Seizure-related injuries in inadequately treated epilepsy patients: A case-control study.

PURPOSE: To compare epilepsy-related injuries in untreated or inadequately treated patients and patients on adequate treatment. METHODS: In a cross-sectional case-control study, seizure-related injuries in patients who were either on no treatment or inadequate treatment were compared with another group of patients receiving appropriate evidence-based epilepsy treatment. The inadequately treated patients or 'cases' were drawn from an outreach epilepsy clinic while the adequately treated patients or 'controls' were recruited from a tertiary care facility providing comprehensive epilepsy management. RESULTS: The odds of injury were eight times higher in inadequately treated patients or cases compared to the adequately treated patients or controls. After adjusting for gender, epilepsy duration, seizure frequency, current medication, and number of AEDs, the odds of injury were 15. 8 times higher in the cases. Major injuries such as burns, fractures, and tooth injuries were also higher in the cases. CONCLUSION: Untreated or inadequately treated epilepsy patients have a significantly higher risk of injuries. With adequate treatment, some of the risks of injury can be mitigated.

The development of a smartphone application to help manage epilepsy in resource-limited settings.

PURPOSE: Epilepsy is treatable but in low- and middle-income countries (LMICs) it goes untreated with dire consequences for people with it and their families. There are not enough available doctors to treat it so it has been suggested that non-physician health workers (NPHWs) take a role in diagnosis and management. Tools will be essential to help them. A smartphone application (app) for episode diagnosis has proved safe and effective; this paper describes an app for epilepsy management. METHODS: Questions were devised which captured temporal characteristics of episodes, diagnosis of episodes, seizure types, and epilepsy type, together with information on previous investigations, treatment, drug reactions, and current treatment. For untreated patients a management plan was suggested. The app generated a summary which could be sent to a remote specialist for advice. The finished app was evaluated in 23 people presenting with possible epilepsy by four doctors in training and one NPHW; its summary was compared to face-to-face evaluation by a neurologist. RESULTS: The app was correct in 22 of 23 (96 %) patients for episode diagnosis, 2 of 2 for symptomatic seizures,18/20 (90 %) for epilepsy type and 9/10 (90 %) for treatment suggestion in untreated patients. The app took less than 15 min to complete. CONCLUSION: The initial results suggest that this management app is a worthwhile tool to help inexpert doctors or NPHWs manage suspected epilepsy. Its accuracy is well within reported inter-observer agreement. In its present form it requires input from a remote epilepsy specialist. This combination is a potential solution to managing epilepsy in LMICs.

Managing Epilepsy by Telemedicine in Resource-Poor Settings.

Epilepsy is a common and treatable disease; in rich countries the expectation is that two-thirds of people will have their seizure episodes controlled on medication. In low- and middle-income countries (LMICs) however most people are not on treatment either because no doctors live near them or the logistics of affordable drug supply is absent. People with epilepsy then are prone to the bad effects of this disease-death, disfigurement from accidents and burns, and social problems due to the stigma with which the disease is associated. So this represents a failure of conventional face-to-face medicine. Might a telemedicine approach do better? The World Health Organization has suggested that non-physician health workers are empowered to diagnose and manage epilepsy; to do this they will need considerable medical support, which might be provided by telemedicine through the telephone, smartphone applications or a combination. This paper sets out what telemedicine does at present for people with epilepsy in LMICs and suggests how it might be developed in the future.

Diagnosis of epileptic seizures by community health workers using a mobile app: A comparison with physicians and a neurologist.

PURPOSE: The World Health Organisation (WHO) strategy for non-physician health workers (NPHWs) to diagnose and manage people with untreated epilepsy depends on them having access to suitable tools. We have devised and validated an app on a tablet computer to diagnose epileptic episodes and now examine how its use by NPHWs compares with diagnosis by local physicians and a neurologist. METHODS: Fifteen NPHWs at Jan Swasthya Sahyog (JSS) a hospital with community outreach in Chhattisgarh, India were trained in the use of an epilepsy diagnosis app on a tablet computer. They were asked to determine the app scores on patients in their communities with possible epilepsy and then refer them first to their local JSS doctors and then to a visiting neurologist. With the neurologist's opinion as the "gold standard", the misdiagnosis rate from the NPHWs was compared with that of the local physicians. RESULTS: There were 96 patients evaluated completely. The NPHWs misdiagnosed eight and the physicians seven. There were more uncertain diagnoses by the NPHWs. In the 22 patients who presented for the first time during the study, the NPHWs misdiagnosed three and the physicians five. CONCLUSIONS: NPHWs using an app achieved similar misdiagnosis rates to local physicians. Both these rates were well within the range of misdiagnosis in the published literature. These results suggest that task-shifting epilepsy diagnosis and management from physicians to NPHWs, who are enabled with appropriate technology, can be an effective and safe way of reducing the epilepsy treatment gap.

Help seeking and suicidality among people with epilepsy in a rural low income country setting: cross-sectional survey.

BACKGROUNDS: Epilepsy is a serious neurological disorder associated with a high level of psychiatric comorbidity. Suicidality is a recognised complication of epilepsy. As part of developing an integrated service for people with epilepsy (PWE) and priority psychiatric disorders within primary care, a cross-sectional study was conducted in a rural district in Ethiopia to investigate patterns of help-seeking, suicidality and the association with duration of untreated epilepsy (DUE) among PWE. METHODS: Cases were identified through community key informants and diagnosis was confirmed by trained primary care clinicians. Severity of epilepsy, depression and suicidality were assessed using standardised methods. Multivariable regression analysis was used to test the hypothesis that suicidality was associated with DUE. RESULTS: The majority of PWE sought help from both religious and biomedical healing centres. The lifetime treatment gap for biomedical care was 26.9%, with a 12 month treatment gap of 56.7%. Close to one-third (29.9%) of participants reported using traditional and cultural healing practices. Nearly one-third (30.2%) of participants reported suicidality (suicidal ideation, plan or attempt) in the previous 1 year. The median (IQR) DUE was 24 months (4-72). There was no association between DUE and suicidality. In the multivariable model, being married [odds ratio (OR) 2.81, 95% CI 1.22, 6.46], increased depressive symptoms (OR 1.17, 95% CI 1.10, 1.26) and perceived poorer wealth relative to others (OR 2.67, 95% CI 1.07, 6.68) were associated independently with suicidality. CONCLUSION: In this study, PWE sought help from both biomedical and religious healing centres. Suicidality and depression have a high prevalence in PWE in this setting. Integrated mental and neurological health care within primary care is needed for improved holistic management of epilepsy.

Validation of a phone app for epilepsy diagnosis in India and Nepal.

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.

Telemedicine for epilepsy support in resource-poor settings.

THE PROBLEM: Epilepsy is a common disease worldwide causing significant physical and social disability. It is one of the most treatable neurological diseases. Yet, in rural, poorer countries like much of India and Nepal, most people with epilepsy are not undergoing any treatment often because they cannot access doctors. Conventional Approaches: It is being appreciated that perhaps doctors are not the solution and that enabling health workers to treat epilepsy may be better. Few details, however, have been put forward about how that might be achieved. Thinking Differently: Untreated epilepsy should be considered a public health problem like HIV/AIDS, the various steps needed for treatment identified and solutions found. Telemedicine Approaches: Telemedicine might contribute to two steps - diagnosis and review. A tool that enables non-doctors to diagnose episodes as epileptic has been developed as a mobile phone app and has good applicability, sensitivity, and specificity for the diagnosis. There are a number of ways in which the use of phone review or short messaging service can improve management. CONCLUSION: Telemedicine, as part of a public health program, can potentially help the millions of people in the resource-poor world with untreated epilepsy.

A Bayesian tool for epilepsy diagnosis in the resource-poor world: development and early validation.

PURPOSE: The epilepsy treatment gap in resource-poor countries is so large that existing numbers of doctors are unlikely to be able to close it. Other health workers are likely to be needed but they will need help. The diagnosis of an attack as epileptic or not is an essential step in the management of epilepsy. It should be possible to devise a tool to give the probability of episodes being epileptic based on a Bayesian analysis of the results of history taking. METHOD: We asked about the nature of episodes in patients referred to epilepsy camps in Nepal. Answers were then compared to the final clinical diagnosis of epilepsy and the likelihood ratio (LR) of the episode being epileptic obtained for each answer. The most informative LRs, tested sequentially, formed the basis for a tool which was validated in a different Nepalese population. RESULTS: Data was obtained from 67 patients. The pre-test probability of having epilepsy was 0.76. Answers to 11 questions with the most informative LRs were then combined into a tool. This was tested on 14 different patients. Post-test probability scores in those with epilepsy ranged from 0.88 to 1 and for those with non-epilepsy from 0.07 to 0.42. CONCLUSION: It is possible to devise a tool based on simple clinical information using Bayesian principles. Initial validation suggests that this has the potential to enable health workers to diagnose episodes as epileptic or not. This now needs to be tested in different populations. The tool is easily converted to a mobile phone app.