Cardiac Structure and Function in Patients with Cystic Fibrosis
Cardiac Structure and Function in Patients with Cystic Fibrosis
In a prospective observational cohort study (n = 100), the investigators aim to assess the correlation between cardiac biomarkers, advanced echocardiography and cystic fibrosis genotype and severity and determine whether these are prognostic markers of heart disease in patients suffering from cystic fibrosis (CF).
Background:
Previous studies using standard echocardiography have shown contradictory results regarding left ventricle (LV) structure and function in patients with CF. By the use of strain rate analyses, few studies have identified LV systolic abnormalities even in the setting of preserved conventional echocardiographic measures of LV systolic function such as left ventricular ejection fraction (LVEF) and fractional shortening. The expression of the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel in myocytes of different mammalian species including mice and humans has been known for many years. Two studies showed that CFTR is involved in regulation of cardiomyocyte contraction in mice and another study demonstrated that loss of CFTR function in mice led to LV remodeling and increased aortic stiffness. The presence of CFTR in the myocardium has prompted debate regarding a possible intrinsic cardiac impairment due to loss of CFTR. A recent study found an association between severity of genotype in patients with CF and cardiac impairment. Several studies of pediatric CF patients with none or mild respiratory manifestations have also demonstrated early signs of cardiovascular impairments, such as arterial stiffness, increased pulmonary artery pressure (PAP) and abnormalities of right ventricular (RV) structure and function.
Primary hypothesis: CF is independently associated with higher prevalence of asymptomatic cardiac dysfunction and abnormal cardiac structure determined by conventional and advanced echocardiographic deformation measures (cross sectional study).
Secondary hypotheses: 1) CF is associated with elevated levels of specific cardiac biomarkers (cross sectional study). 2) CF is associated with higher pulmonary artery systolic pressure and higher prevalence of pulmonary hypertension determined by echocardiography (cross sectional study). 3) Asymptomatic cardiac dysfunction and abnormal cardiac structure assessed by conventional and advanced echocardiographic deformation measurements are early markers identifying CF patients in high risk of cardiac disease (prospective study).
Objective:
In a prospective observational cohort study (n = 100) the aim is to investigate the correlation between cardiac biomarkers, advanced echocardiography and cystic fibrosis (CF) genotype and severity and determine whether these are prognostic markers of heart disease in patients suffering from CF.
Design and control group:
The study is a prospective observational cohort study consisting of a random sample of consecutive patients from a population of outpatients with CF and a control group from the general population. The project group aims to include 100 participants with CF. The findings in CF participants will be compared with findings in the general population to estimate the risk of cardiovascular disease in CF patients. The investigators expect an inclusion period of approximately 6 months with register-based follow-up after 2, 5 and 10 years after inclusion.
The control group will consist of a random sample of age- and sex-matched patients (n=100) from the general population examined in the5th Copenhagen City Heart Study, 2011-2015 (ClinicalTrials.gov identifier NCT02993172, I-Suite no. 03741, National Committee on Health Research Ethics approval HEH-2015-045).
Baseline cardiovascular examination:
Baseline examination at CF Centre Copenhagen:
All included participants will undergo a physical examination by a physician at the CF center as well as an experienced pulmonary physiotherapist. The examinations will be performed at inclusion and prior to echocardiographic examination and contain the following: 1) Clinical assessment, 2) Pulmonary function testing.
Moreover, data on genetics and health status will be retrieved from the medical records and the national CF database. Diagnoses and/or medical history obtained will include:
CF genotype CF mutation type and mutation class CF-related comorbidities: CF-related diabetes, pancreatic insufficiency, liver steatosis/fibrosis, pulmonary function including high resolution CT scans, kidney disease, infectious disease burden and chronic infections as well as use of acute and chronic antibiotics.
Cardiovascular comorbidities: Stroke, peripheral artery disease (PAD), atrial fibrillation/atrial flutter and/or other cardiac arrythmias, pacemaker, kidney disease, hypertension, hypercholesterolemia, valvular disease (mitral, aortic, tricuspid and pulmonic valve disease), previous heart surgery, ischemic heart disease including non-invasive ischemic imaging results, prior myocardial infarction, prior revascularization and/or coronary artery bypass graft (CABG), heart failure, sleep apnea, venous thromboembolic syndrome (VTE) (deep vein thrombosis, pulmonary embolism).
Data management and statistics:
The General Data Protection Regulation and the Data Protection Act will be complied with.
All data will be stored in a password-protected electronic research database, REDCap, The Capital Region of Denmark's electronic data system. Questionnaires, signed consent forms and other sensitive documents will be kept in a locked archive in a locked office at the Department of Cardiology. The data management plan has been approved by the Danish Data Protection Agency (P-2022-366), and all data will be handled confidentially according to Danish law.
Baseline characteristics across the endpoints will be compared with trend tests using linear regression for continuous Gaussian distributed variables, by an extension of the Wilcoxon rank-sum test for continuous Gaussian distributed variables and by chi-square test for trend for proportions. Rates of all events will be calculated as the number of events divided by person-time at risk and stratified according to the primary endpoints. Hazard ratios (HR) will be calculated by Cox proportional hazards regression analysis. C-statistics will be obtained from univariable Cox models. Non-Gaussian distributed continuous variables will be categorized as dichotomous variables. The assumptions of proportional hazards in the models will be tested based on residuals. Predictive models for predicting the risk of future heart disease will be constructed using logistic regression. A p-value <= 0.05 in 2-sided test will be considered statistically significant.
Inclusion Criteria:
Exclusion Criteria: