Pulmonary artery pressure monitoring in chronic heart failure: effects across clinically relevant subgroups in the MONITOR-HF trial.

BACKGROUND AND AIMS: In patients with chronic heart failure (HF), the MONITOR-HF trial demonstrated the efficacy of pulmonary artery (PA)-guided HF therapy over standard of care in improving quality of life and reducing HF hospitalizations and mean PA pressure. This study aimed to evaluate the consistency of these benefits in relation to clinically relevant subgroups. METHODS: The effect of PA-guided HF therapy was evaluated in the MONITOR-HF trial among predefined subgroups based on age, sex, atrial fibrillation, diabetes mellitus, left ventricular ejection fraction, HF aetiology, cardiac resynchronisation therapy, and implantable cardioverter defibrillator. Outcome measures were based upon significance in the main trial and included quality of life, clinical, and PA pressure endpoints, and were assessed for each subgroup. Differential effects in relation to the subgroups were assessed with interaction terms. Both unadjusted and multiple testing adjusted interaction terms were presented. RESULTS: The effects of PA monitoring on quality of life, clinical events, and PA pressure were consistent in the predefined subgroups, without any clinically relevant heterogeneity within or across all endpoint categories (all adjusted interaction P-values were nonsignificant). In the unadjusted analysis of the primary endpoint quality-of-life change, weak trends towards a less pronounced effect in older patients (Pinteraction = 0.03; adjusted Pinteraction = 0.33) and diabetics (Pinteraction = 0.01; adjusted Pinteraction = 0.06) were observed. However, these interaction effects did not persist after adjusting for multiple testing. CONCLUSIONS: This subgroup analysis confirmed the consistent benefits of PA-guided HF therapy observed in the MONITOR-HF trial across clinically relevant subgroups, highlighting its efficacy in improving quality of life, clinical, and PA pressure endpoints in chronic HF patients.

Circadian rhythms in pump parameters of patients on contemporary left ventricular assist device support.

BACKGROUND: Algorithms to monitor pump parameters are needed to further improve outcomes after left ventricular assist device (LVAD) implantation. Previous research showed a restored circadian rhythm in pump parameters in patients on HeartWare (HVAD) support. Circadian patterns in HeartMate3 (HM3) were not studied before, but this is important for the development of LVAD monitoring algorithms. Hence, we aimed to describe circadian patterns in HM3 parameters and their relation to patterns in heart rate (HR). METHODS: 18 HM3 patients were included in this study. HM3 data were retrieved at a high frequency (one sample per 1 or 2 h) for 1-2 weeks. HR was measured using a wearable biosensor. To study overall patterns in HM3 parameters and HR, a heatmap was created. A 24-h cosine was fitted on power and HR separately. The relationship between the amplitude of the fitted cosines of power and HR was calculated using Spearman correlation. RESULTS: A lower between patient variability was found in power compared with flow and PI. 83% of the patients showed a significant circadian rhythmicity in power (p < 0.001-0.04), with a clear morning increase. All patients showed significant circadian rhythmicity in HR (p < 0.001-0.02). The amplitudes of the circadian rhythm in power and HR were not correlated (Spearman correlation of 0.32, p = 0.19). CONCLUSIONS: A circadian rhythm of pump parameters is present in the majority of HM3 patients. Higher frequency pump parameter data should be collected, to enable early detection of complications in the future development of predictive algorithms.

Age is the main determinant of COVID-19 related in-hospital mortality with minimal impact of pre-existing comorbidities, a retrospective cohort study.

BACKGROUND: Age and comorbidities increase COVID-19 related in-hospital mortality risk, but the extent by which comorbidities mediate the impact of age remains unknown. METHODS: In this multicenter retrospective cohort study with data from 45 Dutch hospitals, 4806 proven COVID-19 patients hospitalized in Dutch hospitals (between February and July 2020) from the CAPACITY-COVID registry were included (age 69[58-77]years, 64% men). The primary outcome was defined as a combination of in-hospital mortality or discharge with palliative care. Logistic regression analysis was performed to analyze the associations between sex, age, and comorbidities with the primary outcome. The effect of comorbidities on the relation of age with the primary outcome was evaluated using mediation analysis. RESULTS: In-hospital COVID-19 related mortality occurred in 1108 (23%) patients, 836 (76%) were aged ≥70 years (70+). Both age 70+ and female sex were univariably associated with outcome (odds ratio [OR]4.68, 95%confidence interval [4.02-5.45], OR0.68[0.59-0.79], respectively;both p<  0.001). All comorbidities were univariably associated with outcome (p<0.001), and all but dyslipidemia remained significant after adjustment for age70+ and sex. The impact of comorbidities was attenuated after age-spline adjustment, only leaving female sex, diabetes mellitus (DM), chronic kidney disease (CKD), and chronic pulmonary obstructive disease (COPD) significantly associated (female OR0.65[0.55-0.75], DM OR1.47[1.26-1.72], CKD OR1.61[1.32-1.97], COPD OR1.30[1.07-1.59]). Pre-existing comorbidities in older patients negligibly (<6% in all comorbidities) mediated the association between higher age and outcome. CONCLUSIONS: Age is the main determinant of COVID-19 related in-hospital mortality, with negligible mediation effect of pre-existing comorbidities. TRIAL REGISTRATION: CAPACITY-COVID ( NCT04325412 ).

The benefit of vaccination against COVID-19 outweighs the potential risk of myocarditis and pericarditis.

Vaccines against coronavirus 2019 disease (COVID-19) have shown to be greatly effective in preventing viral spread, serious illness and death from this infectious disease and are therefore critical for the management of the COVID-19 pandemic. However, the listing of myocarditis and pericarditis as possible rare side effects of the messenger RNA (mRNA) vaccines against COVID-19 by regulatory agencies has sparked discussion on the vaccines' safety. The most important published cohort studies to date demonstrat that myocarditis is a very rare side effect after COVID-19 mRNA vaccination, with an incidence of approximately 1-4 cases per 100,000 vaccinated persons. Young males (16-29 years) appear to be at highest risk, predominantly after receiving the second dose. The disease course is self-limiting in a vast majority of cases: 95% of patients show a rapid resolution of symptoms and normalisation of cardiac biomarkers, electro- and echocardiographic findings within days. Importantly, the available data suggest that the incidence rate of myocarditis in the context of COVID-19 is much greater than the risk of this side effect following vaccination. We conclude that the benefit of vaccination against COVID-19 outweighs the potential risk of myocarditis and pericarditis in both adolescents and adults. Prospective follow-up of patients who have developed these complications after vaccination is required to assess long-term outcomes.

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning.

BACKGROUND AND PURPOSE: The electrocardiogram (ECG) is frequently obtained in the work-up of COVID-19 patients. So far, no study has evaluated whether ECG-based machine learning models have added value to predict in-hospital mortality specifically in COVID-19 patients. METHODS: Using data from the CAPACITY-COVID registry, we studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw format 12-lead ECGs recorded within 72 h of admission were studied. With data from five hospitals (n = 634), three models were developed: (a) a logistic regression baseline model using age and sex, (b) a least absolute shrinkage and selection operator (LASSO) model using age, sex and human annotated ECG features, and (c) a pre-trained deep neural network (DNN) using age, sex and the raw ECG waveforms. Data from two hospitals (n = 248) was used for external validation. RESULTS: Performances for models a, b and c were comparable with an area under the receiver operating curve of 0.73 (95% confidence interval [CI] 0.65-0.79), 0.76 (95% CI 0.68-0.82) and 0.77 (95% CI 0.70-0.83) respectively. Predictors of mortality in the LASSO model were age, low QRS voltage, ST depression, premature atrial complexes, sex, increased ventricular rate, and right bundle branch block. CONCLUSION: This study shows that the ECG-based prediction models could be helpful for the initial risk stratification of patients diagnosed with COVID-19, and that several ECG abnormalities are associated with in-hospital all-cause mortality of COVID-19 patients. Moreover, this proof-of-principle study shows that the use of pre-trained DNNs for ECG analysis does not underperform compared with time-consuming manual annotation of ECG features.

Rationale and design of the PHOspholamban RElated CArdiomyopathy intervention STudy (i-PHORECAST).

BACKGROUND: The p.Arg14del (c.40_42delAGA) phospholamban (PLN) pathogenic variant is a founder mutation that causes dilated cardiomyopathy (DCM) and arrhythmogenic cardiomyopathy (ACM). Carriers are at increased risk of malignant ventricular arrhythmias and heart failure, which has been ascribed to cardiac fibrosis. Importantly, cardiac fibrosis appears to be an early feature of the disease, occurring in many presymptomatic carriers before the onset of overt disease. As with most monogenic cardiomyopathies, no evidence-based treatment is available for presymptomatic carriers. AIMS: The PHOspholamban RElated CArdiomyopathy intervention STudy (iPHORECAST) is designed to demonstrate that pre-emptive treatment of presymptomatic PLN p.Arg14del carriers using eplerenone, a mineralocorticoid receptor antagonist with established antifibrotic effects, can reduce disease progression and postpone the onset of overt disease. METHODS: iPHORECAST has a multicentre, prospective, randomised, open-label, blinded endpoint (PROBE) design. Presymptomatic PLN p.Arg14del carriers are randomised to receive either 50 mg eplerenone once daily or no treatment. The primary endpoint of the study is a multiparametric assessment of disease progression including cardiac magnetic resonance parameters (left and right ventricular volumes, systolic function and fibrosis), electrocardiographic parameters (QRS voltage, ventricular ectopy), signs and/or symptoms related to DCM and ACM, and cardiovascular death. The follow-up duration is set at 3 years. BASELINE RESULTS: A total of 84 presymptomatic PLN p.Arg14del carriers (n = 42 per group) were included. By design, at baseline, all participants were in New York Heart Association (NHYA) class I and had a left ventricular ejection fraction > 45% and < 2500 ventricular premature contractions during 24-hour Holter monitoring. There were no statistically significant differences between the two groups in any of the baseline characteristics. The study is currently well underway, with the last participants expected to finish in 2021. CONCLUSION: iPHORECAST is a multicentre, prospective randomised controlled trial designed to address whether pre-emptive treatment of PLN p.Arg14del carriers with eplerenone can prevent or delay the onset of cardiomyopathy. iPHORECAST has been registered in the clinicaltrials.gov-register (number: NCT01857856).

Impact of cardiovascular disease and cardiovascular risk factors in hospitalised COVID-19 patients.

BACKGROUND: Hospitalised COVID-19 patients with underlying cardiovascular disease (CVD) and cardiovascular risk factors appear to be at risk of poor outcome. It is unknown if these patients should be considered a vulnerable group in healthcare delivery and healthcare recommendations during the COVID-19 pandemic. METHODS: A systematic literature search was performed to answer the following question: In which hospitalised patients with proven COVID-19 and with underlying CVD and cardiovascular risk factors should doctors be alert to a poor outcome? Relevant outcome measures were mortality and intensive care unit admission. Medline and Embase databases were searched using relevant search terms until 9 June 2020. After systematic analysis, 8 studies were included. RESULTS: Based on the literature search, there was insufficient evidence that CVD and cardiovascular risk factors are significant predictors of mortality and poor outcome in hospitalised patients with COVID-19. Due to differences in methodology, the level of evidence of all studies was graded 'very low' according to the Grading Recommendations Assessment, Development and Evaluation methodology. It is expected that in the near future, two multinational and multicentre European registries (CAPACITY-COVID and LEOSS) will offer more insight into outcome in COVID-19 patients. CONCLUSION: This literature review demonstrated there was insufficient evidence to identify CVD and cardiovascular risk factors as important predictors of poor outcome in hospitalised COVID-19 patients. However, patients with CVD and cardiovascular risk factors remain vulnerable to infectious disease outbreaks. As such, governmental and public health COVID-19 recommendations for vulnerable groups apply to these patients.

Clinical profile and contemporary management of patients with heart failure with preserved ejection fraction: results from the CHECK-HF registry.

BACKGROUND: Clinical management of heart failure with preserved ejection fraction (HFpEF) centres on treating comorbidities and is likely to vary between countries. Thus, to provide insight into the current management of HFpEF, studies from multiple countries are required. We evaluated the clinical profiles and current management of patients with HFpEF in the Netherlands. METHODS: We included 2153 patients with HFpEF (defined as a left ventricular ejection fraction ≥ 50%) from the CHECK-HF registry, which included patients from 2013 to 2016. RESULTS: Median age was 77 (IQR 15) years, 55% were women and the most frequent comorbidities were hypertension (51%), renal insufficiency (45%) and atrial fibrillation (AF, 38%). Patients between 65 and 80 years and those over 80 years had on average more comorbidities (up to 64% and 74%, respectively, with two or more comorbidities) than patients younger than 65 years (38% with two or more comorbidities, p-value < 0.001). Although no specific drugs are available for HFpEF, treating comorbidities is advised. Beta-blockers were most frequently prescribed (78%), followed by loop diuretics (74%), renin-angiotensin system (RAS) inhibitors (67%) and mineralocorticoid receptor antagonists (MRAs, 39%). Strongest predictors for loop-diuretic use were older age, higher New York Heart Association class and AF. CONCLUSION: The medical HFpEF profile is determined by the underlying comorbidities, sex and age. Comorbidities are highly prevalent in HFpEF patients, especially in elderly HFpEF patients. Despite the lack of evidence, many HFpEF patients receive regular beta-blockers, RAS inhibitors and MRAs, often for the treatment of comorbidities.

BIO FOr CARE: biomarkers of hypertrophic cardiomyopathy development and progression in carriers of Dutch founder truncating MYBPC3 variants-design and status.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by truncating variants in the MYBPC3 gene. HCM is an important cause of sudden cardiac death; however, overall prognosis is good and penetrance in genotype-positive individuals is incomplete. The underlying mechanisms are poorly understood and risk stratification remains limited. AIM: To create a nationwide cohort of carriers of truncating MYBPC3 variants for identification of predictive biomarkers for HCM development and progression. METHODS: In the multicentre, observational BIO FOr CARe (Identification of BIOmarkers of hypertrophic cardiomyopathy development and progression in Dutch MYBPC3 FOunder variant CARriers) cohort, carriers of the c.2373dupG, c.2827C > T, c.2864_2865delCT and c.3776delA MYBPC3 variants are included and prospectively undergo longitudinal blood collection. Clinical data are collected from first presentation onwards. The primary outcome constitutes a composite endpoint of HCM progression (maximum wall thickness ≥ 20 mm, septal reduction therapy, heart failure occurrence, sustained ventricular arrhythmia and sudden cardiac death). RESULTS: So far, 250 subjects (median age 54.9 years (interquartile range 43.3, 66.6), 54.8% male) have been included. HCM was diagnosed in 169 subjects and dilated cardiomyopathy in 4. The primary outcome was met in 115 subjects. Blood samples were collected from 131 subjects. CONCLUSION: BIO FOr CARe is a genetically homogeneous, phenotypically heterogeneous cohort incorporating a clinical data registry and longitudinal blood collection. This provides a unique opportunity to study biomarkers for HCM development and prognosis. The established infrastructure can be extended to study other genetic variants. Other centres are invited to join our consortium.

Risk stratification and subclinical phenotyping of dilated and/or arrhythmogenic cardiomyopathy mutation-positive relatives: CVON eDETECT consortium.

In relatives of index patients with dilated cardiomyopathy and arrhythmogenic cardiomyopathy, early detection of disease onset is essential to prevent sudden cardiac death and facilitate early treatment of heart failure. However, the optimal screening interval and combination of diagnostic techniques are unknown. The clinical course of disease in index patients and their relatives is variable due to incomplete and age-dependent penetrance. Several biomarkers, electrocardiographic and imaging (echocardiographic deformation imaging and cardiac magnetic resonance imaging) techniques are promising non-invasive methods for detection of subclinical cardiomyopathy. However, these techniques need optimisation and integration into clinical practice. Furthermore, determining the optimal interval and intensity of cascade screening may require a personalised approach. To address this, the CVON-eDETECT (early detection of disease in cardiomyopathy mutation carriers) consortium aims to integrate electronic health record data from long-term follow-up, diagnostic data sets, tissue and plasma samples in a multidisciplinary biobank environment to provide personalised risk stratification for heart failure and sudden cardiac death. Adequate risk stratification may lead to personalised screening, treatment and optimal timing of implantable cardioverter defibrillator implantation. In this article, we describe non-invasive diagnostic techniques used for detection of subclinical disease in relatives of index patients with dilated cardiomyopathy and arrhythmogenic cardiomyopathy.

ONCOR: design of the Dutch cardio-oncology registry.

BACKGROUND: The relative new subspecialty 'cardio-oncology' was established to meet the growing demand for an interdisciplinary approach to the management of cancer therapy-related cardiovascular adverse events. In recent years, specialised cardio-oncology services have been implemented worldwide, which all strive to improve the cardiovascular health of cancer patients. However, limited data are currently available on the outcomes and experiences of these specialised services, and optimal strategies for cardio-oncological care have not been established. AIM: The ONCOR registry has been created for prospective data collection and evaluation of cardio-oncological care in daily practice. METHODS: Dutch hospitals using a standardised cardio-oncology care pathway are included in this national, multicentre, observational cohort study. All patients visiting these cardio-oncology services are eligible for study inclusion. Data collection at baseline consists of the (planned) cancer treatment and the cardiovascular risk profile, which are used to estimate the cardiotoxic risk. Information regarding invasive and noninvasive tests is collected during the time patients receive cardio-oncological care. Outcome data consist of the incidence of cardiovascular complications and major adverse cardiac events, and the impact of these events on the oncological treatment. DISCUSSION: Outcomes of the ONCOR registry may aid in gaining more insight into the incidence of cancer therapy-related cardiovascular complications. The registry facilitates research on mechanisms of cardiovascular complications and on diagnostic, prognostic and therapeutic strategies. In addition, it provides a platform for future (interventional) studies. Centres with cardio-oncology services that are interested in contributing to the ONCOR registry are hereby invited to participate.

Outcome of mechanical circulatory support at the University Medical Centre Utrecht.

BACKGROUND: The prevalence of heart failure (HF) is increasing substantially and, despite improvements in medical therapy, HF still carries a poor prognosis. Mechanical circulatory support (MCS) by a continuous-flow left ventricular assist device (cf-LVAD) improves survival and quality of life in selected patients. This holds especially for the short-term outcome, but experience regarding long-term outcome is growing as the waiting time for heart transplantation is increasing due to the shortage of donor hearts. Here we present our results from the University Medical Centre Utrecht. METHODS: Data of all patients with a cf-LVAD implant between March 2006 and January 2018 were collected. The primary outcome was survival. Secondary outcomes included adverse events defined according to the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) definitions, described per patient year. RESULTS: A total of 268 patients (69% male, mean age 50 ± 13 years) received a cf-LVAD. After a median follow-up of 542 (interquartile range 205-1044) days, heart transplantation had been performed in 82 (31%) patients, the cf-LVAD had been explanted in 8 (3%) and 71 (26%) had died. Survival at 1, 3 and 5 years was 83%, 72% and 57%, respectively, with heart transplantation, cf-LVAD explantation or death as the end-point. Death was most often caused by neurological complications (31%) or infection (20%). Major bleeding occurred 0.51 times and stroke 0.15 times per patient year. CONCLUSION: Not only short-term results but also 5­year survival after cf-LVAD support demonstrate that MCS is a promising therapy as an extended bridge to heart transplantation. However, the incidence of several major complications still has to be addressed.

Strength of patient cohorts and biobanks for cardiomyopathy research.

In 2011 the Netherlands Heart Foundation allocated funding (CVON, Cardiovasculair Onderzoek Nederland) to stimulate collaboration between clinical and preclinical researchers on specific areas of research. One of those areas involves genetic heart diseases, which are frequently caused by pathogenic variants in genes that encode sarcomere proteins. In 2014, the DOSIS (Determinants of susceptibility in inherited cardiomyopathy: towards novel therapeutic approaches) consortium was initiated, focusing their research on secondary disease hits involved in the onset and progression of cardiomyopathies. Here we highlight several recent observations from our consortium and collaborators which may ultimately be relevant for clinical practice.

A randomised comparison of the effect of haemodynamic monitoring with CardioMEMS in addition to standard care on quality of life and hospitalisations in patients with chronic heart failure : Design and rationale of the MONITOR HF multicentre randomised clinical trial.

BACKGROUND: Assessing haemodynamic congestion based on filling pressures instead of clinical congestion can be a way to further improve quality of life (QoL) and clinical outcome by intervening before symptoms or weight gain occur in heart failure (HF) patients. The clinical efficacy of remote monitoring of pulmonary artery (PA) pressures (CardioMEMS; Abbott Inc., Atlanta, GA, USA) has been demonstrated in the USA. Currently, the PA sensor is not reimbursed in the European Union as its benefit when applied in addition to standard HF care is unknown in Western European countries, including the Netherlands. AIMS: To demonstrate the efficacy and cost-effectiveness of haemodynamic PA monitoring in addition to contemporary standard HF care in a high-quality Western European health care system. METHODS: The current study is a prospective, multi-centre, randomised clinical trial in 340 patients with chronic HF (New York Heart Association functional class III) randomised to HF care including remote monitoring with the CardioMEMS PA sensor or standard HF care alone. Eligible patients have at least one hospitalisation for HF in 12 months before enrolment and will be randomised in a 1:1 ratio. Minimum follow-up will be 1 year. The primary endpoint is the change in QoL as measured by the Kansas City Cardiomyopathy Questionnaire (KCCQ). Secondary endpoints are the number of HF hospital admissions and changes in health status assessed by EQ-5D-5L questionnaire including health care utilisation and formal cost-effectiveness analysis. CONCLUSION: The MONITOR HF trial will evaluate the efficacy and cost-effectiveness of haemodynamic monitoring by CardioMEMS in addition to standard HF care in patients with chronic HF. Clinical Trial Registration number NTR7672.

Targeted next-generation sequencing in Slovak cardiomyopathy patients.

OBJECTIVES: For the first time we used targeted next-generation sequencing to detect candidate pathogenic variants in Slovak cardiomyopathy patients. BACKGROUND: Targeted next-generation sequencing is considered to be the best practice in genetic diagnostics of cardiomyopathies. However, in Slovakia, with high cardiomyopathies prevalence of 1/440, the current diagnostic tests are still based on Sanger sequencing of a few genes. Consequently, little is known about the exact contribution of pathogenic variants in known cardiomyopathy genes in Slovak patients. METHODS: We used a panel of 46 known cardiomyopathy-associated genes to detect genetic variants in 16 Slovak cardiomyopathy patients (6 dilated, 8 hypertrophic, 2 non-compaction subtypes). RESULTS: We identified candidate pathogenic variants in 11 of 16 patients (69 %). Genes with higher count of candidate pathogenic variants were MYBPC3, MYH and TTN, each with 3 different variants. Seven variants ACTC1 (c.329C>T), ANKRD1 (c.683G>T), MYH7 (c.1025C>T), PKP2 (c.2003delA), TTN (c.51655C>T, c.84841G>T, c.101874_101881delAGAATTTG) have been detected for the first time and might represent Slovak-specific genetic cause. CONCLUSIONS: We have performed genetic testing of previously untested Slovak cardiomyopathy patients using next-generation sequencing cardiomyopathy gene panel. Given the high percentage of candidate pathogenic variants it should be recommended to implement this method into routine genetic diagnostic practice in Slovakia (Tab. 4, Ref. 39).

Cardiac amyloidosis: the need for early diagnosis.

Amyloidosis is a collection of systemic diseases characterised by misfolding of previously soluble precursor proteins that become infiltrative depositions, thereby disrupting normal organ structure and function. In the heart, accumulating amyloid fibrils lead to progressive ventricular wall thickening and stiffness, resulting in diastolic dysfunction gradually progressing to a restrictive cardiomyopathy. The main types of cardiac amyloidosis are amyloid light chain (AL) amyloidosis caused by an underlying plasma cell dyscrasia, amyloid transthyretin (TTR) amyloidosis of wild-type (normal) TTR at older age (ATTRwt) and hereditary or mutant amyloid TTR (ATTRm) in which a genetic mutation leads to an unstable TTR protein. Overall survival is poor once heart failure develops, underlining the need for early referral and diagnosis. Treatment for AL amyloidosis has improved markedly over the last decades, and TTR amyloidosis gene silencers and orally available transthyretin stabilisers are ready to enter the clinical arena after recent positive outcome trials. Novel therapies aiming at fibril degradation with monoclonal antibodies are under investigation. In this review, we focus on 'red flag' signs and symptoms, diagnosis and management of cardiac amyloidosis which differs considerably from the general management of heart failure. Only by increasing awareness, prognosis for patients with this devastating disease can be improved.

A computerised decision support system for cardiovascular risk management 'live' in the electronic health record environment: development, validation and implementation-the Utrecht Cardiovascular Cohort Initiative.

PURPOSE: We set out to develop a real-time computerised decision support system (CDSS) embedded in the electronic health record (EHR) with information on risk factors, estimated risk, and guideline-based advice on treatment strategy in order to improve adherence to cardiovascular risk management (CVRM) guidelines with the ultimate aim of improving patient healthcare. METHODS: We defined a project plan including the scope and requirements, infrastructure and interface, data quality and study population, validation and evaluation of the CDSS. RESULTS: In collaboration with clinicians, data scientists, epidemiologists, ICT architects, and user experience and interface designers we developed a CDSS that provides 'live' information on CVRM within the environment of the EHR. The CDSS provides information on cardiovascular risk factors (age, sex, medical and family history, smoking, blood pressure, lipids, kidney function, and glucose intolerance measurements), estimated 10-year cardiovascular risk, guideline-compliant suggestions for both pharmacological and non-pharmacological treatment to optimise risk factors, and an estimate on the change in 10-year risk of cardiovascular disease if treatment goals are adhered to. Our pilot study identified a number of issues that needed to be addressed, such as missing data, rules and regulations, privacy, and patient participation. CONCLUSION: Development of a CDSS is complex and requires a multidisciplinary approach. We identified opportunities and challenges in our project developing a CDSS aimed at improving adherence to CVRM guidelines. The regulatory environment, including guidance on scientific evaluation, legislation, and privacy issues needs to evolve within this emerging field of eHealth.

UNRAVEL: big data analytics research data platform to improve care of patients with cardiomyopathies using routine electronic health records and standardised biobanking.

INTRODUCTION: Despite major advances in our understanding of genetic cardiomyopathies, they remain the leading cause of premature sudden cardiac death and end-stage heart failure in persons under the age of 60 years. Integrated research databases based on a large number of patients may provide a scaffold for future research. Using routine electronic health records and standardised biobanking, big data analysis on a larger number of patients and investigations are possible. In this article, we describe the UNRAVEL research data platform embedded in routine practice to facilitate research in genetic cardiomyopathies. DESIGN: Eligible participants with proven or suspected cardiac disease and their relatives are asked for permission to use their data and to draw blood for biobanking. Routinely collected clinical data are included in a research database by weekly extraction. A text-mining tool has been developed to enrich UNRAVEL with unstructured data in clinical notes. PRELIMINARY RESULTS: Thus far, 828 individuals with a median age of 57 years have been included, 58% of whom are male. All data are captured in a temporal sequence amounting to a total of 18,565 electrocardiograms, 3619 echocardiograms, data from over 20,000 radiological examinations and 650,000 individual laboratory measurements. CONCLUSION: Integration of routine electronic health care in a research data platform allows efficient data collection, including all investigations in chronological sequence. Trials embedded in the electronic health record are now possible, providing cost-effective ways to answer clinical questions. We explicitly welcome national and international collaboration and have provided our protocols and other materials on www.unravelrdp.nl .

Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium.

BACKGROUND: Machine learning (ML) allows the exploration and progressive improvement of very complex high-dimensional data patterns that can be utilised to optimise specific classification and prediction tasks, outperforming traditional statistical approaches. An enormous acceleration of ready-to-use tools and artificial intelligence (AI) applications, shaped by the emergence, refinement, and application of powerful ML algorithms in several areas of knowledge, is ongoing. Although such progress has begun to permeate the medical sciences and clinical medicine, implementation in cardiovascular medicine and research is still in its infancy. OBJECTIVES: To lay out the theoretical framework, purpose, and structure of a novel AI consortium. METHODS: We have established a new Dutch research consortium, the CVON-AI, supported by the Netherlands Heart Foundation, to catalyse and facilitate the development and utilisation of AI solutions for existing and emerging cardiovascular research initiatives and to raise AI awareness in the cardiovascular research community. CVON-AI will connect to previously established CVON consortia and apply a cloud-based AI platform to supplement their planned traditional data-analysis approach. RESULTS: A pilot experiment on the CVON-AI cloud was conducted using cardiac magnetic resonance data. It demonstrated the feasibility of the platform and documented excellent correlation between AI-generated ventricular function estimates as compared to expert manual annotations. The resulting AI solution was then integrated in a web application. CONCLUSION: CVON-AI is a new consortium meant to facilitate the implementation and raise awareness of AI in cardiovascular research in the Netherlands. CVON-AI will create an accessible cloud-based platform for cardiovascular researchers, demonstrate the clinical applicability of AI, optimise the analytical methodology of other ongoing CVON consortia, and promote AI awareness through education and training.

The Netherlands Arrhythmogenic Cardiomyopathy Registry: design and status update.

BACKGROUND: Clinical research on arrhythmogenic cardiomyopathy (ACM) is typically limited by small patient numbers, retrospective study designs, and inconsistent definitions. AIM: To create a large national ACM patient cohort with a vast amount of uniformly collected high-quality data that is readily available for future research. METHODS: This is a multicentre, longitudinal, observational cohort study that includes (1) patients with a definite ACM diagnosis, (2) at-risk relatives of ACM patients, and (3) ACM-associated mutation carriers. At baseline and every follow-up visit, a medical history as well information regarding (non-)invasive tests is collected (e. g. electrocardiograms, Holter recordings, imaging and electrophysiological studies, pathology reports, etc.). Outcome data include (non-)sustained ventricular and atrial arrhythmias, heart failure, and (cardiac) death. Data are collected on a research electronic data capture (REDCap) platform in which every participating centre has its own restricted data access group, thus empowering local studies while facilitating data sharing. DISCUSSION: The Netherlands ACM Registry is a national observational cohort study of ACM patients and relatives. Prospective and retrospective data are obtained at multiple time points, enabling both cross-sectional and longitudinal research in a hypothesis-generating approach that extends beyond one specific research question. In so doing, this registry aims to (1) increase the scientific knowledge base on disease mechanisms, genetics, and novel diagnostic and treatment strategies of ACM; and (2) provide education for physicians and patients concerning ACM, e. g. through our website ( www.acmregistry.nl ) and patient conferences.