Combined coronary microvascular dysfunction and AI-enabled ECG-derived elevated filling pressure identified patients with the highest 1-year (12.7%) and 8-year (51.8%) risk of MACE.
Cohort
Does the combination of coronary flow reserve and AI-enabled ECG-derived filling pressure predict major adverse cardiovascular events in patients with angina with nonobstructive coronary arteries?
Integrating AI-enabled ECG-derived filling pressure and coronary flow reserve provides complementary prognostic information and enhances risk stratification in patients with angina with nonobstructive coronary arteries.
p-value: p=0.02
BACKGROUND: Coronary flow reserve reflects microvascular function, whereas filling pressure indicates myocardial hemodynamic burden. In angina with nonobstructive coronary arteries, abnormalities in either could contribute to a supply-demand mismatch; however, their combined prognostic significance remains unclear. METHODS: Patients with angina with nonobstructive coronary arteries who underwent invasive coronary reactivity tests were studied retrospectively. Coronary microvascular dysfunction (CMD) was coronary flow reserve <2.5. An artificial intelligence-enabled ECG marker of elevated filling pressure (AIEFP) was applied as a scalable prognostic marker of myocardial hemodynamic stress. Associations with major adverse cardiovascular events were evaluated using Cox regression and propensity score overlap weighting. RESULTS: =0.02). In a 4-group model, adjusted risks increased in a graded manner. Overlap-weighted analysis after covariate balance demonstrated distinct temporal risk trajectories: CMD+/AIEFP+ had the highest 1-year risk (12.7%), and AIEFP+ had the highest cumulative 8-year risk (57% in CMD- and 51.8% in CMD+). CONCLUSIONS: CMD and AIEFP provide complementary prognostic information, with AIEFP remaining significantly associated with outcomes after multivariable adjustment. A dual-axis framework integrating myocardial hemodynamic stress (AIEFP) and microvascular function (coronary flow reserve) may enhance risk stratification and enable identification of clinically distinct angina with nonobstructive coronary arteries phenotypes with divergent trajectories.
Kalhor et al. (Wed,) conducted a cohort in Angina with nonobstructive coronary arteries. Coronary microvascular dysfunction (CMD) and AI-enabled ECG marker of elevated filling pressure (AIEFP) was evaluated on Major adverse cardiovascular events (p=0.02). Combined coronary microvascular dysfunction and AI-enabled ECG-derived elevated filling pressure identified patients with the highest 1-year (12.7%) and 8-year (51.8%) risk of MACE.
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