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Principal Investigator: ROBERT E GERSZTEN
Organization: BETH ISRAEL DEACONESS MEDICAL CENTER
Fiscal Year: 2024
Award: $439,554
Funding agency: National Heart Lung and Blood Institute
PROJECT SUMMARY/ABSTRACT
There is mounting concern that patients hospitalized with COVID-19 experience unexpectedly high rates of
cardiac and vascular events. Identifying which patients are at highest risk for COVID-19-related cardiovascular
events and delineating how these events affect short- and long-term outcomes may help support individualized
patient care, illuminate underlying pathophysiologic mechanisms, and accelerate the development of effective
therapies. However, little is known about how multi-dimensional risk factors, including prior medical conditions,
socioeconomic indicators, and circulating levels of biomarkers affect patient outcomes. Building on our
team's expertise in data linkage, prediction modeling, and biomarker discovery, we will create a unique
and powerful linked data resource to characterize the biological, clinical, health system, and
socioeconomic risk factors for the development of cardiovascular sequelae of COVID-19 and examine
their impact on health outcomes. To create this data resource, we have partnered with the American Heart
Association, whose COVID-19 Cardiovascular Disease Registry is actively capturing high-quality, standardized
information on all adults hospitalized with confirmed SARS-CoV-2 infection at >100 U.S. sites spanning 30
states. We will link this registry to comprehensive health care claims, a national socioeconomic deprivation
index, and detailed health care system information. In Aim 1, we will apply traditional and machine learning
approaches to the linked multicenter registry in order to identify the clinical, health system, and socioeconomic
factors that predict in-hospital major adverse cardiovascular events (MACE) among COVID-19 patients. In Aim
2, we will characterize long-term MACE (i.e., at 1 and 2 years after discharge from the index COVID-19
hospitalization) among older adults in a large multicenter registry linked with longitudinal Medicare claims, and
identify the clinical, health system, and socioeconomic factors that predict their occurrence. Based on this
work, we will create clinically implementable risk scores which will estimate, at the time of admission for and
discharge from an index COVID-19 hospitalization, a patient's risk of developing a major cardiovascular event.
In Aim 3, we evaluate the proteomic profiles of a subset of patients in the linked registry with biobanked serial
blood samples, and identify biochemical markers that predict the occurrence of MACE, both during index
hospitalization for COVID-19 and after discharge. This research will advance our collective understanding of
the biological, clinical, and socioeconomic predictors of COVID-19-related cardiovascular morbidity and
mortality. By identifying patients at greatest at risk of cardiovascular events, our work will help frontline
clinicians better individualize clinical management strategies and health systems improve care delivery during
future waves of the pandemic.
Terms: <21+ years old><Acceleration><Address><Admission><Admission activity><Adult><Adult Human><Affect><American Heart Association><Apoplexy><Approaches to prevention><Asystole><Biochemical><Biochemical Markers><Biological><Biological Markers><Blood Clotting><Blood Proteins><Blood Sample><Blood Vessels><Blood coagulation><Blood specimen><Brain Vascular Accident><COVID infected patient><COVID patient><COVID positive patient><COVID-19><COVID-19 infected patient><COVID-19 infection><COVID-19 patient><COVID-19 positive patient><COVID-19 related risk><COVID-19 risk><COVID-19 risk factor><COVID-19 sequelae><COVID-19 virus infection><COVID19 infection><COVID19 patient><COVID19 positive patient><CV-19><Cardiac><Cardiac Arrest><Cardiac infarction><Cardiovascular><Cardiovascular Body System><Cardiovascular Diseases><Cardiovascular Organ System><Cardiovascular system><Cerebral Stroke><Cerebrovascular Apoplexy><Cerebrovascular Stroke><Cessation of life><Characteristics><Clinical><Clinical Management><Communities><Comprehensive Health Care><Comprehensive Healthcare><Coronavirus Infectious Disease 2019><Dangerousness><Data><Data Linkages><Death><Deep Vein Thrombosis><Deep-Venous Thrombosis><Development><Dimensions><Disease><Disorder><Embolism><Embolus><Event><Future><Geography><Health><Health Insurance for Aged and Disabled, Title 18><Health Insurance for Disabled Title 18><Health system><Healthcare><Heart Arrest><Heart Vascular><Heart failure><Hospital Admission><Hospitalization><Hospitals><Institution><Israel><Link><Long-term Follow-up><Longterm Follow-up><Lung><Lung Respiratory System><Machine Learning><Measures><Medical><Medical center><Medicare><Medicare claim><Modeling><Morbidity><Morbidity - disease rate><Myocardial Infarct><Myocardial Infarction><Myocarditis><Outcome><Pathology><Patient Care><Patient Care Delivery><Patient outcome><Patient risk><Patient-Centered Outcomes><Patient-Focused Outcomes><Patients><Precision care><Predicting Risk><Predictive Factor><Prevention approach><Proteins><Proteomics><Record Linkage Study><Registries><Research><Risk><Risk Factors><SARS-CoV-2 infected patient><SARS-CoV-2 infection><SARS-CoV-2 patient><SARS-CoV-2 positive patient><SARS-CoV-2 sequelae><SARS-CoV2 infection><Severe acute respiratory syndrome coronavirus 2 infection><Site><Socioeconomic Factors><Source><Standardization><Stroke><Time><Title 18><Ventricular Arrhythmia><Work><adulthood><bio-markers><biobank><biologic><biologic marker><biomarker><biomarker discovery><biorepository><brain attack><cardiac damage><cardiac failure><cardiac infarct><cardiac inflammation><cardiovascular disorder><cardiovascular risk><cardiovascular risk factor><care delivery><care for patients><care of patients><caring for patients><cerebral vascular accident><cerebrovascular accident><circulatory system><clinical phenotype><clinical predictors><clinical risk><cohort><comprehensive care><computer based prediction><coronary attack><coronary infarct><coronary infarction><coronavirus disease 2019><coronavirus disease 2019 infected patient><coronavirus disease 2019 infection><coronavirus disease 2019 patient><coronavirus disease 2019 positive patient><coronavirus disease 2019 risk><coronavirus disease 2019 risk factor><coronavirus disease infected patient><coronavirus disease patient><coronavirus disease positive patient><coronavirus disease-19><coronavirus disease-19 patient><coronavirus infectious disease-19><coronavirus patient><data resource><deprivation><developmental><disease registry><economic indicator><effective therapy><effective treatment><elderly patient><experience><forecasting risk><health care><health insurance for disabled><healthcare information system><heart attack><heart damage><heart infarct><heart infarction><high risk><improved><indexing><individualized care><individualized management><individualized patient care><individualized patient management><infected with COVID-19><infected with COVID19><infected with SARS-CoV-2><infected with SARS-CoV2><infected with coronavirus disease 2019><infected with severe acute respiratory syndrome coronavirus 2><insight><long-term followup><longterm followup><machine based learning><medical information system><model generalizability><mortality><older adult><older adulthood><older patient><pandemic><pandemic disease><patient infected with COVID><patient infected with COVID-19><patient infected with SARS-CoV-2><patient infected with coronavirus disease><patient infected with coronavirus disease 2019><patient infected with severe acute respiratory syndrome coronavirus 2><patient oriented outcomes><patient subclass><patient subcluster><patient subgroups><patient subpopulations><patient subsets><patient subtypes><patient with COVID><patient with COVID-19><patient with COVID19><patient with SARS-CoV-2><patient with coronavirus disease><patient with coronavirus disease 2019><patient with severe acute respiratory distress syndrome coronavirus 2><personalized care><personalized clinical management><personalized disease management><personalized management><personalized patient care><precision management><predict risk><predict risks><predicted risk><predicted risks><predicting risks><predictive biomarkers><predictive marker><predictive modeling><predictive molecular biomarker><predictive risk><predicts risk><prognostic><pulmonary><risk associated with COVID-19><risk factor associated with COVID-19><risk factor related to COVID-19><risk prediction><risk predictions><risk related to COVID-19><rurality><sequelae following COVID-19><sequelae following SARS-CoV-2 infection><sequelae of COVID-19><severe acute respiratory syndrome coronavirus 2 infected patient><severe acute respiratory syndrome coronavirus 2 patient><severe acute respiratory syndrome coronavirus 2 positive patient><socio-economic><socio-economic factors><socio-economically><socioeconomically><socioeconomics><stroked><strokes><vascular>