Abstract

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Gigi e Pupa Ferrari ONLUS. Background It has been shown that atherosclerosis risk factors have been associated with aortic valve sclerosis (AVSc) and that AVSc is associated with both all-cause and cardiovascular mortality. Thus, it is not surprising that atherosclerotic disorders (e.g., carotid or coronary atherosclerosis) and AVSc often coexist in the same subject, eventually leading to acute myocardial infarction (AMI). Patients with AMI are at increased risk of recurrent cardiovascular events with an average all-cause mortality rate at 5 years of 25%. Therefore, it is crucial to identify the precise phenotype(s) that characterize(s) patients who will experience adverse events after AMI and AVSc may serve as a marker of risk. Purpose To evaluate whether AVSc can be an independent prognostic predictor in patients with AMI or a biomarker reflecting their comorbidity burden. Methods We analysed 2388 AMI patients who were admitted at our cardiology center (2010-2019). All patients underwent echocardiographic evaluation for AVSc assessment. Long-term all-cause mortality was retrieved from a regional database system and medical records of cardiovascular hospitalizations were collected for composite events. We employed unsupervised topological data analysis (TDA) to stratify sub-groups of AMI patients with specific probabilities of recurrent AMI and evaluate the importance of AVSc in this setting. Results AVSc was detected in 1151 (48%) patients. We found a significant association of AVSc with adverse cardiovascular events even after full adjustment (HR 1.29, 95%CI 1.02-1.63; p=0.037). Since the composite outcome included cardiovascular conditions with different aetiologies, we performed a sub-analysis looking closely at each outcome. We found that recurrent AMI was associated with AVSc presence in AMI patients (HR 1.54, 95%CI: 1.16-2.05; p=0.003). Of note, in the fully adjusted model, AVSc was significantly associated with recurrent AMI in patients younger than 75 years of age (HR 1.59, 95%CI: 01.04-2.45; p=0.034). Finally, the TDA highlighted the presence of 8 clusters of patients and these clusters exhibit specific risks of recurrent AMI within 2 years after discharge. The evaluation of time-to-event curves allowed us to combine these clusters into three super-clusters (i.e., mild-, moderate-, and high-risk patients) with the average risk of event-free rate after 2 years from discharge close to 98%, 92%, and 83%, respectively. Of note, the random forest procedure showed that AVSc was the most relevant variable to discriminate the three classes of risk (i.e., super-clusters). Conclusions AVSc is frequently detected in AMI patients and it is strongly associated with long-term cardiovascular events, especially in those younger than 75 years old. AVSc has been identified to be the most relevant variable to identify patients at high risk of recurrent AMI.

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