Association between common cardiovascular risk factors and clinical phenotype in patients with hypertrophic cardiomyopathy from the European Society of Cardiology (ESC) EurObservational Research Programme (EORP) Cardiomyopathy/Myocarditis registry

AIMS

The interaction between common cardiovascular risk factors (CVRF) and hypertrophic cardiomyopathy (HCM) is poorly studied. We sought to explore the relation between CVRF and the clinical characteristics of patients with HCM enrolled in the EURObservational Research Programme (EORP) Cardiomyopathy registry.

METHODS AND RESULTS

1739 patients with HCM were studied. The relation between hypertension (HT), diabetes (DM), body mass index (BMI), and clinical traits was analysed. Analyses were stratified according to the presence or absence of a pathogenic variant in a sarcomere gene. The prevalence of HT, DM, and obesity (Ob) was 37, 10, and 21%, respectively. HT, DM, and Ob were associated with older age (P<0.001), less family history of HCM (HT and DM P<0.001), higher New York Heart Association (NYHA) class (P<0.001), atrial fibrillation (HT and DM P<0.001; Ob p = 0.03) and LV (left ventricular) diastolic dysfunction (HT and Ob P<0.001; DM P = 0.003). Stroke was more frequent in HT (P<0.001) and mutation-positive patients with DM (P = 0.02). HT and Ob were associated with higher provocable LV outflow tract gradients (HT P<0.001, Ob P = 0.036). LV hypertrophy was more severe in Ob (P = 0.018). HT and Ob were independently associated with NYHA class (OR 1.419, P = 0.017 and OR 1.584, P = 0.004, respectively). Other associations, including a higher proportion of females in HT and of systolic dysfunction in HT and Ob, were observed only in mutation-positive patients.

CONCLUSION

Common CVRF are associated with a more severe HCM phenotype, suggesting a proactive management of CVRF should be promoted. An interaction between genotype and CVRF was observed for some traits.

Predictors of cardiovascular events and all-cause of death in patients with transfusion-dependent myelodysplastic syndrome

Cardiovascular disease (CVD) involves the second cause of death in low-risk myelodysplastic syndrome (MDS) population. Prospective study to characterise the CVD and to identify predictors for the combined event (CE) cardiovascular event and/or all-cause mortality in transfusion dependent low-risk MDS patients. Thirty-one patients underwent a cardiac assessment including biomarkers and cardiac magnetic resonance (cMR) with parametric sequences (T1, T2 and T2* mapping) and myocardial deformation by feature tracking (FT) and were analysed for clonal hematopoiesis of indeterminate potential mutations. Cardiac assessment revealed high prevalence of unknown structural heart disease (51% cMR pathological findings). After 2·2 [0·44] years follow-up, 35·5% of patients suffered the CE: 16% death, 29% cardiovascular event. At multivariate analysis elevated NT-proBNP ≥ 486pg/ml (HR 96·7; 95%-CI 1·135-8243; P = 0·044), reduced native T1 time < 983ms (HR 44·8; 95%-CI 1·235-1623; P = 0·038) and higher left ventricular global longitudinal strain (LV-GLS) (HR 0·4; 95%-CI 0·196-0·973; P = 0·043) showed an independent prognostic value. These variables, together with the myocardial T2* time < 20ms, showed an additive prognostic value (Log Rank: 12·4; P = 0·001). In conclusion, low-risk MDS patients frequently suffer CVD. NT-proBNP value, native T1 relaxation time and longitudinal strain by FT are independent predictors of poor cardiovascular prognosis, thus, their determination would identify high-risk patients who could benefit from a cardiac treatment and follow-up.

Magnetic Resonance Myocardial Feature Tracking in Transfusion-Dependent Myelodysplastic Syndrome

BACKGROUND

Myocardial deformation with echocardiography allows early detection of systolic dysfunction and is related to myocardial iron overload (MIO) determined by T2* in hereditary anemias under transfusion support. Our aim was to analyze the diagnostic and prognostic usefulness of magnetic resonance feature tracking (MR-FT) myocardial strain in low-risk myelodysplastic syndromes (LR-MDS) patients.

METHODS

Prospective study in transfusion-dependent LR-MDS patients and healthy controls who underwent a cardiac MR-FT. We analyzed the relationships between strain MR-FT and iron overload parameters and its prognostic impact in cardiovascular events and/or death.

RESULTS

Thirty-one patients and thirteen controls were included. MIO (T2* < 20 ms) was detected in 9.7% of patients. Left ventricular global longitudinal strain (LV-GLS) by MR-FT was pathological (> −19.3%) in 32.3% of patients. Less negative strain values correlated with lower T2* (R = −0.37, p = 0.033) and native myocardial T1 (R = −0.39, p = 0.031) times. LV-GLS by MR-FT was significantly associated with higher incidence of the combined cardiovascular events and/or all-cause death (p = 0.047), with a cut-off value of −17.7% for predicting them (63% sensitivity and 81% specificity, area under the curve = 0.69). After adjusting analysis including demographic, biomarkers and imaging variables, a higher LV-GLS value by MR-FT remained as predictor of combined event in transfusion-dependent LR-MDS patients (hazard ratio, 0.4; confidence interval, 0.15–0.98; p = 0.045).

CONCLUSIONS

Longitudinal myocardial strain by MR-FT in LR-MDS patients is associated to MIO and correlates with adverse events in the follow-up, what could serve as a prognostic tool.

P939 Global longitudinal myocardial strain: an independent predictor of cardiovascular events in patients with hematopoietic stem cell transplantation

BACKGROUND

Hematopoietic stem cell transplantation (HSCT) increases the likelihood of potentially serious cardiovascular complications. The scientific evidence on prognostic predictors is limited and cardiac monitoring of these patients is not systematized.

Our aim was to analyze cardiovascular prognosis and identify echocardiographic factors predicting cardiovascular events in the context of HSCT.

METHODS

An observational, retrospective study was designed, including 243 patients (mean age 54 ± 16yo, 60%males, 13% hypertension, 5% diabetes) undergoing a HSCT (60% Allogeneic/40% Autologous) with previous echocardiography, from December 2016 to the present. Clinical data, echocardiographic findings, mortality and cardiovascular events (CVE) were collected and analyzed.

RESULTS

After a median follow-up of 18 [12] months, 22 patients (9%) suffered CVE (54% arrhythmias, 40% heart failure, and 9% ischemic heart disease). Patients with Allogeneic-HSCT (13% vs. 3%; p: 0.007), left ventricular dilatation (40% vs. 8.5%, p = 0.02) or hypertrophy (33% vs. 8%, p: 0.01), dilated left atrium (33% vs. 9%, p:0.03), or pericardial effusion (33% vs. 9%, p: 0.04) in the echocardiographic study performed prior to HSCT suffered significantly more CVE at follow-up. Patients with CVE had significantly higher global longitudinal strain (GLS) (-19 ± 3% vs. -21 ± 3%, p= 0.001). Patients were divided into quartiles based on GLS, those belonging to the fourth quartile (&gt;-19.4%) suffered more frequently CVE (log Rank: 9.6; 18% vs. 6%, p = 0.002) with a significantly lower time to event (27 ± 1.8 vs. 32 ± 0.6 months) (Figure).

In multivariate analysis (Cox regression), Allogeneic-HSCT (HR: 5.6; p = 0.02) and the fourth quartile of GLS (HR: 4.3; p = 0.004) were maintained as independent predictors of cardiovascular event.

CONCLUSION

GLS before HSCT is an independent predictor of cardiovascular events at follow-up. This parameter could allow the identification of high-risk patients who could benefit from intensive protocolized cardiac follow-up.

Abstract P939 Figure. Survival analysis (Kaplan Meier)

SALMANTICOR study. Rationale and design of a population-based study to identify structural heart disease abnormalities: a spatial and machine learning analysis

INTRODUCTION

This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to geography and statistics, need to become used for healthcare research and for political commitment to obtain resources and support effective public health programme implementation.

METHODS AND ANALYSIS

We will perform a cross-sectional survey of randomly selected residents of Salamanca (Spain). 2400 individuals stratified by age and sex and by place of residence (rural and urban) will be studied. The variables to analyse will be obtained from the clinical history, different surveys including social status, Mediterranean diet, functional capacity, ECG, echocardiogram, VASERA and biochemical as well as genetic analysis.

ETHICS AND DISSEMINATION

The study has been approved by the ethical committee of the healthcare community. All study participants will sign an informed consent for participation in the study. The results of this study will allow the understanding of the relationship between the different influencing factors and their relative importance weights in the development of structural heart disease. For the first time, a detailed cardiovascular map showing the spatial distribution and a predictive machine learning system of different structural heart diseases and associated risk factors will be created and will be used as a regional policy to establish effective public health programmes to fight heart disease. At least 10 publications in the first-quartile scientific journals are planned.

TRIAL REGISTRATION NUMBER

NCT03429452.