Electroencephalography as a tool for evidence-based diagnosis and improved outcomes in children with epilepsy in a resource-poor setting

Introduction: Electroencephalography (EEG) remains the most important investigative modality in the diagnostic evaluation of individuals with epilepsy. Children living with epilepsy in the developing world are faced with challenges of lack of access to appropriate diagnostic evaluation and a high risk of misdiagnosis and inappropriate therapy. We appraised EEG studies in a cohort of Nigerian children with epilepsy seen in a tertiary center in order to evaluate access to and the impact of EEG in the diagnostic evaluation of the cases. Methods: Inter-ictal EEG was requested in all cases of pediatric epilepsy seen at the pediatric neurology clinic of the University College Hospital, Ibadan, Nigeria over a period of 18 months. Clinical diagnosis without EEG evaluation was compared with the final diagnosis post- EEG evaluation. Results: A total of 329 EEGs were recorded in 329 children, aged 3months to 16 years, median 61.0 months. Clinical evaluation pre-EEG classified 69.3% of the epilepsies as generalized. The a posteriori EEG evaluations showed a considerably higher proportion of localization-related epilepsies (33.6%). The final evaluation post EEG showed a 21% reduction in the proportion of cases labeled as generalized epilepsy and a 55% increase in cases of localization-related epilepsy(p<0.001). Conclusion: Here we show that there is a high risk of misdiagnosis and therefore the use of inappropriate therapies in children with epilepsy in the absence of EEG evaluation. The implications of our findings in the resource-poor country scenario are key for reducing the burden of care and cost of epilepsy treatment on both the caregivers and the already overloaded tertiary care services.Pan African Medical Journal 2015; 2

Testicular tuberculosis presenting with metastatic intracranial tuberculomas only: a case report

<p>Abstract</p> <p>Introduction</p> <p>Intracranial tuberculomas are a rare complication of tuberculosis occurring through hematogenous spread from an extracranial source, most often of pulmonary origin. Testicular tuberculosis with only intracranial spread is an even rarer finding and to the best of our knowledge, has not been reported in the literature. Clinical suspicion or recognition and prompt diagnosis are important because early treatment can prevent patient deterioration and lead to clinical improvement.</p> <p>Case presentation</p> <p>We present the case of a 51-year-old African man with testicular tuberculosis and multiple intracranial tuberculomas who was initially managed for testicular cancer with intracranial metastasis. He had undergone left radical orchidectomy, but subsequently developed hemiparesis and lost consciousness. Following histopathological confirmation of the postoperative sample as chronic granulomatous infection due to tuberculosis, he sustained significant clinical improvement with antituberculous therapy, recovered fully and was discharged at two weeks post-treatment.</p> <p>Conclusion</p> <p>The clinical presentation of intracranial tuberculomas from an extracranial source is protean, and delayed diagnosis could have devastating consequences. The need to have a high index of suspicion is important, since neuroimaging features may not be pathognomonic.</p

Prevalence and Prognostic Features of ECG Abnormalities in Acute Stroke: Findings From the SIREN Study Among Africans

Background Africa has a growing burden of stroke with associated high morbidity and a 3-year fatality rate of 84%. Cardiac disease contributes to stroke occurrence and outcomes, but the precise relationship of abnormalities as noted on a cheap and widely available test, the electrocardiogram (ECG), and acute stroke outcomes have not been previously characterized in Africans. Objectives The study assessed the prevalence and prognoses of various ECG abnormalities among African acute stroke patients encountered in a multisite, cross-national epidemiologic study. Methods We included 890 patients from Nigeria and Ghana with acute stroke who had 12-lead ECG recording within first 24 h of admission and stroke classified based on brain computed tomography scan or magnetic resonance imaging. Stroke severity at baseline was assessed using the Stroke Levity Scale (SLS), whereas 1-month outcome was assessed using the modified Rankin Scale (mRS). Results Patients\u27 mean age was 58.4 ± 13.4 years, 490 were men (55%) and 400 were women (45%), 65.5% had ischemic stroke, and 85.4% had at least 1 ECG abnormality. Women were significantly more likely to have atrial fibrillation, or left ventricular hypertrophy with or without strain pattern. Compared to ischemic stroke patients, hemorrhagic stroke patients were less likely to have atrial fibrillation (1.0% vs. 6.7%; p = 0.002), but more likely to have left ventricular hypertrophy (64.4% vs. 51.4%; p = 0.004). Odds of severe disability or death at 1 month were higher with severe stroke (AOR: 2.25; 95% confidence interval: 1.44 to 3.50), or atrial enlargement (AOR: 1.45; 95% confidence interval: 1.04 to 2.02). Conclusions About 4 in 5 acute stroke patients in this African cohort had evidence of a baseline ECG abnormality, but presence of any atrial enlargement was the only independent ECG predictor of death or disability

Abdominal ultrasonography in HIV/AIDS patients in southwestern Nigeria

<p>Abstract</p> <p>Background</p> <p>Though the major target of the HIV-virus is the immune system, the frequency of abdominal disorders in HIV/AIDS patients has been reported to be second only to pulmonary disease. These abdominal manifestations may be on the increase as the use of antiretroviral therapy has increased life expectancy and improved quality of life. Ultrasonography is an easy to perform, non invasive, inexpensive and safe imaging technique that is invaluable in Africa where AIDS is most prevalent and where sophisticated diagnostic tools are not readily available. Purpose: To describe the findings and evaluate the clinical utility of abdominal ultrasonography in HIV/AIDS patients in Ibadan, Nigeria</p> <p>Methods</p> <p>A Prospective evaluation of the abdominal ultrasonography of 391 HIV-positive patients as well as 391 age and sex-matched HIV-negative patients were carried out at the University College Hospital, Ibadan.</p> <p>Results</p> <p>Of the 391 cases studied, 260 (66.5%) were females; the mean age was 38.02 years, (range 15–66 years). The disease was most prevalent in the 4th decade with an incidence of 40.4%. Compared with the HIV-negative individuals, the HIV+ group of patients had a significantly higher proportion of splenomegaly (13.5% vs. 7.7%; p < 0.01), lymphadenopathy (2.0% vs. 1.3%; p < 0.70), and renal abnormalities (8.4% vs. 3.8%; p < 0.02). There were no differences in hepatic and pancreatic abnormalities between the HIV+ and HIV- groups. There were significantly fewer gallstones in the HIV+ group (1.4% vs. 5.1%; p < 0.01).</p> <p>Conclusion</p> <p>AIDS is a multi-systemic disease and its demographic and clinical pattern remains the same globally. Ultrasonography is optimally suited for its clinical management especially in Africa. Its accuracy and sensitivity may be much improved with clinico-pathologic correlation which may not be readily available in developing countries; further studies may provide this much needed diagnostic algorithms.</p

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing