RESUMEN
INTRODUCTION: Depressive disorder is the most common psychiatric comorbidity in individuals with epilepsy (IWE) and is associated with a significant negative impact with increased morbidity and mortality rate. However, the magnitude of comorbid depression in such patients in the Nepalese setting is still poorly understood. Therefore, we aimed to determine the magnitude of depression in individuals diagnosed as having epilepsy and further examine the influencing factors associated with it. METHODS: This cross-sectional observational study was conducted from April 2018 to September 2018 at Nepal Epilepsy Center, Lazimpat, Kathmandu, Nepal. One hundred and forty-two eligible subjects were enrolled for analysis. The core outcome variable evaluated in this study was depressive disorder, whereas age, gender, types of epilepsy, frequency of seizures, duration of epilepsy, and drug use were evaluated as covariates. The mean ages of the patients were 31.45⯱â¯12.05â¯years, and 87 (61.3%) were male. The prevalence of depression was found to be 31% (95% confidence interval [CI]; lower limit: 23.39% and upper limit: 38.60%), with majority subjects had a mild type of depression, and 63.63% (95% CI; lower limit: 55.05% and upper limit: 70.94%). The frequency of drug use remained a significant predictor for depression in individuals with epilepsy (Pâ¯=â¯0.002), and the odds of having depression in individuals receiving polytherapy were 3.82 higher than in those receiving monotherapy (95%: 1.61-9.05, Pâ¯=â¯0.002). CONCLUSION: Our study indicated a high rate of depression in a substantial number of IWE in the Nepalese setting. Polytherapy emerged as an independent predictor for depression. The high coexistence of depression in this vulnerable population and an increased risk for comorbid in polytherapy necessitate incorporating depression screening and proper treatment into the existing epilepsy program. Furthermore, revising treatment guidelines on comorbid depression to reduce polytherapy and encouraging health education on epilepsy to reduce stigma may also be warranted.
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Depresión , Epilepsia , Adulto , Comorbilidad , Estudios Transversales , Depresión/epidemiología , Epilepsia/complicaciones , Epilepsia/tratamiento farmacológico , Epilepsia/epidemiología , Humanos , Masculino , Prevalencia , Adulto JovenRESUMEN
PURPOSE: Most people with epilepsy live in low- or middle-income countries (LMICs) where there are relatively few doctors. Over 50% of people with epilepsy in these countries are untreated so other models of care are needed. In this report we evaluate a novel model of care. METHODS: We trained four residents of Myagdi, a rural district in Nepal as epilepsy field workers (EFWs). They provided epilepsy awareness to their communities. When they identified someone with possible epilepsy they used a smartphone application (app) to determine the probability score for an episode being epileptic and contacted an epilepsy specialist by phone. If the specialist thought treatment was indicated this was arranged by the EFW. We recorded mortality, change of diagnosis at face-to-face consultation and drug-related events as measures of safety. Seizure frequency and general wellbeing were also recorded, and a questionnaire was devised to measure satisfaction. RESULTS: 112 patients with app scores suggesting epileptic seizures were identified and managed in 18 months, of whom 15 had provoked seizures. Forty-three percent of epilepsy patients were untreated. At follow-up one had died of a cause other than epilepsy. Diagnostic agreement at face-to-face assessment was 93%. Overall 5% had side-effects of medication. Seizures were stopped in 33% and reduced in 57%. Ninety-six percent of patients preferred this service to travelling to other doctors. CONCLUSION: This novel service met all criteria of safety and was effective in reducing frequency of seizures. Patients preferred it to conventional services. It should be transferable to other LMICs.
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Agentes Comunitarios de Salud , Epilepsia , Aplicaciones Móviles , Evaluación de Procesos y Resultados en Atención de Salud , Población Rural , Convulsiones , Teléfono Inteligente , Telemedicina/métodos , Adolescente , Adulto , Anciano , Niño , Epilepsia/diagnóstico , Epilepsia/terapia , Femenino , Humanos , Masculino , Persona de Mediana Edad , Nepal , Convulsiones/diagnóstico , Convulsiones/terapia , Telemedicina/instrumentación , Telemedicina/normas , Teléfono , Adulto JovenRESUMEN
PURPOSE: Untreated epilepsy is a major global public health problem with more than 20 million people not being treated for an easily treatable disease. In part this is due to a lack of trained doctors. There are many more non-medical health workers than doctors and they could have an important role in diagnosis and treatment of epilepsy if they had some tools. We have previously described such a tool to distinguish epileptic episodes from other causes of altered consciousness and here present its validation in three new populations. METHODS: The tool was presented as a phone app where the answers to 11 questions provided a probability score which indicated whether episodes might be due to epilepsy or not. It was applied either by non-medical volunteers, health workers, or inexperienced doctors to 132 patients in three separate populations in India and Nepal and compared with the "gold standard" diagnosis of a neurologist with expertise in epilepsy. RESULTS: There was good agreement between the app score and the neurologists' diagnoses (weighted kappa=75.3%). An app score of 90 or greater had a sensitivity of 88% and a specificity of 100% for diagnosing epilepsy. The app was easy to use with little training and took about 5min to administer. CONCLUSION: A tool presented as a phone app can be used by non-medical health workers to identify episodes as epileptic or not with good accuracy. It needs to be evaluated more widely but has the potential to play a part in reducing the epilepsy treatment gap.
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Epilepsia/diagnóstico , Aplicaciones Móviles , Teléfono Inteligente , Algoritmos , Trastornos de la Conciencia/diagnóstico , Diagnóstico Diferencial , Personal de Salud , Humanos , India , Nepal , Probabilidad , Convulsiones/diagnóstico , Sensibilidad y Especificidad , Tiempo de Tratamiento , VoluntariosRESUMEN
BACKGROUND: Despite optimal medical therapy, a sizeable number of patients continue to have persistent seizures. We evaluated the association of pretreatment and treatment variables with unfavorable seizure outcome. METHODS: Patients with follow-up over 12 years in the Nepal Epilepsy Association were evaluated. Patients having seizures for at least a year and already on polytherapy after failure of two monotherapy trials were considered having unfavourable outcome. Variables under study were: age, sex, duration and frequency of seizures prior to treatment, type of seizure, neurological status, Computed Tomography (CT) finding, and failure of first anti-epileptic drug (AED). Bivariate analysis was done with Chi-square and Fisher exact tests. Potential interaction between variables was studied with a logistic regression analysis. RESULTS: Out of a total 529 consecutive patients, 490 were included in the study. Unfavorable seizure outcome was seen in 26.8% of patients. Among 284 patients who remained viable for analysis, bivariate analysis showed significant association of unfavorable outcome with frequency of seizure (p 0.01), abnormal neurological status (p 0.01) and failure of first AED (p 0.00), while no significant association was seen with age at onset (p 0.45), sex (p 0.47), duration of seizure (p 0.43), type of seizure (p 0.12), and presence of CT abnormality (p 0.46). The fitted regression model portended an unfavorable prognosis with failure of first AED and abnormal neurological status, however, failed to show significant association with frequency of seizure. CONCLUSIONS: Failure of first AED trial and associated neurological deficits are significant predictors of unfavorable seizure outcome.