The Prevalence of Depression in Patients With Epilepsy in the Kingdom of Saudi Arabia

Abstract

Objective Among patients with epilepsy (PWE), the prevalence of depression ranges from 30% to 50%, with a 5-25% prevalence of suicide. Depression and epilepsy affect daily tasks such as driving, employment, and physical activity. Depression is the most common comorbidity among patients with epilepsy. Because both conditions involve pathophysiological changes, treating mood disorders helps treat epilepsy and vice versa. Studies about epilepsy and depression in Saudi Arabia are scarce, and no study has been conducted on this topic at King Fahad Medical City (KFMC); hence, we aimed to determine the prevalence of depression among PWE who were followed up at KFMC. Methods This retrospective hospital-based study was conducted at KFMC in Riyadh, Saudi Arabia. This investigation spanned a period of 10 years, from 2008 to 2018. The study included patients with PWE who were diagnosed with depression. Results According to a study of individuals aged 18 to 69, 73.7% of patients had been diagnosed with chronic depression (i.e., for more than a year); most of these patients had completed elementary school. Higher rates of depression were also observed among elementary school pupils, divorced women, and non-Riyadh residents. A correlation was observed between the severity of depression based on the Patient's Health Questionnaire( PHQ-9) score, which was used to screen for depression and diabetes mellitus (DM), the number of antidepressant medications (ADM) used, the duration of antidepressant use, suicidal ideation or attempts, and the duration of depression. Epilepsy was most prevalent in the temporal lobe, accounting for 22.6% of all cases, and it was managed in 78.2% of the patients. The duration of epilepsy was significantly associated with the severity of depression.

Keywords: antiseizure medications; depression; kfmc; pwe; saudi arabia.

Figure 1. Pie chart of the severity of depression among the study group

Figure 2. Multivariable logistic regression analysis of potential factors associated with the severity of depression