Study Population and Baseline Characteristics
The protocol has been approved by Anzhen Hospital Review Committee. Written informed consent and publication consent have been obtained from all participants. From July 2005 to October 2017, patients (age ≥18 years) with HCM and AMI admitted to Beijing Anzhen Hospital, in China, were consecutively enrolled. AMI is a subset of a spectrum of acute coronary syndrome (ACS) including unstable angina pectoris (UA) and AMI with or without ST-segment elevation. AMI can be diagnosed if cardiac troponin I level >99th percentile and patients had at least one of the following conditions: 1. Persistent chest pain lasting >20 minutes; 2. Serial electrocardiographic changes consisting of new pathological Q waves, new ST-segment or T-wave changes, or new left bundle branch block.
Baseline patient characteristics were derived from hospitalized patients and included age, sex, BMI, smoking status, hypertension, diabetes, hyperlipidemia, obesity, hospitalization days and clinically relevant comorbidities (atrial fibrillation, known coronary artery disease, family history of coronary artery disease, chronic obstructive pulmonary disease, chronic renal insufficiency, peripheral artery disease, prior stroke/transient ischemic attack, ventricular tachycardia, anterior myocardial infarction, prior percutaneous coronary intervention, prior myocardial infarction, prior coronary artery bypass grafting, carotid artery disease, pulmonary embolism, heart failure). Laboratory tests included total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, B-type natriuretic peptide, troponin I, D-Dimer and serum creatinine. Echocardiographic parameters were assessed using transthoracic echocardiography with the Teichholz method prior to coronary angiography; these included left ventricular ejection fraction, left ventricular posterior wall, thickness of the interventricular septum and left ventricular end-diastolic inner diameter. Coronary angiography was performed according to standard criteria. Offline analysis of digital angiograms was performed in the core laboratory using an automated edge detection system (CMS; Medis Medical Imaging Systems, Leiden, the Netherlands). Binary stenosis was defined as stenosis of >50% of the luminal diameter. The above methods were performed according to the method descriptions reported by Liu F et al.15
Follow up and Definition of Endpoints
Major adverse events recorded in hospital included death, cardiogenic shock, major bleeding, atrioventricular block (AVB), episodes sustained ventricular tachyarrhythmia (VT)/ventricular fibrillation (VF) and thrombosis. Major bleeding was defined as: Any intracranial bleeding (excluding microhemorrhages <10 mm evident only on gradient-echo MRI); clinically overt signs of hemorrhage associated with a drop in hemoglobin of ≥5 g/dL; Fatal bleeding (bleeding that directly results in death within 7d). Post hospital discharge, major adverse cardiac events were defined as cardiac death, cardiogenic shock, re-myocardial infarction (re-MI), re-percutaneous coronary intervention (re-PCI), re-coronary artery bypass grafting (re-CABG) and stroke. Cardiac death was defined as mortality resulting from cardiac disease. The secondary endpoints were defined as rehospitalization, recurrent angina, thrombosis, bleeding, heart failure and arrhythmias. Bleeding was defined as: Clinically overt (including imaging), resulting in hemoglobin drop of 3 to <5 g/dL. The above definitions were quoted from the study by Liu F et al.15
All subjects were followed from the first hospitalization until a first coronary event, death or 7 November 2017. Endpoint status was ascertained via clinic visits, medical records, telephone contact, and text messages. If more than two complications occurred in a single patient, each complication type was recorded. For deceased patients, death certificates were procured, and the next of kin were interviewed to determine the time of death15.
Statistical Analysis
Continuous variables are presented as mean and standard deviation or as median and quartiles where appropriate. Differences were assessed with Student’s t-test. Categorical variables were expressed as frequencies with percentages, and compared using the chi-square test where appropriate. The 95% confidence interval (CI) of annual mortality rate was calculated using the binomial approximation. Survival was graphically represented using Kaplan-Meier curves. Differences in survival rates were compared using the log-rank test. The 95% CI of annual mortality rate was calculated using GraphPad Prism 6 (GraphPad Software Inc., La Jolla, USA). All other analyses were performed using SPSS statistical software, version 21.0 (SPSS Inc., Chicago, USA). All tests were 2-tailed, and statistical significance was defined as P < 0.05.