Eye Segmentation Method for Telehealth: Application to the Myasthenia Gravis Physical Examination.

Due to the precautions put in place during the COVID-19 pandemic, utilization of telemedicine has increased quickly for patient care and clinical trials. Unfortunately, teleconsultation is closer to a video conference than a medical consultation, with the current solutions setting the patient and doctor into an evaluation that relies entirely on a two-dimensional view of each other. We are developing a patented telehealth platform that assists with diagnostic testing of ocular manifestations of myasthenia gravis. We present a hybrid algorithm combining deep learning with computer vision to give quantitative metrics of ptosis and ocular muscle fatigue leading to eyelid droop and diplopia. The method works both on a fixed image and frame by frame of the video in real-time, allowing capture of dynamic muscular weakness during the examination. We then use signal processing and filtering to derive robust metrics of ptosis and l ocular misalignment. In our construction, we have prioritized the robustness of the method versus accuracy obtained in controlled conditions in order to provide a method that can operate in standard telehealth conditions. The approach is general and can be applied to many disorders of ocular motility and ptosis.

A Digital Telehealth System to Compute the Myasthenia Gravis Core Examination Metrics.

Background: Telemedicine practice for neurological diseases has grown significantly during the COVID-19 pandemic.Telemedicine offers an opportunity to assess digitalization of examinations and enhances access to modern computer vision and artificial intelligence processing to annotate and quantify examinations in a consistent and reproducible manner. The Myasthenia Gravis Core Examination (MG-CE) has been recommended for the telemedicine evaluation of patients with myasthenia gravis. Objective: We aimed to assess the ability to take accurate and robust measurements during the examination, which would allow improvement in workflow efficiency by making the data acquisition and analytics fully automatic and thereby limit the potential for observation bias. Methods: We used Zoom (Zoom Video Communications) videos of patients with myasthenia gravis undergoing the MG-CE. The core examination tests required 2 broad categories of processing. First, computer vision algorithms were used to analyze videos with a focus on eye or body motions. Second, for the assessment of examinations involving vocalization, a different category of signal processing methods was required. In this way, we provide an algorithm toolbox to assist clinicians with the MG-CE. We used a data set of 6 patients recorded during 2 sessions. Results: Digitalization and control of quality of the core examination are advantageous and let the medical examiner concentrate on the patient instead of managing the logistics of the test. This approach showed the possibility of standardized data acquisition during telehealth sessions and provided real-time feedback on the quality of the metrics the medical doctor is assessing. Overall, our new telehealth platform showed submillimeter accuracy for ptosis and eye motion. In addition, the method showed good results in monitoring muscle weakness, demonstrating that continuous analysis is likely superior to pre-exercise and post-exercise subjective assessment. Conclusions: We demonstrated the ability to objectively quantitate the MG-CE. Our results indicate that the MG-CE should be revisited to consider some of the new metrics that our algorithm identified. We provide a proof of concept involving the MG-CE, but the method and tools developed can be applied to many neurological disorders and have great potential to improve clinical care.

Dietary diversity and associated factors among adult cancer patients attending treatment at Black Lion Specialized Hospital, Addis Ababa, Ethiopia.

Background: Cancer has become a significant public health issue around the world and an increasingly important contributor to disease burdens. In countries like Ethiopia with high nutrient demands, people with chronic diseases like cancer are at a high risk of macro and micronutrient deficiencies. Therefore, the present study attempted to assess dietary diversity and associated factors among adult cancer patients attending treatment at Black Lion Specialized Hospital, Addis Ababa, Ethiopia. Method and Materials: Hospital-based cross-sectional study was conducted from 22 April 2021 to 22 May 2021 on 416 adult cancer patients at Black Lion Specialized Hospital (BLSH). A systematic random sampling technique was applied to select study subjects. Quantitative data were collected using a structured, pretested and interviewer-administered questionnaire. The questionnaire comprised the standard dietary diversity measurement tool, which was adopted from the Food and Technical Assistance (FANTA) then data were entered into EPI INFO software and analysed using Statistical Package for the Social Sciences (SPSS) version 25. Frequency, mean and standard deviation were used to describe variables. A binary logistic regression model was fitted to elicit factors associated with the dietary diversity of cancer patients and a P-value of less than 0⋅2 was used as a cut-off for further analysis. Logistic regression analysis with a 95 % confidence interval (CI) was estimated to measure the strength of association at P < 0⋅05. Results: The present study revealed that 61⋅5 % of patients had low dietary diversity. Being from a family size of five and more (AOR = 1⋅48, 95 % CI 1⋅28, 1⋅83), having no permanent income (AOR = 1⋅31, 95 % CI 1⋅15, 1⋅67), alcohol consumption (AOR = 3⋅97, 95 % CI 1⋅20, 13⋅1), not doing regular physical exercise (AOR = 1⋅83, 95 % CI 1⋅07, 3⋅12), lack of nutritional information (AOR = 2⋅23, 95 % CI 1⋅30, 3⋅82), poor nutritional knowledge (AOR = 1⋅84, 95 % CI 1⋅05, 3⋅25) and minimum meal frequency (AOR = 10⋅7, 95 % CI 5⋅04, 22⋅7) were factors associated with inadequate dietary diversity. Conclusion: The present study showed that the majority of cancer patients had low dietary diversity, suggesting that they are highly vulnerable to micronutrient deficiencies. Therefore, efforts should be strengthened to improve patients' income level, access to nutrition information and nutritional knowledge.

Impact of the Covid-19 epidemic on a US sample of patients with myasthenia gravis.

Introduction: The Covid-19 pandemic has devastated the world and demonstrated the inadequacy of health care in the United States. To assess its impact, the Rare Disease Clinical Research Network conducted a survey to assess the pandemic on the rare disease community of patients, including those with myasthenia gravis (MG). Methods: A cross-sectional survey was designed to target people or their care givers who live in the United States, have a rare disease, and are under 90 years of age. Respondents logged onto a dedicated web page and completed the survey online, which requested demographic, disease-specific, drug treatment, and symptom information as well as assessment of Covid-19 impact on them. The survey was open from May 2020 to December 2020. Results: Five hundred ninety-four with self-reported myasthenia gravis completed the survey, which was the largest number of respondents. Sixty percent of respondents were women with a mean age of 60 years. Eighty-nine percent identified as White. Respondents did not appreciate a worsening of symptoms after the pandemic. Only 7 respondents reported the diagnosis of Covid-19 but 11% indicated they had difficulty accessing care at the time of the survey. Discussion and Conclusion: Patients with MG complained of worse access to medical care during the early months of the pandemic, including challenges in diagnosis of suspected Covid-19 infection. A major limitation of the survey is its inability to access minority populations. Nevertheless, the results of the Rare Disease Clinical Research Network (RCDRN) survey of patients with MG provide clear evidence that the pandemic has demonstrated the deficiencies in US healthcare.

Impact of Covid-19 Pandemic on Patients with Myasthenia Gravis Deeper understanding of the consequences of the Covid-19 pandemic on people with rare diseases is critically important in order to enhance health care in the future. The Rare Disease Clinical Research Network (RDCRN) performed a web-based survey of individuals with rare diseases in the first year of the pandemic utilizing questions to assess the impact of the pandemic on their symptoms, access to healthcare, and medication use. Five hundred and ninety-four respondents reported having myasthenia gravis (MG). The average age was 60 years and 60% were women. Nearly ninety percent were White. A large minority indicated difficulty accessing health care and nearly a third used telemedicine. Only seven respondents indicated a diagnosis of Covid-19 but many more had symptoms consistent with infection. Overall, there was no increase in symptoms of MG after the beginning of the pandemic. The pandemic has demonstrated the deficiencies in US healthcare, and these are appreciated in the results of the RCDRN survey of patients with MG. The RDCRN will continue to survey the rare disease community to understand the ongoing impact of the Covid-19 pandemic.