N3C CTR DURs

In this project, we aim to study the role of the COVID-19 pandemic on the weight-gain trends in the US. Informed by the existing studies, our hypothesis is that the pandemic had a meaningful adverse impact on the already alarming weight-gain trends. We plan to investigate these trends separately in children and adult populations. While trying to identify such trends at a large scale and on the individual level, we also aim to study the disparities with respect to COVID-19 status, age, gender, race, and social determinant of health (SDOH).

Mathematical models currently used to explain the progression of pandemic-inducing pathogens are wholly deficient at explaining and accurately predicting pandemics with ever-evolving characteristics. The current basic SEIR model (susceptible, exposed, infectious, and recovered) can only account for one wave of infection because it does not account for dynamically changing susceptibility, infectiousness, etc. With this project, we aim to develop a mathematical modeling tool developed from chemical reaction kinetics equations that can better predict the dynamic evolution of the COVID-19 pandemic among others, as well as predict the effect of certain policies on transmission (such as mask mandating, social distancing, vaccination, etc.) This model already shows promise with adult populations, as validated by recursive forward prediction. Using patient data on COVID test type, result, date as well as recovery or death dates, a mathematical model can be built to represent changes in infection over time. Also, using deprivation indices and ZIP code, this model may be able to predict infection at a localized level.

This project will examine anxiety, depression and trauma-related symptoms among children within the N3C Data Enclave. Children may be disproportionately impacted by SARS-CoV-2/COVID-19. We will describe the incidence, timing, and severity of sequelae of anxiety, depression and PTSD symptoms among children diagnosed with SARS-CoV-2 infection, including determining incidence rates across different racial/ethnic groups and urban and rural populations. This analysis will assist us in developing risk prediction models for identifying children who are at-risk for recurring and/or persistent mental health symptoms as a result of the pandemic.

As SARS-CoV2 is a novel pathogen and is only now becoming well characterized and understood, there has yet been insufficient data to predict long-term post-acute sequelae of the virus. Acute respiratory complications occasionally leading to mortality has been successfully identified, but long-term complications are not yet understood. Preliminary studies show cognitive complications, among others, in those who contracted COVID-19 which can persist beyond the acute contraction of the virus. In this study, we seek to use N3C medical record data to identify long-term effects of SARS-CoV2 in the population by comparing diagnosis rates in the population that has contracted the virus to the population that has not. Limited data is requested for this project to associate positive SARS-CoV2 tests to diagnoses rates with importance to difference in time between the two events.

SARS-CoV2 infection has been linked to either acute myocardial involvement or myocarditis or a delayed\nmultisystem inflammatory syndrome in children (MIS-C), a potentially serious condition affecting multiple organs\nincluding cardiac and vascular tissues. Myocarditis secondary to SARS-CoV2 may go unrecognized and present\nlate with nonspecific symptoms of fatigue and chest pain. Observations mad e early during the COVID-19\npandemic, stemming from patients hospitalized with COVID-19, suggest that a considerable (25- 80%)\npercentage manifest clinically-relevant myocardial involvement, as evidenced by elevated cardiac troponin and\nthe appearance of regional functional abnormalities and scarring noted on noninvasive imaging. 1The long-term\ncardiovascular effects of unrecognized myocarditis and MIS-C across this range are not well understood, and at\npresent, there is no widely accepted definition of what constitutes clinically relevant myocardial injury secondary\nto SARS-CoV2 infection. A better understanding of the long-term sequelae of recognized and unrecognized\ncardiac involvement in the pandemic is critically needed. Our team seeks to address these knowledge gaps and\nprovide a framework for better understanding and predicting the effects of infectious and inflammatory conditions\non cardiac performance. In this pilot study, we focus on the risk to children and youth of returning to athletic\nparticipation after SARS-CoV2 exposure

Coronavirus disease 2019 (COVID-19) is characterized by a male predominance in severity and mortality worldwide, but reasons underlying the sex-bias are unclear. Sex differences in comorbidities, sex hormones, and inflammatory biomarkers may all be factors involved in the sex differences of COVID-19 outcomes. However, few studies examined the role of these factors in COVID-19 outcomes stratified b y sex. In our recent study in a COVID cohort of adults in Louisiana, we observed sex differences in comorbidities and biomarkers as predictors of COVID-19 severe outcomes. Our study underscores the need for a larger study with sex-stratification and robust analysis to determine if our findings are region-specific or hold generalizability to other populations. We propose to use the rich and population-based National COVID Cohort Collaborative (N3C) data to examine to what extent comorbidities, female sex hormones, and inflammatory biomarkers represent sex-specific determinants of COVID-19 outcomes.

This project aims to use collaborative filtering to analyze the effects of various drugs on COVID patients? suffering from clinical depression over time and whether these effects are different for patients without COVID. These will then be compared to estimations using logistic regression, content-based filtering, and machine learning. Unlike aforementioned methods, the collaborative filtering a spect of this project will not involve covariates, but rather look for recommendations solely on patient outcomes. Through the process of serendipity, these can identify preferences and similarities that may be missed by analysis of covariates. As we will not have data on patients? approval of the effectiveness of medications, we will estimate these outcomes by the change in depression severity over time, and form a similarity matrix identifying similar users based on similar drug regimens. If similar users share positive outcomes of 3 different medications, but some users with positive results also takes a 4th medication, that can be seen as a recommendation. This will be used on test data to evaluate the accuracy of predictions. This can be compared to the results of logistic regression and other methods.

The project will investigate if background therapy with oral anticoagulants for history of AF, VTE/PE, mechanical heart valve, or CVA is associated with outcome among patients hospitalized for COVID-19 disease.

Previous studies and meta-analyses demonstrate an adjusted association between RAAS inhibitor background therapy and lower risk of mortality among patients hospitalized for COVID-19 disease. Using a propensity score matched analysis, we will examine the consistency of this association across angiotensin converting enzyme inhibitors, angiotensin receptor blockers, and mineralocorticoid receptor an tagonists. Cohorts will be stratified by several baseline comorbidities and other medications.

Our previous work has examined individual and area-level risk factors for breakthrough SARS-CoV-2 infection in the fully vaccinated using parametric statistical models. We plan to evaluate whether a ML/DL model can improve prediction of breakthrough infection risk. This may be useful in guiding the selection and timing of booster doses as well as other prevention efforts in individuals with feature groups associated with increased risk for symptomatic breakthrough infection.

The SARS-CoV-2 enters the human gastrointestinal tract via the ACE-2 receptors which are predominantly expressed within the gastrointestinal tract, from gastric to colonic tissue. The pathophysiology of the SARS-CoV-2 infection on the gastrointestinal tract is commonly manifested as anorexia, nausea, vomiting, and diarrhea in COVID-19 patients. These clinical manifestations usually (have been repo rted to) occur in combination with respiratory symptoms in 50% of the affected patients and independently without respiratory symptoms in 10% of patients. Patients also present with abnormalities of pancreatic and hepatic enzymes. Whether COVID presentation including gastrointestinal symptoms portends worse outcomes remains poorly undefined. The project will examine whether COVID clinical presentation with gastrointestinal symptoms is associated with ICU length of stay, total length of hospitalization, and inpatient survival. The relationship between gastrointestinal symptoms at clinical presentation and other known or candidate risk factors for severity of illness and poor outcomes such as obesity, diabetes mellitus, and hypertension will also be examined.

A single center analysis suggests a variety of GI symptoms at and during hospitalization for C19 are associated with worse C19 outcomes adjusted for other organ system symptoms and findings. These associations will be evaluated in the larger N3C experience.

This project will compare comorbidity rates across both the COVID-19 negative and COVID-19 positive patients in N3C. The utility\nof this analysis is to determine if comorbidity incidence, which will facilitate more trips to the hospital for routine care and condition management, is indicative of a higher or lower incidence of COVID-19 in the N3C population. Preliminary evidence suggests that pati ents with comorbidities, particularly those with immunosuppressive and/or low survival over 10 years, may have a lower incidence of COVID-19 due to better adherence to social distancing practices.

Malnutrition is a global health crisis that effects up to one out of two older adults and results in an estimated annual cost of $51.3 billion per year in the United States. Malnutrition is linked to weaker immune systems, reduced cardiac output, poor diaphragmatic and respiratory muscle function and impaired gastrointestinal function. Early studies have explored the prevalence and severity of malnutrition in COVID-19 patients. However, small sample sizes and single-site studies limit the generalizability of results. Currently, a gap in knowledge exists regarding the relationship of malnutrition in hospital admissions in COVID-19 patients and the impact of malnutrition on clinical outcomes.

With the progress of COVID pandemic, reoccurrence of COVID cases have been reported not only among people without symptoms or with mild symptoms, but also have occurred with patients who have been hospitalized, recovered with two consecutive negative tests and then infected again with severe symptoms. Understanding the mechanism behind the reoccurrence of COVID and the severity of the disease related to it is important for fighting COVID in the long term. We will develop novel competing risk models and machine learning algorithms to understand this question.

The purpose of this study is to define incidence of GI bleeding in Covid-19 positive adults seen in the ED or admitted to the hospital at sites participating in the N3C. Further, we plan to characterize outcomes in these patients (length of stay, mortality, readmission, etc) as well as factors that may predispose to GI bleeding (use of anti-platelet medications, anticoagulants, age, comorbidities).

Deaths by suicide are a leading cause of adolescent and young adult deaths nationally; presentations to the emergency room for suicidal ideation or attempts at self- harm through ingestions or other means are common. This project will expand existing research conducted at OU Health Sciences Center, where it was found that there has been a large increase since the beginning of the COVID-19 pandemic. We will review records for patients aged 4 years or older with diagnoses associated with suicide attempt or self harm and attempt to identify trends in overall rates within the context of pre-existing patterns, with special attention paid in the period of time after March 2020. Age-dependent suicide attempt time-to-event tables will be constructed and compared over pre and post-pandemic eras.

Pulmonary vasodilators offer several potential benefits to patients with refractory hypoxemia in the setting of severe acute respiratory distress syndrome (ARDS), including improved ventilation-perfusion mismatch, oxygenation, pulmonary pressures and right ventricular function.1 While randomized trials of inhaled nitric oxide, a pulmonary vasodilator often used in the acute setting, in patients with ARDS have not demonstrated a significant mortality benefit, the efficacy of newer pulmonary vasodilators in patients with ARDS is unclear as studies are lacking.2-5 Pulmonary vasodilators are nevertheless used as adjunctive therapies to rescue patients with refractory hypoxemia in the setting of severe ARDS, and have been used to treat patients with severe COVID-19 associated ARDS.6-9 However, effects on mortality, oxygenation, length of ICU stay or mechanical ventilation, use of vasopressors, and side effects are not known. The practice patterns of pulmonary vasodilator use in patients with severe COVID-19 are limited to single-center studies. We aim to describe the use of pulmonary vasodilators in patients hospitalized with severe COVID-19 within the multicenter National COVID Cohort Collaborative (N3C), and investigate the efficacy of pulmonary vasodilator therapy in patients with severe COVID-19.

The SARS-CoV-2 pandemic has been marked by severe acute respiratory distress syndrome (ARDS) in approximately 20% of patients.1 A number will require end-organ support with extracorporeal membrane oxygenation (ECMO).2,3 To-date over 15,000 patients with COVID-19 treated with ECMO have been reported to the Extracorporeal Life Support Organization. Hemorrhage and thrombosis are the most significant causes of morbidity and mortality during ECMO.4 Half of patients will suffer major hemorrhage and approximately 12% will have major thrombotic complications.5 Stroke and intracerebral hemorrhage are the most morbid of these complications and are the leading cause of death during ECMO.6 Patients with severe COVID-19 can develop a hypercoagulable state with an increased risk of thrombotic complications.7-10 Thus, patients with severe COVID-19 associated ARDS treated with ECMO may inherently have a higher risk of complications because of the hypercoagulable COVID-19 phenotype.11,12\n\nWe aim to describe the use of ECMO in patients hospitalized with severe COVID-19 associated ARDS within the multi-center National COVID Cohort Collaborative (N3C), and compare the rate of hemorrhagic and thrombotic complications in patients with and without COVID-19 treated with ECMO.

Background: Children are at risk for severe SARS-Cov-2 infection. Epidemiology of SARS-COVID-19 in children is evolving and poorly characterized. There is paucity of literature regarding outcomes and predictive factors of hospitalized children. Projections indicate that incidence of COVID-19 may persist for several months. Clinical characteristics and outcomes of hospitalized children will be help ful for future resource utilization. \nObjectives:\nTo study the characteristics and outcomes of children presenting with COVID-19 using a large multi-institutional dataset and a validated identification method. To study the factors predictive of adverse outcomes in hospitalized children

We will isolate I COVID-19 patients (at least age of 18 years) using ICD 10 codes and then divided into four groups: (1) patients with cancer, (2) patients with heart failure (3) patients with both cancer and heart failure and (4) Control (patients without cancer or heart failure). The patient is full received chemotherapy within six months of COVID-19 diagnosis will be included in the cancer group. The patient is with chronic systolic or diastolic heart failure will be considered in the Cardiac group

The purpose of this request is to establish a group of experts who will examine the N3C data in terms of COVID’s impact on individuals (of all ages) who have at least one disability. Disability types would include: intellectual, developmental, vision impairment, deaf or hard of hearing, mental health conditions, acquired brain injury, and mobility/physical disabilities. We anticipate disparities between individuals based on ability differences in terms of the prevalence of COVID, symptomology, and service utilization. Individuals with disabilities and their families have documented challenges to care and an increased vulnerability to infections and complications due to their disability and other medical conditions. With more than 35% of the nation’s population reporting at least one disability, it is important to examine the impact of COVID-19 across the lifespan. Information garnered from this effort would potentially provide opportunities for public health, infectious disease, and other approaches.

There are no clear data on the best treatments for COVID-19 to minimize mortality in various populations. As an example, an NIH randomized clinical trial concluded that remdesivir was superior to placebo among hospitalized patients, significantly shortening time to recovery (10 vs. 15 days).1 Though mortality was significantly lower in the remdesivir group at day 15 (6.7% vs. 11.9%), mortality at day 29 trended lower (11.4% vs. 15.2%) but did not reach statistical significance. In contrast, a recent World Health Organization guidelines panel recommended against remdesivir use citing that there is currently no evidence that it improves survival. The WHO guideline was based on analysis of four clinical trials conducted among 7000 patients.2 This project utilizing the N3C database seeks to evaluate what therapies are associated with the lowest mortality among various populations.

After Covid diagnosis, there are changes to the pro-inflammatory/pro-thrombotic state. In elective joint replacement surgery, this inflammation/thrombosis could lead to increased postoperative risks. Will be utilizing data to understand the safest timing for elective surgery following Covid infection and complication rates compared to cohorts.

The effect of severe COVID-19 infection in pregnancy is limited to a small number of case reports. The use of extracorporeal membrane oxygenation (ECMO) in pregnancy is rare, typically reserved for salvage therapy in acute respiratory distress syndrome (ARDS). Specifically, veno-venous ECMO (V-V ECMO) may be used for refractory hypoxemia in patients who cannot be safely supported with conventional mechanical ventilation. The use of ECMO for COVID-19 infection in pregnancy has not yet been reported in a large series as individual institutions only have few cases. This limits the information available for analysis. We seek to investigate the maternal and neonatal outcomes of ECMO use in pregnancy-associated COVID-19 infection in a large national cohort.

The prevalence of obesity is rising in the United States. Excess adipose tissue causes difficulty in managing severe illness secondary to changes in anatomic and physiological properties. Changes in respiratory mechanics can make the mechanical ventilation of a person with obesity more challenging. The use of extracorporeal membrane oxygenation (ECMO) has been shown to be safe in people affected by obesity. Unfortunately, obesity is a risk factor for poor outcomes with COVID-19 complicated by ARDS. It is unknown whether outcomes in patients with obesity may have improved outcomes on ECMO therapy. We seek to evaluate the outcomes of patients that are obese versus non-obese with life-threatening COVID-19 illness treated by ECMO therapy.

Aim of this project is to study individuals with cardiovascular diseases who have taken covid-19 vaccine. Patients with cardiovascular diseases are demonstrated strong risk factors for COVID-19. However, there is little if any analysis after vaccination for high risk group of patients. Analysis steps that were planned contains: studying characteristics of this patients infected by SARS-CoV2, and studying/explain their outcomes.

Diagnosis of Severe Acute Respiratory Syndrome coronavirus 2, SARS-Cov-2, has spread into a world-wide pandemic at an unprecedented rate. Little is known concerning adverse events of a covid-19 diagnosis. With increased clotting factors, thrombotic events may be more likely. The interaction of SARS-Cov-2 and prescription birth control are unknown. However, hormonal birth control can cause thrombos is in high risk patients. (5) With the introduction of Covid-19 into this population, can we accurately determine an increase in thrombotic events? \n\nThrombotic events leading to pulmonary embolism have been reported in 31% of patients in an ICU with a Covid-19 diagnosis. (1) Patients entering the ICU with a Covid-19 diagnosis usually have comorbid conditions. The health of the population in an ICU differs from that of a non-hospitalized population. However, if thrombotic events are occurring at a higher rate in this population, pregnancy outcomes may be effected. Covid-19 infection increases systemic inflammation with high levels of C-Reactive protein and ferritin. (2) Inflammation in the body can lead to a clotting event; thus, the thrombotic events in women of reproductive age can jeopardize the viability of pregnancy. \n\nLimited data is available of Covid-19 as a causal effect of miscarriages. However, multiple letters to the editors have outlined suspicion of covid-19 infection contributing to miscarriage. Hachem et. al. found a late term miscarriage in a women who presented with vaginal bleeding and otherwise healthy pregnancy. The woman had a RT-PCR positive Covid-19 Result, and increased WBC levels and c- reactive protein. (3) Similarly, a first trimester miscarriage was reported in a woman who was diagnosed with Covid-19 at 10 weeks after substantial exposure. (4) \n\nKlok, F. A., Kruip, M. J. H. A., Van der Meer, N. J. M., Arbous, M. S., Gommers, D. A. M. P. J., Kant, K. M., … & Endeman, H. (2020). Incidence of thrombotic complications in critically ill ICU patients with COVID-19. Thrombosis research, 191, 145-147.\nBoggess, K. A., Lieff, S., Murtha, A. P., Moss, K., Jared, H., Beck, J., & Offenbacher, S. (2005). Maternal serum C-reactive protein concentration early in pregnancy and subsequent pregnancy loss. American journal of perinatology, 22(06), 299-304.\nHachem, R., Markou, G. A., Veluppillai, C., & Poncelet, C. (2020). Late miscarriage as a presenting manifestation of COVID-19. European Journal of Obstetrics and Gynecology and Reproductive Biology, 252, 614.\nWong, T. C., Lee, Z. Y., Sia, T. L., Chang, A. K., & Chua, H. H. (2020). Miscarriage risk in COVID-19 infection. SN Comprehensive Clinical Medicine, 2(9), 1449-1452.\nGray, B., Floyd, S., & James, A. H. (2018). Contraceptive management for women who are at high risk of thrombosis. Clinical obstetrics and gynecology, 61(2), 243-249

Patients who have acquired coronavirus disease 2019 (COVID-19) have displayed numerous cardiovascular complications during the course of their infection, where these complications have included acute myocardial injury, ischemic heart disease, heart failure, stroke, and arrhythmias. While these manifestations are responsible for several complications during the course of the disease, numerous patients have reported continued cardiovascular abnormalities following their recovery. Our study will use the data present in the N3C Enclave to investigate the pharmacological management of patients prior to and post COVID19 exposure to determine whether there is an association between COVID-19 and an increased incidence or progression of different cardiovascular diseases that required increased or additional pharmacological management

The COVID-19 pandemic has caused significant economic impact. However, regional, pre-COVID 19 pandemic economic conditions related outcomes are unknown. The purpose of is study is to look at how regional economic conditions played a role in COVID-19 related outcomes.

Abstract – SARS-CoV-2 infection, primarily a disorder of the vascular endothelium, results in intravascular thrombosis and a generalized inflammatory response. While the most common and lethal manifestation of SARS-CoV-2 is acute hypoxemic respiratory failure, the occurrence of intracranial thrombosis resulting in stroke in young patients not otherwise at high risk has been reported. Additionally, the generalized inflammatory response seen is likely present in the brain as well. The consequences of neuroinflammation on neurotransmitter pathways and cognitive function are complex and may have implications for psychiatric disease onset or progression. Finally, the Long-Covid syndrome is associated with various cognitive disturbances such as impaired memory and concentration. These observations suggest a direct or indirect impact on neurophysiology that could manifest in differences in prevalence or progression of various psychiatric conditions following SARS-CoV-2 infection. This study will seek to explore prevalence of psychiatric diagnoses in patients testing positive for SARS-CoV-2 compared to a matched cohort of Covid negative patients using proportional hazards modeling. From the resulting relative risk and odds ratios, machine learning techniques will be used to develop a predictive model of future psychiatric sequalae of SARS-CoV-2 infection.

This project uses de-identified person level demographic and COVID-19 (i.e. testing and vaccination) related data gathered from five West Virginia health care systems and the National COVID Cohort Collaborative (N3C) to inform targeted West Virginia health systems in efforts to improve care and outreach for vulnerable populations including those who are racial and ethnic minorities, have underlying medical conditions (such as diabetes, heart disease, cancer, etc.), are 65+, and those with social determinants of health that put them at increased risk for contracting COVID-19 (i.e. low-income, limited access to healthcare).