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Summary: Background: Identification of convulsive epilepsy in sub-Saharan Africa relies on access to resources that are often unavailable. Infrastructure and resource requirements can further complicate case verification. Using machine-learning techniques, we have developed and tested a region-specific questionnaire panel and predictive model to identify people who have had a convulsive seizure. These findings have been implemented into a free app for health-care workers in Kenya, Uganda, Ghana, Tanzania, and South Africa. Methods: In this retrospective case-control study, we used data from the Studies of the Epidemiology of Epilepsy in Demographic Sites in Kenya, Uganda, Ghana, Tanzania, and South Africa. We randomly split these individuals using a 7:3 ratio into a training dataset and a validation dataset. We used information gain and correlation-based feature selection to identify eight binary features to predict convulsive seizures. We then assessed several machine-learning algorithms to create a multivariate prediction model. We validated the best-performing model with the internal dataset and a prospectively collected external-validation dataset. We additionally evaluated a leave-one-site-out model (LOSO), in which the model was trained on data from all sites except one that, in turn, formed the validation dataset. We used these features to develop a questionnaire-based predictive panel that we implemented into a multilingual app (the Epilepsy Diagnostic Companion) for health-care workers in each geographical region. Findings: We analysed epilepsy-specific data from 4097 people, of whom 1985 (48·5%) had convulsive epilepsy, and 2112 were controls. From 170 clinical variables, we initially identified 20 candidate predictor features. Eight features were removed, six because of negligible information gain and two following review by a panel of qualified neurologists. Correlation-based feature selection identified eight variables that demonstrated predictive value; all were associated with an increased risk of an epileptic convulsion except one. The logistic regression, support vector, and naive Bayes models performed similarly, outperforming the decision-tree model. We chose the logistic regression model for its interpretability and implementability. The area under the receiver operator curve (AUC) was 0·92 (95% CI 0·91–0·94, sensitivity 85·0%, specificity 93·7%) in the internal-validation dataset and 0·95 (0·92–0·98, sensitivity 97·5%, specificity 82·4%) in the external-validation dataset. Similar results were observed for the LOSO model (AUC 0·94, 0·93–0·96, sensitivity 88·2%, specificity 95·3%). Interpretation: On the basis of these findings, we developed the Epilepsy Diagnostic Companion as a predictive model and app offering a validated culture-specific and region-specific solution to confirm the diagnosis of a convulsive epileptic seizure in people with suspected epilepsy. The questionnaire panel is simple and accessible for health-care workers without specialist knowledge to administer. This tool can be iteratively updated and could lead to earlier, more accurate diagnosis of seizures and improve care for people with epilepsy. Funding: The Wellcome Trust, the UK National Institute of Health Research, and the Oxford NIHR Biomedical Research Centre.

Chemotherapy has been used to inhibit cancer growth for decades, but emerging evidence shows it can affect the tumor stroma, unintentionally promoting cancer malignancy. After treatment of primary tumors, remaining drugs drain via lymphatics. Though all drugs interact with the lymphatics, we know little of their impact on them. Here, we show a previously unknown effect of platinums, a widely used class of chemotherapeutics, to directly induce systemic lymphangiogenesis and activation. These changes are dose-dependent, long-lasting, and occur in healthy and cancerous tissue in multiple mouse models of breast cancer. We found similar effects in human ovarian and breast cancer patients whose treatment regimens included platinums. Carboplatin treatment of healthy mice prior to mammary tumor inoculation increased cancer metastasis as compared to no pre-treatment. These platinum-induced phenomena could be blocked by VEGFR3 inhibition. These findings have implications for cancer patients receiving platinums and may support the inclusion of anti-VEGFR3 therapy into treatment regimens or differential design of treatment regimens to alter these potential effects.

BackgroundEpilepsy is one of the most common neurological conditions globally, estimated to constitute 0.75% of the global burden of disease, with the majority of this burden found in low- and middle- income countries (LMICs). Few studies from LMICs, including much of sub-Saharan Africa, have described the incidence, remission or mortality rates due to epilepsy, which are needed to quantify the burden and inform policy. This study investigates the epidemiological parameters of convulsive epilepsy within a context of high HIV prevalence and an emerging burden of cardiovascular disease.MethodsA cross-sectional population survey of 82,818 individuals, in the Agincourt Health and Socio-demographic Surveillance Site (HDSS) in rural northeast South Africa was conducted in 2008, from which 296 people were identified with active convulsive epilepsy. A follow-up survey was conducted in 2012. Incidence and mortality rates were estimated, with duration and remission rates calculated using the DISMOD II software package.ResultsThe crude incidence for convulsive epilepsy was 17.4/100,000 per year (95%CI: 13.1-23.0). Remission was 4.6% and 3.9% per year for males and females, respectively. The standardized mortality ratio was 2.6 (95%CI: 1.7-3.5), with 33.3% of deaths directly related to epilepsy. Mortality was higher in men than women (adjusted rate ratio (aRR) 2.6 (95%CI: 1.2-5.4)), and was significantly associated with older ages (50+ years versus those 0-5 years old (RR 4.8 (95%CI: 0.6-36.4)).ConclusionsThe crude incidence was lower whilst mortality rates were similar to other African studies; however, this study found higher mortality amongst older males. Efforts aimed at further understanding what causes epilepsy in older people and developing interventions to reduce prolonged seizures are likely to reduce the overall burden of ACE in rural South Africa.

The article focuses on applying social network theory to evaluate and utilize different social media platforms for various graduate medical education (GME) applications, based on factors like density, diffusion, and complexity.

Byline: Arun. Mani, Appaswamy. Prabhakar, P. Alexander, Aditya. Nair, Asish. Vijayaraghavan, Atif. Shaikh, Rohit. Benjamin, Ajith. Sivadasan, Vivek. Mathew, Sanjith. Aaron, Mathew. Alexander Background: Guillain-Barre syndrome can be electrophysiologically classified [...]

Byline: Sanjith. Aaron, John. Mary, Anupriya. Arthur, Shyamkumar. Nidugala, Sunithi. Mani, A. Prabakhar, Ajith. Sivadasan, Vivek. Mathew, Mathew. Alexander Sir, A 30-year-old lady presented was brought to the emergency room [...]

Byline: Asish. Vijayaraghavan, Pullumpallil. Alexander, Aditya. Nair, Ajith. Sivadasan, Arun. Mani, Donna. Mathew, Atif. Shaikh, Rohit. Benjamin, A. Prabhakar, John. Jude, Sunithi. Mani, Sanjith. Aaron, Vivek. Mathew, Mathew. Alexander Background: [...]

Byline: Arun. Mani, A. Prabhakar, Pavithra. Mannam, Rohit. Benjamin, Atif. Ahmed Shaikh, Donna. Mathew, Pankaj. Singh, Aditya. Nair, P. Alexander, Asish. Vijayaraghavan, Ajith. Sivadasan, Sunithi. Mani, Vivek. Mathew, Sanjith. Aaron, [...]

Byline: Sanjith. Aaron, Jeyaseelan. Lakshmanan, Thambu. Sudarsanam, Kenneth. Benjamin, Jothilakshmi. Durairaj, Vivek. Mathew, Ajith. Sivadasan, A. Prabhakar, Shyam. N. Keshava, Pavitra. Mannam, Prabhu. Kirubakaran, Jayaprakash. Muliyil, Mathew. Alexander Background and [...]

Byline: Anupriya. Arthur, Ajith. Sivadasan, Pavitra. Mannam, A. Prabakhar, Sanjith. Aaron, Vivek. Mathew, M. Karthik, Rohith. Benjamin, Shaikh. Iqbalahmed, Gideon. Rynjah, Mathew. Alexander Background: Tolosa-Hunt Syndrome (THS) is one of [...]

Byline: Ajith. Sivadasan, Mathew. Alexander, Sanjith. Aaron, Vivek. Mathew, Shalini. Nair, Karthik. Muthusamy, A. Prabhakar, Rohit. Benjamin, Atif. Shaikh, Gideon. Rynjah Introduction: There is scarce literature regarding the clinical course, [...]

Byline: Prabhakar. Appasamy, Teddy. Dan, Vedavati. Bandyopadhyay, Vivek. Mathew, Visalakshi. Jeyaseelan, Suresh. Babu, Sanjith. Aaron, Mathew. Alexander Introduction: The Babinski sign is one of the most important clinical signs for [...]

Accessing difficult to reach hydrocarbon reservoirs while simultaneously reducing risk and increasing efficiency demonstrates a need for improved autonomous directional control of rotary steerable systems (RSS). The inherently uncertain drilling environment presents a challenge for control algorithms and human operators alike, where model mismatch can be significant and the parameters are time varying. Parameter estimation can improve the performance of steering controllers through model adaptation as well as provide valuable information to human operators. This paper proposes the use of a Markov Chain Monte Carlo (MCMC) method to estimate time-varying model parameters in real-time using only measurements commonly obtained while drilling. The proposed method is evaluated on historical field data and its accuracy is quantified by prediction accuracy to achieve a mean absolute error of 0.68 deg over 30 m. Next, the proposed method is used to adapt the model of a model predictive controller (MPC) and its performance is compared with a static MPC in closed-loop simulation of a prototypical drilling scenario. The estimator reduces tracking error of the MPC by 93.36% and produces a higher quality borehole. Finally, the utility of estimation for human-in-the-loop operation is explored through the design of an early warning system (EWS). The posterior distribution produced by MCMC is utilized in the EWS to predict the probability of undesirable future trajectories. By providing automatic alerts, the EWS serves as a safety mechanism that enhances operators' proficiency when monitoring several autonomously drilled wells. [ABSTRACT FROM AUTHOR]

Medicaid is a critical antipoverty program. Since the Affordable Care Act expanded Medicaid eligibility, millions of newly eligible people have enrolled, creating positive financial improvements for low-income families. We examined the association of Virginia's 2019 Medicaid expansion and changes in health care--related and non-health-care-related financial needs among newly eligible Medicaid enrollees. Our unique survey collected responses between December 2018 and April 2019 from newly enrolled members reporting on experiences in the year before enrollment and between July 2020 and May 2021 from members reporting on experiences one year after enrollment. The follow-up period coincided with the COVID-19 pandemic. Medicaid enrollment was associated with decreases in concern about all financial needs assessed: housing, food, monthly bills, credit card and loan payments, and health care costs. These reductions were broadly similar across demographic subgroups and across the months of the pandemic that overlapped with the follow-up period. We add to the evidence that Medicaid expansion is a social safety-net policy that could improve equity among low-income families, potentially encouraging states that have yet to expand to do so. [ABSTRACT FROM AUTHOR]

Byline: Rohit. Benjamin, Sanjith. Aaron, Ajith. Sivadasan, Suresh. Devasahayam, Amalan. Sebastin, Mathew. Alexander Background: Autoimmune autonomic dysfunction is described in Myasthenia Gravis. In myasthenic crisis, the spectrum of autonomic dysfunction [...]

Byline: Vedantam. Rajshekhar, Mathew. Alexander [AUTHOR:1] Prof KV Mathai (KVM), born on 17 October 1926, joined the portals of Christian Medical College (CMC), Vellore in 1947 as one of the [...]

Byline: Sanjith. Aaron, Anupriya. Arthur, A. Prabakhar, Pavitra. Mannam, N. Shyamkumar, Sunithi. Mani, Vivek. Mathew, Jeyanthi. Peter, Ajith. Sivadasan, Anika. Alexander, M. Karthik, Rohith. Benjamin, Mathew. Alexander Visual impairment can [...]

Byline: Ajith. Sivadasan, Karthik. Muthusamy, Bimal. Patel, Rohit. Benjamin, A. Prabhakar, Vivek. Mathew, Sanjith. Aaron, Mathew. Alexander Objectives: There are limited data regarding long-term follow-up and therapeutic outcomes in Sjogren's [...]

Byline: Suresh. Pasangulapati, T. Murthy, Ajith. Sivadasan, L. Gideon, A. Prabhakar, Aaron. Sanjith, Vivek. Mathew, Mathew. Alexander Introduction: In chronic inflammatory demyelinating polyneuropathy (CIDP), emphasis has been on motor disabilities, [...]

Byline: Sahil. Kohli, Suresh. Pasangulapati, Sangeetha. Yoganathan, Gideon. Rynjah, A. Prabhakar, Sanjith. Aaron, Mathew. Alexander, Vivek. Mathew Objectives: To determine the proportion of refractory status epilepticus (RSE) and super-RSE (SRSE) [...]