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Principal Investigator: Kelly Cho
Organization: VETERANS HEALTH ADMINISTRATION
Fiscal Year: 2024
Funding agency: Veterans Affairs
The objective of this project is to utilize a longitudinal, VA national cardiovascular disease virtual cohort
to investigate traditional, and [new] risk factors (RFs), for Heart Failure (HF), Atrial Fibrillation (AF), and stroke
among United States Veterans ≥ 65. This cohort will consist of contemporary and comprehensive electronic
health record (EHR) data and will include continued curation and validation of complex phenotypes using
innovative analytics. [The specific aims of this research in older Veterans are to: 1) Assess determinants of HF
risk and prognosis after HF diagnosis in a VA Healthcare facility, 2), Assess determinants of AF risk and
prognosis and 3) Assess determinants of Stroke risk and prognosis.]
[During the previous funding cycle, we leveraged the VA’s large scale national longitudinal EHR data,
linked to additional data sources including the Centers for Medicare and Medicaid Services (CMS) and the
National Death Index (NDI) to create a comprehensive cardiovascular database. Data curation for traditional
RFs, ASCVD preventive therapies, and several ASCVD outcomes was also completed in the previous funding
cycle. Our new proposal will include continued data curation to include novel RFs, such as red cell indices,
white blood cell indices, obstructive sleep apnea, frailty, alcohol intake, aortic stenosis, medication use, lifestyle
factors, and blood measures [estimated glomerular filtration rate (eGFR), serum albumin]. We will achieve this
by employing high-throughput probabilistic phenotyping and multimodal and network data modeling. Outcomes
and risk factors will be evaluated over time where appropriate.]
Electronic health record (EHR) data will be used to identify a baseline index date for Veterans based on
an outpatient VAMC visit at which time the Veteran had blood assayed for traditional lipids. Information from
the baseline and follow up visits will be obtained with database programming and will include: age, sex, systolic
BP, diabetes status, cholesterol, HDL-C, TG, and CVD preventive medications. Filtering algorithms will be
used for laboratory measures across the different hospital laboratories, as has already been undertaken by this
research team. Similarly, BMI, glucose and hemoglobin A1c (HbA1c) measurements, and vascular disease
ICD-9/10 codes will be added.
[Incidence and prognosis of HF, AF, and stroke will assess the role of established and novel risk
profiles. Outcomes to be analyzed include myocardial infarction, stroke, cardiovascular mortality, and all-cause
mortality. For HF we will also examine HF hospital admissions and HF re-admissions within 30 days of
diagnosis. We will compare currently published algorithms for the three conditions where appropriate and
compare the results to our own developed regression models that include novel RFs using mediation analyses
and reclassification strategies where appropriate. We will also report county- specific mapping of outcomes.]
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Financing Administration><Health Facilities><Health care facility><Healthcare Facility><Heart><Heart Diseases><Heart Vascular><Heart failure><Heavy Lipoproteins><Hemoglobin><Hemoglobin A(1)><High Density Lipoprotein Cholesterol><High Density Lipoproteins><High density lipoprotein><Hispanic Populations><Hispanic group><Hispanic individual><Hispanic people><Hispanics><Hospital Admission><Hospitalization><ICD-9><Incidence><Insurance><Investigation><Investigators><Ketosis-Resistant Diabetes Mellitus><LDL Cholesterol><LDL Cholesterol Lipoproteins><Laboratories><Length of Stay><Leukocyte Count><Leukocyte Number><Leukocytes><Leukocytes Reticuloendothelial System><Link><Lipids><Low Density Lipoprotein Cholesterol><Maps><Marrow leukocyte><Maturity-Onset Diabetes Mellitus><Measurement><Measures><Mediation><Medical><Medication><Modeling><Modernization><Myocardial Infarct><Myocardial Infarction><NIDDM><Negotiating><Negotiation><Non-Insulin Dependent Diabetes><Non-Insulin-Dependent Diabetes 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for stroke><risk of stroke><risk prediction><risk predictions><sex><social role><stroke risk><stroked><strokes><suburb><suburban><suburbia><type 2 DM><type II DM><type two diabetes><validations><vascular><vascular dysfunction><vasculopathy><venous thromboembolism><virtual><white blood cell><white blood corpuscle><≥65 years>