The characteristics of patients with coronavirus disease 2019 (COVID-19) have primarily been described in hospitalized adults. Characterization of COVID-19 in ambulatory care is needed for a better understanding of its evolving epidemiology. Our aim is to provide a description of the demographics, comorbidities, clinical presentation, and social factors in confirmed SARS-CoV-2-positive non-hospitalized adults. We conducted a retrospective medical record review of 208 confirmed SARS-CoV-2-positive patients treated in a COVID-19 virtual outpatient management clinic established in an academic health system in Georgia. The mean age was 47.8 (range 21–88) and 69.2% were female. By race/ethnicity, 49.5% were non-Hispanic African American, 25.5% other/unknown, 22.6% non-Hispanic white, and 2.4% Hispanic. Nearly 70% had at least one preexisting medical condition. The most common presenting symptoms were cough (75.5%), loss of smell or taste (63%), headache (62%), and body aches (54.3%). Physician or advanced practice provider assessed symptom severity ranged from 51.9% mild, 30.3% moderate, and 1.4% severe. Only eight reported limitations to home care (3.8%), 55.3% had a caregiver available, and 93.3% reported initiating self-isolation. Care needs were met for 83.2%. Our results suggest the demographic and clinical characteristics of COVID-19 illness in non-hospitalized adults differ considerably from hospitalized patients and warrant greater awareness of risk among younger and healthier individuals and consideration of testing and recommending self-isolation for a wider spectrum of clinical symptoms by clinicians. Social factors may also influence the efficacy of preventive strategies and allocation of resources toward the SARS-CoV-2 pandemic.

Understanding the relationships between health and aging is essential for delaying morbidity and maximizing independence in aging populations as life expectancies increase. Loss of cognitive function is a feared age-associated condition and growing public health concern. Alzheimer’s disease (AD), the most common cause of dementia, has no curative therapies. Characterizing the relationships between risk factors, biomarkers, and AD progression is critical for the development of effective disease prediction, clinical intervention, and ultimately, disease prevention. The Emory Healthy Aging Study (EHAS) and the Emory Healthy Brain Study (EHBS), which is nested within EHAS, aim to further the understanding of healthy aging and the pathogenesis of age-related illnesses in well-characterized, community-based prospective cohorts and to identify biomarkers for the earliest manifestations of AD for the facilitation of preventative interventions. The EHAS is an innovative, longitudinal, web-based study enrolling English-speaking adults in the U.S. who agree to be contacted for future studies. Using validated instruments, the annual questionnaire enquires about demographics, socioeconomics, self-reported cognitive function, personal and family medical history, lifestyle, and psychosocial factors. Cognitive assessments are also obtained using an ambulatory device. Nested within EHAS, the EHBS is enrolling up to 2,500 EHAS participants, 50–75 years old, who do not have a diagnosis of AD, mild cognitive impairment, or any other memory disorder. EHBS in-person, biennial study visits, include neuropsychological testing, cardiovascular measures, retinal and brain imaging, biospecimen collection (blood, cerebrospinal fluid, gut microbiome), and other assessments. Since spring 2016, EHAS and EHBS have enrolled 12,500 and 863 participants with completed baseline assessments, respectively. Data and biospecimens from EHBS participants will support a broad range of AD biomarker discovery efforts, and follow-up of EHAS participants will enable assessment of self-reported cognitive trajectories and accumulation of incident cases of a variety of health conditions. The EHAS design supports the interval deployment of new study instruments and targeted sampling for ancillary studies. This project will increase our knowledge about healthy aging, improve our understanding of risk factors for cognitive impairment and dementias, support development of biomarkers, and facilitate studies of age-associated disorders including AD.

Renal cell carcinoma (RCC) is diagnosed through expensive cross-sectional imaging, frequently followed by renal mass biopsy, which is not only invasive but also prone to sampling errors. Hence, there is a critical need for a noninvasive diagnostic assay. RCC exhibits altered cellular metabolism combined with the close proximity of the tumor(s) to the urine in the kidney, suggesting that urine metabolomic profiling is an excellent choice for assay development. Here, we acquired liquid chromatography− mass spectrometry (LC−MS) and nuclear magnetic resonance (NMR) data followed by the use of machine learning (ML) to discover candidate metabolomic panels for RCC. The study cohort consisted of 105 RCC patients and 179 controls separated into two subcohorts: the model cohort and the test cohort. Univariate, wrapper, and embedded methods were used to select discriminatory features using the model cohort. Three ML techniques, each with different induction biases, were used for training and hyperparameter tuning. Assessment of RCC status prediction was evaluated using the test cohort with the selected biomarkers and the optimally tuned ML algorithms. A seven-metabolite panel predicted RCC in the test cohort with 88% accuracy, 94% sensitivity, 85% specificity, and 0.98 AUC. Metabolomics Workbench Study IDs are ST001705 and ST001706.

Global initiatives such as the Millennium Development Goals have led to major improvements in the health of women and children, and significant reductions in childhood mortality. Worldwide, maternal mortality has decreased by 45% and under-five mortality has fallen by over 50% over the past two decades [1]. However, improvements have not been achieved evenly across all ages; since 1990, under-five mortality has declined by ∼5% annually, but the average decrease in neonatal mortality is only ∼3% per year. Against this background, the Bill and Melinda Gates Foundation (BMGF) convened a meeting in Berlin on January 29-30, 2015 of global health stakeholders, representing funders, academia, regulatory agencies, non-governmental organizations, vaccine manufacturers, and Ministries of Health from Africa and Asia. The topic of discussion was the potential of maternal immunization (MI) to achieve further improvements in under-five morbidity and mortality rates in children, and particularly neonates and young infants, through targeting infectious diseases that are not preventable by other interventions in these age groups. The meeting focused on effective and appropriately priced MI vaccines against influenza, pertussis, and tetanus, as well as against respiratory syncytial virus, and the group B Streptococcus, for which no licensed vaccines currently exist. The primary goals of the BMGF 2015 convening were to bring together the global stakeholders in vaccine development, policy and delivery together with the Maternal, Newborn and Child Health (MNCH) community, to get recognition that MI is a strategy shared between these groups and so encourage increased collaboration, and obtain alignment on the next steps toward achieving a significant health impact through implementation of a MI program.

No abstract