Long-term Cardiometabolic Disease in COVID-19

Background: People with COVID-19 have increased risk of death and cardiometabolic disease including cardiovascular disease, diabetes mellitus, dyslipidemia and kidney disease. However, the evidence base is limited in 3 key aspects: (1) Existing studies have characterized the risks of adverse outcomes associated with earlier variants of SARS-CoV-2 and have limited follow-up. (2) It is not clear whether an annual vaccination for COVID-19 beyond the third dose reduces risk of adverse events. (3) Comparative analyses of COVID-19 vs. influenza are helpful to benchmarking risks but are only available for earlier variants and for limited follow up. Significance/Impact: Our proposal aims to answer key questions that are critical to guiding public health policy – including 1) characterizing short- and long-term risks of old, new and yet to emerge variants and subvariants of SARS-CoV-2 (proxied by the era in which they predominate); 2) on an ongoing annual basis, evaluate the effectiveness of COVID-19 vaccines in reducing risks of adverse health outcomes; and 3) on an ongoing basis, provide a comparative assessment of COVID-19 vs seasonal influenza. The proposal is specifically designed to address several key research questions outlined in the US Government National Research Action Plan on Long Covid. The results will have direct and substantial real-world impact in informing policy and clinical care. Innovation: The proposal leverages the unique power of the VA’s large-scale electronic health records and recent methodologic innovations in causal inference and clinical epidemiology to expand the evidence base about the health effects of COVID-19 and the role of vaccines. Specific Aims: To use healthcare data from the VA to: (1) characterize the acute and long-term risks of death and cardiometabolic disease in people with COVID-19 from 2020-2029, cohorted into variant-predominant eras, versus a matched historical control; (2) evaluate the effectiveness of receipt of the COVID-19 vaccine in each year (from 2022-2029) in reducing risk adverse health outcomes in the 12 months after receipt of the vaccine; and (3) comparatively evaluate the acute and long-term risks of death and cardiometabolic disease in people hospitalized for COVID-19, cohorted into variant-predominant eras, versus those hospitalized for seasonal influenza in each influenza season (from 2020 to 2029). Methodologies: VA electronic health record data will be used to construct independent cohorts for each aim and outcome being examined. COVID-19 test results and vaccination data will be collected form the COVID-19 Shared Data Resource, VA laboratory data and Medicare data. Incident outcome definitions validated for use with EHR data will be used. Inverse probability weighing will be used to balance for individual-level patient characteristics (predefined and algorithmically selected covariates), contextual characteristics, and characteristics related to the pandemic. Censoring weights will additionally be used to address situations that may result in informative loss to follow- up. Survival and mixed effect regression models will then be used to estimate differences in risk of outcomes between the COVID-19 exposure group of interest and reference groups, and estimates will be reported as hazard ratios and adjusted incidence rates, or differences in slopes. Implementation/Next Steps: Results from this proposal will inform public health policies (e.g. vaccine policies) and clinical care. Future studies will investigate optimizing care of people with cardiometabolic disease. Project Number: 1I01CX002988-01 | Fiscal Year: 2025 | NIH Institute/Center: Veterans Affairs (VA) | Principal Investigator: Ziyad Al-Aly | Institution: ST. LOUIS VA MEDICAL CENTER, St. Louis, MO | Activity Code: I01 | Study Section: Special Emphasis Panel[ZRD1 CARA-V (01)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11187313