Time-Critical Cardiovascular Risk After COVID-19: A Population-Based Analysis Across Variant Eras

To define the timing and intensity of cardiovascular risk after severe acute respiratory syndrome coronavirus 2 infection across the pre-Delta, Delta, and Omicron eras.

We conducted a population-based retrospective cohort study of 162,471 adults with severe acute respiratory syndrome coronavirus 2 infection from March 1, 2020 to December 31, 2023 using the Rochester Epidemiology Project, a medical records-linkage system covering a 27-county region in Minnesota and Wisconsin. Outcomes included major adverse cardiovascular events, thrombotic events, and dysrhythmias, identified using validated International Classification of Diseases, 10th Revision codes. Cumulative incidence accounted for the competing risk of death, and multivariable Cox regression assessed age- and variant-specific risk.

Over a median follow-up of 1.9 years (interquartile range, 1.2-2.4 years), 4922 individuals experienced major adverse cardiovascular events. Risk was highest within 30 days after infection and declined thereafter (P<.0001). During this early hazard window, adults aged ≥80 years had substantially higher adjusted risk in the pre-Delta and Delta eras compared with Omicron (pre-Delta hazard ratio, 3.89 [95% CI, 3.17-4.77]; Delta hazard ratio, 2.91 [95% CI, 2.28-3.71]). Thrombotic events showed a similar early, age-dependent pattern, peaking during the pre-Delta and Delta eras. Early dysrhythmia rates rose steeply with age and peaked during the Delta era, exceeding 60 events per 1000 person-months among adults aged ≥80 years. Late dysrhythmia incidence was stable across eras, reflecting persistent age-related risk.

Cardiovascular events after corona virus disease 2019 infection clustered within the first 30 days, with variation by age and variant era. This early concentration, most pronounced among older adults during the pre-Delta and Delta eras, is supportive of a clinically relevant hazard window while distinguishing observed patterns from causal inference. These findings support targeted, time-sensitive cardiovascular monitoring in higher-risk populations.