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Abstract Aims Cardiac allograft vasculopathy (CAV) is the major long‐term complication after heart transplantation, leading to mortality and re‐transplantation. As available non‐invasive biomarkers are scarce for CAV screening, we aimed to identify a proteomic signature for CAV. Methods and results We measured urinary proteome by capillary electrophoresis coupled with mass spectrometry in 217 heart transplantation recipients (mean age: 55.0 ± 14.4 years; women: 23.5%), including 76 (35.0%) patients with CAV diagnosed by coronary angiography. We randomly and evenly grouped participants into the derivation cohort (n = 108, mean age: 56.4 ± 13.8 years; women: 22.2%; CAV: n = 38) and the validation cohort (n = 109, mean age: 56.4 ± 13.8 years; women: 24.8%, CAV: n = 38), stratified by CAV. Using the decision tree‐based machine learning methods (extreme gradient boost), we constructed a proteomic signature for CAV discrimination in the derivation cohort and verified its performance in the validation cohort. The proteomic signature that consisted of 27 peptides yielded areas under the curve of 0.83 [95% confidence interval (CI): 0.75–0.91, P

Abstract Aims Identifying early right ventricular (RV) dysfunction and impaired vasodilator reserve is challenging in heart failure with preserved ejection fraction (HFpEF). We hypothesized that cardiac magnetic resonance (CMR)‐based exercise imaging and serial cyclic guanosine monophosphate (cGMP) measurements can identify dynamic RV‐arterial uncoupling and responsiveness to pulmonary vasodilators at early stages of the HFpEF syndrome. Methods and results Patients with HFpEF (n = 16), impaired left ventricular relaxation due to concentric remodelling (LVCR, n = 7), and healthy controls (n = 8) underwent CMR at rest and during supine bicycle exercise with simultaneous measurements of central haemodynamics and circulating cGMP levels, before and after oral administration of 50 mg sildenafil. At rest, mean pulmonary artery pressures (mPAP) were higher in HFpEF, compared with LVCR and controls (27 ± 2, 18 ± 1, and 11 ± 1, respectively; P = 0.01), whereas biventricular volumes, heart rate, and stroke volume were similar. During exercise, LVCR and HFpEF had a greater increase in the ratio of mPAP over cardiac output than controls (5.50 ± 0.77 and 6.34 ± 0.86 vs. 2.24 ± 0.55 in controls, P = 0.005). The ratio of peak exercise to rest RV end‐systolic pressure‐volume, a surrogate of RV contractility, was significantly reduced in LVCR and HFpEF (2.32 ± 0.17 and 1.56 ± 0.08 vs. 3.49 ± 0.35 in controls, P

AimsCreation of an algorithm that includes the most important parameters (history, clinical parameters, and anamnesis) that can be linked to heart failure, helping general practitioners in recognizing heart failure in an early stage and in a better follow-up of the patients.Methods and resultsThe algorithm was created using a consensus-based Delphi panel technique with fifteen general practitioners and seven cardiologists from Belgium. The method comprises three iterations with general statements on diagnosis, referral and treatment, and follow-up. Consensus was obtained for the majority of statements related to diagnosis, referral, and follow-up, whereas a lack of consensus was seen for treatment statements. Based on the statements with good and perfect consensus, an algorithm for general practitioners was assembled, helping them in diagnoses and follow-up of heart failure patients. The diagnosis should be based on three essential pillars, i.e. medical history, anamnesis and clinical examination. In case of suspected heart failure, blood analysis, including the measurement of NT-proBNP levels, can already be performed by the general practitioner followed by referral to the cardiologist who is then responsible for proper diagnosis and initiation of treatment. Afterwards, a multidisciplinary health care process between the cardiologist and the general practitioner is crucial with an important role for the general practitioner who has a key role in the up-titration of heart failure medication, down-titration of the dose of diuretics and to assure drug compliance.ConclusionsBased on the consensus levels of statements in a Delphi panel setting, an algorithm is created to help general practitioners in the diagnosis and follow-up of heart failure patients.

Introduction. The data assessing the impact of beta blocker (BB) medication on survival in patients after heart transplantation (HTx) are scarce and unequivocal; therefore, we investigated this population. Methods. We retrospectively analyzed the HTx Zabrze Registry of 380 consecutive patients who survived the 30-day postoperative period. Results. The percentage of patients from the entire cohort taking BBs was as follows: atenolol 24 (17%), bisoprolol 67 (49%), carvedilol 11 (8%), metoprolol 28 (20%), and nebivolol 8 (6%). The patients receiving BBs were older (56.94 ± 14.68 years vs. 52.70 ± 15.35 years, p=0.008) and experienced an onset of HTx earlier in years (11.65 ± 7.04 vs. 7.24 ± 5.78 p≤0.001). They also had higher hematocrit (0.40 ± 0.05 vs. 0.39 ± 0.05, p=0.022) and red blood cells (4.63 (106/μl) ± 0.71 vs. 4.45 (106/μl) ± 0.68, p=0.015). Survival according to BB medication did not differ among the groups (p=0.655) (log-rank test). Univariate Cox proportional hazard regression analysis revealed that the following parameters were associated with unfavorable diagnosis: serum concentration of albumin (g/l) HR: 0.87, 95% CI (0.81–0.94), p=0.0004; fibrinogen (mg/dl) HR: 1.006, 95% CI (1.002–1.008), p=0.0017; and C-reactive protein (mg/l) HR: 1.014, 95% CI (1.004–1.023), p=0.0044. Conclusions. The use of BBs in our cohort of patients after HTx was not associated with survival benefits.

Background. This proof-of-concept study investigated the feasibility of using biomarkers to monitor right heart pressures (RHP) in heart transplanted (HTx) patients. Methods. In 298 patients, we measured 7.6 years post-HTx mean pressures in the right atrium (mRAP) and pulmonary artery (mPAP) and capillaries (mPCWP) along with plasma high-sensitivity troponin T (hsTnT), a marker of cardiomyocyte injury, and the multidimensional urinary classifiers HF1 and HF2, mainly consisting of dysregulated collagen fragments. Results. In multivariable models, mRAP and mPAP increased with hsTnT (per 1-SD, +0.91 and +1.26 mm Hg; P < 0.0001) and with HF2 (+0.42 and +0.62 mm Hg; P ≤ 0.035), but not with HF1. mPCWP increased with hsTnT (+1.16 mm Hg; P < 0.0001), but not with HF1 or HF2. The adjusted odds ratios for having elevated RHP (mRAP, mPAP or mPCWP ≥10, ≥24, ≥17 mm Hg, respectively) were 1.99 for hsTnT and 1.56 for HF2 (P ≤ 0.005). In detecting elevated RHPs, areas under the curve were similar for hsTnT and HF2 (0.63 vs 0.65; P = 0.66). Adding hsTnT continuous or per threshold or HF2 continuous to a basic model including all covariables did not increase diagnostic accuracy (P ≥ 0.11), whereas adding HF2 per optimized threshold increased both the integrated discrimination (+1.92%; P = 0.023) and net reclassification (+30.3%; P = 0.010) improvement. Conclusions. Correlating RHPs with noninvasive biomarkers in HTx patients is feasible. However, further refinement and validation of such biomarkers is required before their clinical application can be considered.

OBJECTIVES:Heart transplant (HTx) recipients have a high heart rate (HR), because of graft denervation and are frequently started on β-blockade (BB). We assessed whether BB and HR post HTx are associated with a specific urinary proteomic signature. METHODS:In 336 HTx patients (mean age, 56.8 years; 22.3% women), we analyzed cross-sectional data obtained 7.3 years (median) after HTx. We recorded medication use, measured HR during right heart catheterization, and applied capillary electrophoresis coupled with mass spectrometry to determine the multidimensional urinary classifiers HF1 and HF2 (known to be associated with left ventricular dysfunction), ACSP75 (acute coronary syndrome) and CKD273 (renal dysfunction) and 48 sequenced urinary peptides revealing the parental proteins. RESULTS:In adjusted analyses, HF1, HF2 and CKD273 (p ≤ 0.024) were higher in BB users than non-users with a similar trend for ACSP75 (p = 0.06). Patients started on BB within 1 year after HTx and non-users had similar HF1 and HF2 levels (p ≥ 0.098), whereas starting BB later was associated with higher HF1 and HF2 compared with non-users (p ≤ 0.014). There were no differences in the urinary biomarkers (p ≥ 0.27) according to HR. BB use was associated with higher urinary levels of collagen II and III fragments and non-use with higher levels of collagen I fragments. CONCLUSIONS:BB use, but not HR, is associated with a urinary proteomic signature that is usually associated with worse outcome, because unhealthier conditions probably lead to initiation of BB. Starting BB early after HTx surgery might be beneficial.

ObjectivesUrinary Proteomics in Predicting Heart Transplantation Outcomes (uPROPHET; NCT03152422) aims: (i) to construct new multidimensional urinary proteomic (UP) classifiers that after heart transplantation (HTx) help in detecting graft vasculopathy, monitoring immune system activity and graft performance, and in adjusting immunosuppression; (ii) to sequence UP peptide fragments and to identify key proteins mediating HTx-related complications; (iii) to validate UP classifiers by demonstrating analogy between UP profiles and tissue proteomic signatures (TP) in diseased explanted hearts, to be compared with normal donor hearts; (iv) and to identify new drug targets. This article describes the uPROPHET database construction, follow-up strategies and baseline characteristics of the HTx patients.MethodsHTx patients enrolled at the University Hospital Gasthuisberg (Leuven) collected mid-morning urine samples. Cardiac biopsies were obtained at HTx. UP and TP methods and the statistical work flow in pursuit of the research objectives are described in detail in the Data supplement.ResultsOf 352 participants in the UP study (24.4% women), 38.9%, 40.3%, 5.7% and 15.1% had ischemic, dilated, hypertrophic or other cardiomyopathy. The median interval between HTx and first UP assessment (baseline) was 7.8 years. At baseline, mean values were 56.5 years for age, 25.2 kg/m2 for body mass index, 142.3/84.8 mm Hg and 124.2/79.8 mm Hg for office and 24-h ambulatory systolic/diastolic pressure, and 58.6 mL/min/1.73 m2 for the estimated glomerular filtration rate. Of all patients, 37.2% and 6.5% had a history of mild (grade = 1B) or severe (grade ≥ 2) cellular rejection. Anti-body mediated rejection had occurred in 6.2% patients. The number of follow-up urine samples available for future analyses totals over 950. The TP study currently includes biopsies from 7 healthy donors and 15, 14, and 3 patients with ischemic, dilated, and hypertrophic cardiomyopathy.ConclusionsuPROPHET constitutes a solid resources for UP and TP research in the field of HTx and has the ambition to lay the foundation for the clinical application of UP in risk stratification in HTx patients.