comorbidities, and their respective risk of experiencing affective disorders, using a Latent Class Analysis (LCA). METHODS: Latent class analysis, is a model-driven statistical approach, which aims at latent, unobservable clusters on selected disease features. LCA has therefore the potential for uncovering previously unobservable groups or classes with similar comorbidity patterns. It allows for comparisons between those classes regarding risk or promotive factors - such as affective disorders. Our data derives from the Austrian cohort of the European Study on Burden and Care of Epilepsy (ESBACE; http://www.esbace.eu/). In ESBACE, multiple factors were collected to get a detailed picture on prevalence, epilepsy-related variables and comorbidities in a population-based cohort from the region of Salzburg, Austria. We used LCA to identify epilepsy-somatic-comorbidity-clusters and further, compared them to the observed the risk of suffering from affective disorders. RESULTS: The prevalence of epilepsy in the study region was 9.14/1000 inhabitants. LCA unveiled a three-cluster solution, of which one cluster, mainly consisting of individuals with mixed seizure types, higher age, and discrete somatic comorbidities (stroke, cardiovascular - and respiratory/pulmonary diseases) had a higher risk of experiencing affective disorders. SIGNIFICANCE: To our knowledge, this is the first large scale study that uses LCA to identify epilepsy-related comorbidity phenotypes, and therefore it might open a new way for epidemiological research.

Decrease in mortality of adult epilepsy patients since 1980: lessons learned from a hospital-based cohort.

BACKGROUND AND PURPOSE: Data on mortality in patients with epilepsy have been available since the 1800s. They consistently show a 2-3-fold increase compared to the general population. Despite major advances in diagnostic tools and treatment options, there is no evidence for a decrease in premature deaths. The temporal trend of mortality in a hospital-based epilepsy cohort over three decades was assessed. METHODS: A hospital-based incidence cohort was recruited from a specialized epilepsy outpatient clinic at Innsbruck Medical University between 1980 and 2007, divided by decade into three cohorts and followed for 5 years after initial epilepsy diagnosis. Deaths and their primary causes were determined using probabilistic record linkage with the Austrian death registry. Age-, sex- and period-adjusted standardized mortality rates (SMRs) were computed in relation to the general population of the same area and grouped according to time of diagnosis. RESULTS: In all, 122 deaths in 4549.9 person-years (1954.5 women, 2595.2 men) were identified. The overall SMR was 2.2 [95% confidence interval (CI) 1.8-2.6] and decreased from 3.0 (95% CI 2.1-4.3) in 1980-1989, to 2.7 (95% CI 2.0-3.5) in 1990-1999 and to 1.4 (95% CI 1.0-2.0) in 2000-2007. CONCLUSIONS: This study indicates a decrease in mortality in newly diagnosed epilepsy patients over the last three decades. This may be due to advances in diagnosis and treatment over the past three decades, including early identification of drug resistance, introduction of new anti-epileptic drugs and establishment of a comprehensive epilepsy surgery programme in this region.