Background: Killip classification is a practical clinical tool for risk stratification in patients with acute myocardial infarction (AMI). However, its prognostic role in myocardial infarction with non-obstructive coronary artery (MINOCA) is still poorly explored. Our purpose was to evaluate the prognostic role of high Killip class in the specific setting of MINOCA and compare the results with a cohort of patients with obstructive coronary arteries myocardial infarction (MIOCA). Methods: This study included 2455 AMI patients of whom 255 were MINOCA. We compared the Killip classes of MINOCA with those of MIOCA and evaluated the prognostic impact of a high Killip class, defined if greater than I, on both populations’ outcome. Short-term outcomes included in-hospital death, re-AMI and arrhythmias. Long-term outcomes were all-cause mortality, re-AMI, stroke, heart failure (HF) hospitalization and the composite endpoint of MACE. Results: Killip class >1 occurred in 25 (9.8%) MINOCA patients compared to 327 (14.9%) MIOCA cases. In MINOCA subjects, a high Killip class was associated with a greater in-hospital mortality (p = 0.002) and, at long term follow-up, with a three-fold increased mortality (p = 0.001) and a four-fold risk of HF hospitalization (p = 0.003). Among MINOCA, a high Killip class was identified as a strong independent predictor of MACE occurrence [HR 2.66, 95% CI (1.25–5.64), p = 0.01] together with older age and worse kidney function while in MIOCA population also left ventricular ejection fraction and troponin value predicted MACE. Conclusions: Killip classification confirmed its prognostic impact on short- and long-term outcomes also in a selected MINOCA population, which still craves for a baseline risk stratification.
Armillotta Matteo., Amicone S., Bergamaschi Luca., Angeli Francesco., Rinaldi Andrea., Paolisso P., et al. (2023). Predictive value of Killip classification in MINOCA patients. EUROPEAN JOURNAL OF INTERNAL MEDICINE, 81, 42-47 [10.1016/j.ejim.2023.08.011].
Predictive value of Killip classification in MINOCA patients
Armillotta Matteo.;Amicone S.;Bergamaschi Luca.;Angeli Francesco.;Paolisso P.;Stefanizzi A.;Sansonetti A.;Impellizzeri A.;Bodega F.;Canton L.;Suma N.;Fedele Damiano.;Bertolini D.;Foa A.;Pizzi Carmine.
2023
Abstract
Background: Killip classification is a practical clinical tool for risk stratification in patients with acute myocardial infarction (AMI). However, its prognostic role in myocardial infarction with non-obstructive coronary artery (MINOCA) is still poorly explored. Our purpose was to evaluate the prognostic role of high Killip class in the specific setting of MINOCA and compare the results with a cohort of patients with obstructive coronary arteries myocardial infarction (MIOCA). Methods: This study included 2455 AMI patients of whom 255 were MINOCA. We compared the Killip classes of MINOCA with those of MIOCA and evaluated the prognostic impact of a high Killip class, defined if greater than I, on both populations’ outcome. Short-term outcomes included in-hospital death, re-AMI and arrhythmias. Long-term outcomes were all-cause mortality, re-AMI, stroke, heart failure (HF) hospitalization and the composite endpoint of MACE. Results: Killip class >1 occurred in 25 (9.8%) MINOCA patients compared to 327 (14.9%) MIOCA cases. In MINOCA subjects, a high Killip class was associated with a greater in-hospital mortality (p = 0.002) and, at long term follow-up, with a three-fold increased mortality (p = 0.001) and a four-fold risk of HF hospitalization (p = 0.003). Among MINOCA, a high Killip class was identified as a strong independent predictor of MACE occurrence [HR 2.66, 95% CI (1.25–5.64), p = 0.01] together with older age and worse kidney function while in MIOCA population also left ventricular ejection fraction and troponin value predicted MACE. Conclusions: Killip classification confirmed its prognostic impact on short- and long-term outcomes also in a selected MINOCA population, which still craves for a baseline risk stratification.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.