Given the prevalence of COVID-19 infection, assessment of sequelae is critical to public health. Recent studies revealed a higher incidence of resistant hypertension after COVID-19 recovery. Presently, there is limited data and ability to clinically ascribe mechanisms using traditional techniques. Literature-based discovery (LBD) leverages artificial intelligence to stitch together multi-scalar relationships from millions of journal articles. Identified related concepts are ranked according to their predicted relevance in ascribing the shared etiology of hypertension and COVID-19. The dominant LBD-identified ascribed physiology included: altered endocrine function, inflammation, lipid dysfunction, altered nerve input for blood pressure, and altered COVID-19 viral entry.