Study population
We conducted a prospective cohort study at the Department of Cardiology, Zhongshan Hospital of Fudan University, Shanghai city, China, from September 1, 2015, to December 31, 2016. HFrEF patients were prospectively evaluated for inclusion in the study. In this study, HFrEF were prospectively evaluated for inclusion. HFrEF was diagnosed according to the current consensus statements of the American Heart Association[1] and Guidelines for the diagnosis and treatment of Heart failure in China 2018 [12]. All subjects were screened according to the inclusion and exclusion standards at baseline, detailed as follows.The inclusion criteria: (1) symptoms or signs of heart failure, (2) N-terminal prohormone of brain natriuretic peptide (NT-proBNP) > 125 ng/L,(3) left ventricular ejection fraction (LVEF) < 40%,and (4) New York Heart Association functional (NYHA) class ≥ II. Exclusion criteria included (1) congenital heart disease, (2)acute coronary syndrome in the last 30 days, (3) pericardial disease, (4) pacemaker or other conditions precluding patients from CMR, (5)severe anemia (hemoglobin < 7 g/dL), (6) chronic obstructive pulmonary disease GOLD 3 or 4, and (7)estimated glomerular filtration rate < 30 mL/min/1.73 m2. The study protocol conformed to the Declaration of Helsinki, and its subsequent amendments were approved by the local ethics committee of Zhongshan Hospital, Fudan University; all subjects signed informed consent.
Collection of clinical, echocardiographic, CMR imaging and biochemical variables
Covariates in the present study included general information, demographic, variables that can affect the ratio of sST2/LVMI or cardiac mortality, and HF hospitalization based on our clinical experiences and reported by previous literature.
Demographic data, clinical and biochemical variables including age, gender, BMI, diastolic blood pressure, systolic blood pressure, heart rate, NYHA functional class, medical history, and cardiovascular risk factors(smoking, hypertension, diabetes mellitus). Serum biomarkers of myocardial fibrosis (sST2, PICP, PINP, PIIINP), hemoglobin, white blood cells, NT-proBNP, sodium, creatinine, blood urea nitrogen, serum uric acid, albumin, total bilirubin, total cholesterol, high-density lipoprotein cholesterol, hypersensitive C-reactive protein, and hematocrit were collected. Same as our previous work, Enzyme-linked immunosorbent assay (ELISA) was performed to measure the concentration of sST2 using the Presage ST2 assay kit (CriticalDiagnostics, California, USA) [13].
Echocardiography was performed according to the recommendations of ASE guidelines[14]. All participants underwent transthoracic echocardiography using a Philips iE33 ultrasound machine (Philips Medical Systems, Eindhoven, The Netherlands) equipped with an S5–1 and X3–1 probe by board-certified physicians. Left atrial diameter (LAD), LVEF, left ventricular end-diastolic diameter (LVEDD), interventricular septal thickness (IVST) were analyzed.
As our previous work demonstrating[15], all subjects received clinical CMR scans by 2 dedicated CMR technologists with a 1.5-T CMR system (MAG-NETOM Area, Siemens Healthcare, Erlangen, Germany) with an 18-channel phased-array cardiovascular coil.CMR data analysis was performed using dedicated software Argus(Siemens Medical Solution, Erlangen, Germany) by an observer blinded to all clinical data. LVM was determined by tracing the epicardial and endocardial border of each slice at end-diastole, summing the myocardial volume of all slices, and multiplying by myocardial density (1.05 g/mL)[16].LVM was indexed to body surface area (LVMI). Other CMR imaging variables were measured using the methods described in our previous published paper[15].
Follow-up and outcomes
Patients were followed by telephone calls and ambulatory visits at 9-month intervals. The primary outcome was a combined end-point consisting of HF rehospitalization or cardiovascular-cause death. The follow-up time was calculated from discharge to the primary outcome or 9 months after discharge.Endpoints were adjudicated by all coauthor together.
Statistical analysis
Data are expressed as mean (standard deviation) (Gaussian distribution) or median (min, max)(Skewed distribution) for continuous variables and as numbers and percentages for categorical variables. χ2 (categorical variables), One-Way ANOVA test (normal distribution), or Kruskal-Whallis H test (skewed distribution) were used to detect the differences among different the ratio of sST2/LVMI (tertile). We used univariate and multivariate Cox proportional-hazards regression models to test the link between the ratio of sST2/LVMI and primary outcome with three distinct models. Model 1 is the non-adjusted model with no covariates adjusted. Model 2 is the minimally-adjusted model with only sociodemographic variables adjusted. Model 3 is the fully-adjusted model. Because Cox proportional-hazards regression model-based methods are often suspected for their inability to deal with non-linear models, nonlinearity between the ratio of sST2/LVMI and primary outcome were addressed using Cox proportional hazards regression model with cubic spline functions and the smooth curve fitting (penalized spline method). If nonlinearity was detected, we first calculated the inflection point using the recursive algorithm and then constructed a two-piecewise Cox proportional-hazards regression model on both sides of the inflection point. The subgroup analyses were performed using a stratified Cox proportional-hazards regression model. For a continuous variable, we first converted it to a categorical variable according to the clinical cut point or tertile and then performed an interaction test. Tests for effect modification for those of subgroup indicators were followed by the likelihood of ration test.Log-rank tests for Kaplan–Meier survival curves were performed for testing different prognostic values in various levels of the ratio of sST2/LVMI.
Data were analyzed using the statistical software packages R (http://www.R-project.org, The R Foundation) and EmpowerStats (http://www. empowerstats.com, X&Y Solutions, Inc, Boston, MA). All statistical tests were 2-sided, and a P-value < 0.05 was considered statistically significant.