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Association of pulmonary artery capacitance with long-term outcomes in acute coronary syndrome patients with left ventricular systolic dysfunction.
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Abstract
objectiveHemodynamic monitoring via right heart catheterization (RHC) is critical for managing acute coronary syndrome (ACS) patients with heart failure or cardiogenic shock. However, the prognostic value of RHC-derived hemodynamic indices in ACS patients with left ventricular systolic dysfunction (LVSD) but without heart failure or shock remains uncertain.
methodsA retrospective cohort study included 1151 consecutive ACS patients who underwent RHC during hospitalization from 2007 to 2016. After excluding patients with shock, pulmonary edema, and severe valvular disease, 750 ACS patients with LVSD and ejection fraction < 50% were analyzed. Major adverse cardiovascular events (MACEs), including myocardial infarction and all-cause mortality, were followed for five years. Cox regression identified predictors of MACEs, adjusting for comorbidities, treatments, and hemodynamic indices, including pulmonary arterial capacitance (PAC).
resultsAfter a mean follow-up of 4.0 ± 1.7 years, 113 (15.1%) patients experienced MACEs. Multivariate analysis showed that independent predictors included prior stroke, calcified coronary lesions, and PAC. Patients in the lowest PAC tertile (≤2.89 ml/mmHg) had significantly higher risks of myocardial infarction (adjusted hazard ratio [HR]: 3.74; 95% confidence interval [CI]: 1.55-9.07; DISCUSSION: The study demonstrated that PAC is a notably strong hemodynamic parameter with independent long-term prognostic value in ACS patients with LVSD, who do not present with shock or heart failure. This is the first study to establish the prognostic significance of hemodynamic indices obtained from RHC in this population, extending the clinical relevance of RHC from high-risk to intermediate-risk ACS populations.
conclusionsThe use of RHC to assess hemodynamic indices, including PAC, during index hospitalization in this population may enhance long-term risk stratification and improve outcome prediction.
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