551 Killip class predictors and prognostic role in acute myocardial infarction
Authors: Amicone Sara , Sansonetti Angelo , Armillotta Matteo , Angeli Francesco , Stefanizzi Andrea , Bergamaschi Luca , Fabrizio Michele , Paolisso Pasquale , Casella Gianni , Galiè Nazzareno , Pizzi Carmine 
Published: December 2021

Aims

Killip classification is a simple and fast clinical tool for risk stratification in patients with acute coronary syndrome (ACS). However, predictors of high Killip class at admission and its prognostic impact in the clinical contest of myocardial infarction with nonobstructive coronary artery (MINOCA) are still poorly known. To identify the clinical predictors of high Killip class and its potential prognostic role on in-hospital and follow-up outcomes in patients with MINOCA compared to patients with myocardial infarction with obstructive coronary artery (MIOCA).

Methods and results

We included all consecutive patients with myocardial infarction (MI) undergoing coronary angiogram between 2016 and 2019 at our hospital. According to 2016 ESC Position Paper criteria, we considered as MINOCA all patients with acute MI and with the angiographic conventional cut-off of &lt; 50% coronary stenosis without clinically apparent alternative diagnosis (e.g. sepsis, stroke, pulmonary embolism, myocarditis, and Tako-tsubo). We analysed Killip class of MINOCA patients comparing with those of MIOCA (coronary stenosis ≥50%). Kaplan–Meier (KM) curves were developed for the comparison of overall-mortality among MINOCA with high Killip class (major than 1) compared to other. Multivariate logistic regression analysis was used to determine the predictors of high Killip class both in the MINOCA and MIOCA populations. Among 3165 MI, 260 patients fulfilled the 2016 ESC criteria for MINOCA. Overall, 62.3% were males and the mean age was 68.6 ± 13.2 years. The median follow-up time was 23.3 ± 14.5 months. Killip class &gt;1 occurred in 24 patients in MINOCA group and 507 in MIOCA group (17.5% vs. 9.2%, P = 0.001). The KM survival distributions were significantly different across Killip class &gt;1 (P &lt; 0.001) in both populations with higher mortality in patients with higher Killip class. Finally, the multivariate logistic regression showed that the predictors of high Killip class at time of presentation in MIOCA population were older age [odds ratio: 1.04, 95% CI: (1.03–1.06), P &lt; 0.001], diabetes [odd ratio 0.63, 95% CI (0.48–0.81), P &lt; 0.001], ST elevation [odds ratio: 0.65, 95% CI (0.48–0.89), P = 0.008], left ventricle ejection fraction [odds ratio: 0.95, 95% CI (0.94–0.96), P &lt; 0.001], and elevated cardiac troponin [odds ratio: 1.00, 95% CI (1.00–1.00), P = 0.01]. Older age [odds ratio: 1.08, 95% CI (1.03–1.14), P = 0.003], ST elevation [odd ratio 0.14, 95% CI (0.02–0.93), P = 0.042], and diabetes [odd ratio 3.60, 95% CI (1.08–1.96), P = 0.037] were predictors of high Killip class in MINOCA, however left ventricle ejection fraction (P = 0.3) and elevated cardiac troponin (P = 0.6) did not predict the high Killip class in MINOCA patients.

Conclusions

Our data suggest that Killip classification performed at the time of admission is a useful clinical marker of a high risk of early and late adverse cardiovascular events even in patients with MINOCA. The predictors of the high Killip class at time of presentation in MIOCA were older age, diabetes, ST elevation, left ventricle ejection fraction, and elevated cardiac troponin. Older age, ST elevation, and diabetes were predictors of high Killip class even in MINOCA, however left ventricle ejection fraction and elevated cardiac troponin did not predict the high Killip class in MINOCA patients. These results could reflect the different pathogenetic myocardial damage in MINOCA and MIOCA populations. Further studies are needed to evaluate these pathological mechanisms.