The Yale Department of Medicine COVID-19 Data Explorer and Repository (DOM-CovX): An Innovative Approach to Promoting Collaborative Scholarship During a Pandemic

BackgroundThe COVID-19 pandemic has led to an explosion of research publications spanning epidemiology, basic and clinical science. While a digital revolution has allowed for open access to large datasets enabling real-time tracking of the epidemic, detailed, locally-specific clinical data has been less readily accessible to a broad range of academic faculty and their trainees. This perpetuates the separation of the primary missions of clinically-focused and primary research faculty resulting in lost opportunities for improved understanding of the local epidemic; expansion of the scope of scholarship; limitation of the diversity of the research pool; lack of creation of initiatives for growth and dissemination of research skills needed for the training of the next generation of clinicians and faculty. ObjectivesCreate a common, easily accessible and up-to-date database that would promote access to local COVID-19 clinical data, thereby increasing efficiency, streamlining and democratizing the research enterprise. By providing a robust dataset, a broad range of researchers (faculty, trainees) and clinicians are encouraged to explore and collaborate on novel clinically relevant research questions. MethodsWe constructed a research platform called the Yale Department of Medicine COVID-19 Explorer and Repository (DOM-CovX), to house cleaned, highly granular, de-identified, continually-updated data from over 7,000 patients hospitalized with COVID-19 (1/2020-present) across the Yale New Haven Health System. This included a front-end user interface for simple data visualization of aggregate data and more detailed clinical datasets for researchers after a review board process. The goal is to promote access to local COVID-19 clinical data, thereby increasing efficiency, streamlining and democratizing the research enterprise. Expected OutcomesO_LIAccelerate generation of new knowledge and increase scholarly productivity with particular local relevance C_LIO_LIImprove the institutional academic climate by: O_LIBroadening research scope C_LIO_LIExpanding research capability to more diverse group of stakeholders including clinical and research-based faculty and trainees C_LIO_LIEnhancing interdepartmental collaborations C_LI C_LI ConclusionsThe DOM-CovX Data Explorer and Repository have great potential to increase academic productivity. By providing an accessible tool for simple data analysis and access to a consistently updated, standardized and large-scale dataset, it overcomes barriers for a wide variety of researchers. Beyond academic productivity, this innovative approach represents an opportunity to improve the institutional climate by fostering collaboration, diversity of scholarly pursuits and expanding medical education. It provides a novel approach that can be expanded to other diseases beyond COVID 19.

Peripheral Artery Disease and COVID-19 Outcomes: Insights from the Yale DOM-CovX Registry

BackgroundBoth COVID-19 infection and peripheral arterial disease (PAD) cause hypercoagulability in patients, and it remains unknown whether PAD predisposes patients to experience worse outcomes when infected with SARS-CoV-2. MethodsThe Yale DOM-CovX Registry consecutively enrolled inpatients for SARS-CoV-2 between March 1, 2020, and November 10, 2020. Adjusted logistic regression models examined associations between PAD and mortality, stroke, myocardial infarction (MI), and major adverse cardiovascular events (MACE, all endpoints combined). ResultsOf the 3,830 patients were admitted with SARS-CoV-2, 50.5% were female, mean age was 63.1 {+/-}18.4 years, 50.7% were minority race, and 18.3% (n = 693) had PAD. PAD was independently associated with increased mortality (OR=1.45, 95% CI 1.11-1.88) and MACE (OR=1.48, 95% CI 1.16-1.87). PAD was not independently associated with stroke (p=0.06) and MI (p=0.22). ConclusionPatients with PAD have a >40% odds of mortality and MACE when admitted with a SARS-CoV-2, independent of known risk factors.

A neutrophil activation signature predicts critical illness and mortality in COVID-19

Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of over 3,300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, HGF, IL-8, and G-CSF, as the strongest predictors of critical illness. Neutrophil activation was present on the first day of hospitalization in patients who would only later require transfer to the intensive care unit, thus preceding the onset of critical illness and predicting increased mortality. In the health system database, early elevations in developing and mature neutrophil counts also predicted higher mortality rates. Altogether, we define an essential role for neutrophil activation in the pathogenesis of severe COVID-19 and identify molecular neutrophil markers that distinguish patients at risk of future clinical decompensation.