Abstract
BACKGROUND: Cardiovascular medications are vital for the secondary prevention of coronary arterial disease (CAD). However, the effect of cardiovascular medication may depend on the optimal adherence of the patients. This meta-analysis aims to determine the magnitude of adherence to vascular medications that influences the absolute and relative risks (RRs) of mortality in patients with CAD in real-world settings. METHODS: The Cochrane Library, PubMed, and EMBASE databases were searched through March 1, 2022. Prospective studies reporting association as RR and 95% confidence interval between cardiovascular medication adherence and any cardiovascular events and/or all-cause mortality in patients with CAD were included. A one-stage robust error meta-regression method was used to summarize the dose-specific relationships. RESULTS: A total of 18 studies were included. There is a significant inverse linear association between cardiovascular medication adherence and cardiovascular events (p(nonlinearity) = .68) or mortality (p(nonlinearity) = .82). The exposure-effect analysis showed that an improvement of 20% cardiovascular medication adherence was associated with 8% or 12% lower risk of any cardiovascular events or mortality, respectively. In subgroup analysis, the benefit was observed in adherence of stain (RR: 0.90, for cardiovascular events, RR: 0.85, for mortality), angiotensin-converting enzyme inhibitors (ACEI)/angiotensin II receptor blockers (ARB)(RR: 0.90, for mortality), and antiplatelet agent (RR: 0.89 for mortality) but not in beta-blocker (RR: 0.90, p = .14, for cardiovascular events, RR: 0.97, p = .32 for mortality). Estimated absolute differences per 1 million individuals per year for mortality associated with 20% improvement were 175 cases for statin, 129 cases for antiplatelet, and 117 cases for ACEI/ARB. CONCLUSION: Evidence from the real word showed poor adherence to vascular medications contributes to a considerable proportion of all cardiovascular disease events and mortality in patients with CAD.