European Heart Journal

Anker, Stefan; Asselbergs, Folkert Wouter; Brobert, Gunnar; Vardas, Panos; Grobbee, Diederick E; Cronin, Maureen

doi: 10.1093/eurheartj/ehx283pmid: 28863460

The BigData@Heart project will unlock the benefits of big data, to place European citizens at the centre of heart health  Facing the challenge The sustainability and quality of health care provision in Europe is being challenged. Demographic change and rapid innovation are leading to inconsistent medical care across Europe. Despite remarkable progress in the management of cardiovascular diseases, the fragmentation of healthcare data is a missed opportunity to maximize this innovation equitably. The lack of high-resolution and computable definitions and our inability to uniformly access and analyse existing data hinders progress in ensuring a leading role for Europe in innovative cardiovascular disease management. Over the past few years, big data approaches have helped improve efficiency in healthcare information processing in several non-cardiological domains. Big data insights have created value by using analyses from large clinical datasets to expedite the development of new drugs and optimize clinical management approaches. This knowledge can be transmitted to the cardiovascular domain. BigData@heart: what is it all about? BigData@Heart brings together a consortium of 19 stakeholders under an Innovative Medicines Initiative-2 (IMI-2) funded project. Launched in March 2017, the aim of the project is to apply big data approaches to the most common cardiovascular diseases in Europe today, namely, acute coronary syndrome (ACS), atrial fibrillation (AF), and heart failure (HF), in the hope to improve patient outcomes. This project is a public–private enterprise. The European Society of Cardiology (ESC), numerous European academic research groups, and European Federation of Pharmaceutical Industries and Associations (EFPIA)-based pharmaceutical industry have joined forces to develop a big data-driven translational research platform. This platform will deliver clinically relevant disease phenotypes, scalable insights from real-world evidence driving drug development and personalized medicine through advanced analytics. It comprises rich biomedical and omics-data on over 25 million subjects across Europe. Thanks to this partnership, BigData@Heart has access to most of the relevant large-scale European databases, ranging from electronic health records and disease registries through well-phenotyped clinical trials and large epidemiological cohorts covering more than five million cases of ACS, AF, and HF, which represents more than 16 million healthy individuals. By accessing and harmonizing European-wide data sets, the ambition is to design prognosis algorithms that can predict the evolution of disease based on previous medical history, hospitalization, and country-specific statistics. Pooling resources to bridge digital and health domains It is the first time that consented cohorts (conventional research data), electronic health records in population settings, disease quality improvement registries, trial data, and clinically recorded imaging data will be studied together to identify mismatches and deliver novel disease vocabulary and outcome definitions in the cardiovascular realm in Europe. This new vocabulary should assist the development of new medications, interventions, and targeted management recommendations that improve patient outcomes. BigData@Heart’s ambition is to translate these new findings into universal definitions for ACS, AF, and HF. This will impact clinical trial design and contribute in the transition of economically feasible personalized medicine. This endeavour will run for 5 years until 2022 and is guided by both the potential for innovation and key challenges that have frustrated current big data-driven progress. BigData@Heart is not designed to be a one-time project but targets to set new and durable standards for cardiovascular big data science for the next decades. BigData@Heart comprises of seven work packages that work interactively and transversally to create a responsive research framework to address the challenges posed in this project. From project management and dissemination to creation of data sources and definition outcomes, open access informatics and data enrichment, the project will provide tools and methodologies necessary to leverage the value of big data approaches for cardiovascular disease. These new methodologies will be tested in a set of six pilot studies all directly important for academia, industry and society. The project will address ethical and regulatory issues with appropriate and rigorous safeguards notably on personal data protection. The project should establish sustainable governance for data infrastructure during and beyond the project. Unlocking the innovation potential—the project’s added value BigData@Heart envisions unravelling the following features of cardiovascular diseases: Change the way diseases and their outcomes are defined by recasting and standardizing their definitions; this will be achieved by the use of large clinical records and consented data resources Inform the way clinical guidelines are developed from real-world evidence; by accessing European health records, representative estimates of disease will deliver a new generation of ESC clinical guidelines updated by novel data sources and analytics Increase personalized medicine approaches and drug development; genomic approaches will be deployed but also advanced analytics for new drug discovery and validation Develop strategies to use these predictive analytic tools which will support improvement of outcomes for patients and innovative drug development Advance regulatory, clinical, and healthcare practice; regulatory and payer stakeholders need to be streamlined to optimize patient treatment as discrepancies between these two parties often occur Strengthen competitiveness and industrial leadership addressing specific societal changes; drug development will make clinical trials less risky and probably cheaper Improve European citizens’ health and well-being Exciting times ahead Big data has enormous potential to improve patient care through guideline adherence, drug target discovery and validation and optimize clinical management approaches. Partnership and networks are needed between cardiology community, patient organizations, and professionals across different disciplines including computer science, health informatics, ethics, legal, and data science to fully develop and employ big data analytics. The ESC is a key partner in this respect, playing a central role through its extensive network, of international scientific communities across the full spectrum of cardiology. The ESC also works with a broad range of health organizations, as well as other stakeholders and policy-making bodies, whose decisions have a direct impact on the prevention, treatment, and management of cardiovascular disease. BigData@Heart aims to act as a platform for this network to stimulate big data approaches in cardiovascular disease research across Europe. Let us improve cardiovascular healthcare for Europeans. Let us make Europe a leader in this field. Think big. Think big data! Take big data to heart! For more information http://www.bigdata-heart.eu/ Conflict of interest: This work receives support from the EU/EFPIA Innovative Medicines Initiative [2] Joint Undertaking BigData@Heart grant n 116074. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Ouwerkerk, W.; Voors, A.A.; Anker, S.D.; Cleland, J.G.; Dickstein, K.; Filippatos, G.; van der Harst, P.; Hillege, H.L.; Lang, C.C.; ter Maaten, J.M.; Ng, L.L.; Ponikowski, P.; Samani, N.J; van Veldhuisen, D.J.; Zannad, F.; Metra, M.;

Baritussio, Anna; Gately, Amy; Pawade, Joya; Marks, David I.; Bucciarelli-Ducci, Chiara

doi: 10.1093/eurheartj/ehw393pmid: 27616778

A 38-year-old man was admitted with vasculitic rash and horizontal diplopia 9 months post allogenic stem cell transplantation for T-cell acute lymphoblastic leukemia (ALL). Magnetic resonance (MR) of the orbits showed enlarged extra-ocular muscles and an echocardiogram, to exclude cardiac embolic sources, showed bi-ventricular hypertrophy and speckled myocardium. A 12-lead ECG showed diffuse T-wave inversion (Panel 1A). A cardiovascular MR (CMR) showed preserved bi-ventricular systolic function, septal left ventricular (LV) hypertrophy (max 21 mm, normal <12mm) (Panel 1B) with increased LV mass (88 g/m2, normal 48–77 g/m2). Multiple areas of myocardial and pericardial infiltration (n = 9, largest 18×50mm) were noted on advanced tissue characterisation, showing markedly increased T1 values on native T1 mapping, and non-enhancing after contrast administration (Panel 1C and D, white arrows). The CMR findings raised the suspicion of acute cardiac involvement of ALL. A MR-guided biopsy of the swollen ocular left rectus muscle confirmed the diagnosis of relapsed acute T-cell ALL (Panel 2A and B), further supported by evidence of 0.09% T-lymphoblasts on bone marrow flow cytometry and low-level central nervous system (CNS) disease on lumbar puncture. As all the investigations confirmed acute multi-organ ALL relapse (heart, extra-ocular muscles, bone marrow, and CNS), systemic chemotherapy with nelarabine, and intra-thecal cytosine arabinoside were started. Diplopia rapidly improved, and a repeat orbit MR 14 days after commencement of chemotherapy showed complete resolution of extra-ocular muscle enlargement. A 1-month repeat CMR to assess cardiac response demonstrated complete resolution of all nodular lesions with normalization of LV wall thickness (10 mm) and mass (60 g/m2) (Panel 3B, C, and D), and of the widespread T-wave inversion on ECG (Panel 3A). Open in new tabDownload slide Open in new tabDownload slide Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For Permissions, please email: [email protected].

Tavazzi, Luigi

doi: 10.1093/eurheartj/ehx113pmid: 28379426

This editorial refers to ‘Determinants and clinical outcome of uptitration of ACE-inhibitors and beta-blockers in patients with heart failure: a prospective European study’†, by W. Ouwerkerk et al., on page 1883. In recent years, the number of observational reports published in the medical field has exploded. Several reasons may explain this exponential and novel research trend. One is the need to know whether and how the evidence-based recommended treatments are incorporated. In chronic diseases requiring long-term therapy, such as chronic heart failure (CHF), the compliance with recommended treatments is usually low, and frequently the drug doses taken are far below the recommended targets. The current widespread phenomenon of ‘underdosing’ might be related to non-adherence of both physician (in prescribing) and patient (in taking the prescribed drugs). On the other hand, the drug doses recommended in the current guidelines on CHF are those pre-defined as targets in placebo-controlled trials conducted in the now-remote past and subsequently systematically confirmed in guidelines as ‘optimal medical therapy’ in spite of evidence of an increasingly diverging clinical practice. Of note, as pointed out recently,1 also in landmark trials, for instance those testing beta-blockers (BBs) in CHF, a substantial portion of patients (ranging from 22% to 53% could not reach the protocol-defined target doses in spite of forced titration. Information about effectiveness of other doses, either lower or higher, seldom is available. Most effective drugs in CHF have many pharmacological effects (some desirable, some not). We do not know the precise dose at which the drug exerts each of its effects maximally, or the relative contribution of each pharmacological effect to the net clinical effect of the drug. Thus, we do not truly know the ‘optimal dose’ for any individual patient. Moreover, as each new therapy is added to the existing list for any condition, we have no information about the continuing benefit of therapies tested before the more recent additions. Perhaps the presently recommended target doses might best be considered as thresholds beyond which drugs have not been tested, rather than as targets that must be achieved.2 The ‘stack concept’, incorporated as the standard of heart failure (HF) optimal pharmacological medical therapy, might be reconsidered, and new risk models or biomarkers should be sought to better target the available therapy according to the individual clinical conditions, which fluctuate during the evolution of HF and co-existing morbidities.3 Actually, in hypertension, diabetes, and dyslipidaemia, the drug dosing is based on target effect on biomarkers rather than on target dose. The present issue of the journal reports a multinational study aimed to investigate ‘predictors, reasons, and clinical outcome’ of patients who after an acute or worsening episode of HF underwent a 3-month programme of ‘encouraged up-titration’ of angiotensin-converting-enzyme inhibitors (ACE-Is)/angiotensin II receptor blockers (ARBs) and/or BBs, and then were followed for 2 years The main results of the reported analyses were: first, although encouraged, very few patients reached the recommended doses of ACE-Is/ARBs (22%) and even fewer reached the target dose of BB (12%); secondly, reaching <50% of the recommended dose of ACE-Is/ARBs and BBs was associated with a worse outcome in terms of survival and HF hospitalization.4 The proportion of patients achieving the recommended target doses in this study is one of the lowest reported in the literature so far. To develop the most important aim of this study, namely the reasons why the target drug doses were not reached by most patients, the authors classified patients into three groups: (i) those reaching the recommended dose; (ii) those not reaching the recommended dose because of symptoms, side effects, or non-cardiac organ dysfunction (namely drug tolerability); and (iii) those not reaching the recommended dose because of other/unknown/not specified reasons. Unfortunately, the last category included approximately half of patients for ACE-Is/ARBs and two-thirds of the population for BBs, in fact precluding the chance to answer this essential question thoroughly. Several reasons may lie behind the non-prescription or below-target doses of drugs. A recent analysis of a large European Society of Cardiology (ESC) registry in CHF in which the reasons for low dosing were specifically investigated revealed an overall significant rate of inappropriateness, but definitely lower than that found in the present investigation5 (Figure 1). In placebo-controlled trials, it has been clearly shown that non-adherence, either with the study drug or with placebo, is a strong marker of poor outcome per se, which may account for ∼40% of the difference in hard outcomes between adherers and non-adherers to placebo.6 Accordingly, caution is necessary in drawing conclusions on drug effectiveness from registry data. Also the probability of successful drug up-titration may be biased due to baseline differences among patients. The authors used several methods for correction to minimize this bias: (i) a propensity score matching; (ii) a double robust estimation analysis; (iii) inverse probability weighting with the probability to reach the recommended dose; and (iv) a multivariate model with ACE-Is/ARBs and BBs as covariate. The results confirmed that reaching <50% of the recommended doses of both ACE-Is/ARBs and BBs is associated with significantly poorer survival. Figure 1 Open in new tabDownload slide Reasons for non-use of recommended treatments in patients with reduced ejection fraction. (A) Angiotensin-converting enzyme inhibitors (ACE-Is) and angiotensin receptor blockers (ARBs), (B) beta-blockers, and (C) mineralcorticoid antagonists (MRAs).5 Figure 1 Open in new tabDownload slide Reasons for non-use of recommended treatments in patients with reduced ejection fraction. (A) Angiotensin-converting enzyme inhibitors (ACE-Is) and angiotensin receptor blockers (ARBs), (B) beta-blockers, and (C) mineralcorticoid antagonists (MRAs).5 A major issue in clinical research, especially in the observational domain, concerns the representativeness of the population enrolled in a study. This involves several aspects of the study design, including the size of the population, the setting of enrolment, and the criteria for selection of those enrolled (or non-selection).7 The patients included in the study we are commenting on had a demographic profile similar to that usually seen in randomized controlled trials, namely mean age 68 years, 75% males. The demography—age and gender, strictly interlinked—is not a marginal issue in observational studies. One of the successes in the prevention of HF is the increasing age of the patients who present with HF, with the relative increase in the burden of co-morbidities.8,9 This incoming patient phenotype shifts the present CHF profile further away from that of the patients included in the reference trials, and this may affect the use of evidence-based therapies. However, the trials performed by cardiologists in cardiology settings are not very sensitive to this epidemiological evolution. As the present study confirms, the population enrolled in both randomized and observational trials performed in the cardiology setting unrealistically maintain a mean age of ∼65 years (or less) with a male:female ratio near 3:1, fewer co-morbidities, and a much better outcome than that recorded in administrative databases.10 The 2100 patients analysed in the present study were enrolled in 69 hospitals from 11 European countries. The number of patients included in each centre varied widely, between 1 and 157, with a median of 24 patients per centre. In a creditable attempt to reach a clinical practice representativeness, the enrolling centres were selected in each country taking into account the hospital type and complexity; however, with national networks averaging ∼6 centres, national or even macroregional representativeness is hard to achieve. For the same reason, cross-county or inter-regional analyses seem rather precarious. A survey performed by the ESC across the European national cardiac societies showed that there are ‘significant within- and cross-country variations and inequalities in the financing, organization, access, delivery, quality, and effectiveness of cardiac care’.11 Recently the ESC and the Organization for Economic Cooperation and Development (OECD) collaborated in an observational study aimed to identify clinical variables and health system characteristics associated with incomplete guideline application in the drug treatment of patients with CHF, across 15 European countries.12 Patient-level data were derived from the ESC Heart Failure Long-Term Registry, and country-level data were derived from OECD’s Health System Characteristics Survey. The analyses showed that countries with an easier access to medical care, a more structured primary care system, better resourcing, and quality programmes have greater levels of appropriateness of prescription of drug treatment for CHF than countries without these characteristics. However, a long list of acknowledged limitations was discussed in this report. In the study by Ouwerkerk et al.,4 country differences turned out to be independent predictors of drug up-titration success, but it cannot be ruled out that the reasons for this were differences in the number of patients/country enrolled or type of enrolling centres in each country rather than true regional variations in drug dosing. The limitations of the study briefly discussed above are substantially acknowledged by the authors, and represent the array of difficulties encountered by any group of investigators, including outstanding investigators such as those who authored this paper, in organizing vast international studies, based on a freshly created voluntary centre network, with scarce economic and personnel resources, no systematic auditing, and not supported by institutional databases. However, many things are changing across the world. The current acceleration in the development and spread of new technologies—especially Information Technology (IT)—characterizes the present time, with globalization of communication and knowledge. The incorporation of IT into the routine clinical activity of healthcare systems, generating a potentially universal Electronic Health Recording (EHR) network, sharable across countries, is now producing big data, collected day by day, to be interpreted and used by both scientists and public health authorities for a pragmatic, evidence-based public health management and governance. High-quality observational clinical research will serve as a platform for generating a new era of ‘evidence-based public health policies’ and ‘learning Health Systems’.13–15 Conflict of interest: None declared. References 1 Swedberg K , Komajda M, Böhm M, Borer J, Robertson M, Tavazzi L, Ford I. Effects on outcomes of heart rate reduction by ivabradine in patients with congestive heart failure: is there an influence of beta-blocker dose? J Am Coll Cardiol 2012 ; 59 : 1938 – 1945 . Google Scholar Crossref Search ADS PubMed WorldCat 2 Tavazzi L , Maggioni AP, Borer JS. Should we revise our approach to ‘optimal medical therapy’? The case of chronic heart failure . Eur Heart J 2013 ; 34 : 2792 – 2794 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Udelson JE , Stevenson LW. The future of heart failure diagnosis, therapy, and management . Circulation 2016 ; 133 : 2671 – 2686 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Ouwerkerk W, , Voors AA, Anker SD,, Cleland JG,, Dickstein K,, Filippatos G,, van der Harst P,, Hillege HL,, Lang CC, ter Maaten JM, Ng LL, Ponikowski P, Samani NJ, van Veldhuisen DJ, Zannad F, Metra M, Zwinderman AH. Determinants and clinical outcome of uptitration of ACE-inhibitors and beta-blockers in patients with heart failure: a prospective European study . Eur Heart J 2017 ; 38 : 1883 – 1890 . OpenURL Placeholder Text WorldCat 5 Maggioni AP , Anker SD, Dahlström U, Filippatos4 G, Ponikowski P, Zannad F, Amir O, Chioncel, Crespo Leiro M, Drozdz J, Erglis A, Fazlibegovic E, Fonseca C, Fruhwald F, Gatzov P, Goncalvesova E, Hassanein M, Hradec J, Kavoliuniene A, Lainscak M, Logeart D, Merkely B, Metra M, Persson H, Seferovic P, Temizhan A, Tousoulis D, L Tavazzi L. Are hospitalized or ambulatory patients with heart failure treated in accordance with European Society of Cardiology guidelines? Evidence from 12 440 patients of the ESC Heart Failure Long-Term Registry . Eur Heart J 2013 ; 15 : 1173 – 1184 . Google Scholar Crossref Search ADS WorldCat 6 Yue Z , Cai C, Ai-Fang Y, Feng-Min T, Li C, Bin W. The effect of placebo adherence on reducing cardiovascular mortality: a meta-analysis . Clin Res Cardiol 2014 ; 103 : 229 – 235 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Tavazzi L. Do we need clinical registries? Eur Heart J 2014 ; 35 : 7 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Jhund PS , Tavazzi L. Has the ‘epidemic’ of heart failure been replaced by a tsunami of co-morbidities? Eur J Heart Fail 2016 ; 18 : 500 – 502 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Deursen VM van , Urso R, Laroche C, Damman K, Dahlström U, Tavazzi L, Maggioni AP, Voors AA. Co-morbidities in patients with heart failure: an analysis of the European Heart Failure Pilot Survey . Eur J Heart Fail 2014 ; 16 : 103 – 111 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Maggioni AP , Orso F, Calabria S, Rossi E, Cinconze E, Baldasseroni S, Martini N, on behalf of ARNO Observatory . The real-world evidence of Heart Failure: findings from 41 413 patients of the ARNO data-base . Eur J Heart Fail 2016 ; 18 : 402 – 410 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Vardas P , Maniadakis N, Bardinet I, Pinto F. The European Society of Cardiology Atlas of Cardiology: rationale, objectives, and methods . Eur Heart J Qual Care Clin Outcomes 2016 ; 2 : 6 – 15 . Google Scholar Crossref Search ADS WorldCat 12 Maggioni AP , VanGool K, Biondi N, Urso R, Klazinga N, Ferrari R, Maniadakis N, Tavazzi L. Appropriateness of prescriptions of recommended treatments organisation for economic co-operation and development health systems: findings based on the Long-Term Registry of the European Society of Cardiology on Heart Failure . Value Health 2015 ; 18 : 1098 – 1104 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Fiuzat M , Califf R. The US Food and Drug Administration and the future of cardiovascular medicine . JAMA Cardiol 2016 ; 1 : 950 – 952 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Bhatt DL , Drozda JP Jr, Shahian DM, Chan PS, Fonarow GC, Heidenreich PA, Jacobs JP, Masoudi FA, Peterson ED, Welke KF. ACC/AHA/STS Statement on the Future of Registries and the Performance Measurement Enterprise: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures and the Society of Thoracic Surgeons . J Am Coll Cardiol 2015 ; 66 : 2230 – 2245 . Google Scholar Crossref Search ADS PubMed WorldCat 15 Tavazzi L , Ventura C. ‘Observational medicine’: registries and Electronic Health Recording for science and health systems governance . Eur J Heart Fail 2016 ; 18 : 1093 – 1095 . Google Scholar Crossref Search ADS PubMed WorldCat Author notes " The opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology. † " doi:10.1093/eurheartj/ehx026. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Fairbairn, Timothy A

doi: 10.1093/eurheartj/ehx285pmid: 28863462

FFRCT for the diagnosis of suspected ischaemic heart disease, reported by Dr Tim Fairbairn a principal investigator in the ADVANCE Registry  Introduction The UK National Institute for Health and Clinical Excellence (NICE) has recently made two significant decisions that may influence the role of fractional flow reserveCT (FFRCT) in the diagnosis and management of suspected coronary artery disease. The first was a clinical guidance (CG95) recommending coronary computed tomography angiography (CCTA) as the first line diagnostic strategy in the majority of suspected cardiac chest pains. Risk stratification was removed with other non-invasive tests (stress magnetic resonance imaging, stress echocardiography, and myocardial perfusion imaging) remaining the preferred option in individuals with previously known coronary artery disease. Invasive coronary angiography (ICA) was reserved as a third line test. The second decision was a medical technologies approval (MTG32) for the use of HeartFlow CT Fractional Flow Reserve (FFRCT, HeartFlow Inc, Redwood city, CA, USA) in a chest pain diagnostic pathway. Coronary computed tomography angiography for diagnosing coronary artery disease Coronary computed tomography angiography over the past decade has become an increasingly utilized tool for diagnosing coronary artery disease. Its high sensitivity (93%) and negative predictive value (>95%) have made it particularly useful in low-intermediate risk populations.1 Limitations to CCTA include technical factors that affect image quality (heart rate, arrhythmias, partial volume averaging) and radiation dose. However, the major limitation is the lack of a functional ischaemic component to this anatomical test. The ability to identify coronary plaque and degree of stenoses by CCTA and ICA whilst excellent, does not correlate well to myocardial ischaemia.2 Functional or anatomical imaging The importance of ischaemia to guide revascularization in stable ischaemic heart disease is contentious. COURAGE (Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation), STITCH (surgical Treatment for Ischaemic Heart Failure), and BARI 2D (Bypass Angioplasty Revascularization 2 Diabetes) indicated no prognostic benefit of revascularisation vs. medical therapy. However, FAME (fractional flow reserve vs. angiography in multivessel evaluation)3 showed ischaemia-driven therapy to be superior to anatomical guided therapy and several non-invasive studies have reported the importance of a high burden of ischaemia.4,5 International guidelines still recommend ischaemia driven therapy, so revascularizing an angiographically significant stenosis of uncertain functional significance remains controversial.6,7 Fractional flow reserveCT functional assessment Computed tomography assessment of plaque burden and characteristics (spotty calcification, positive arterial remodelling, necrotic core) is excellent and can help predict the likely functional significance of a lesion.8 However, the specificity of CT to determine functional significance is disappointingly low, as a significant proportion of cases remain inconclusive.9 The ability to combine a functional and anatomic non-invasive test is therefore highly desirable. Computed tomography perfusion can potentially address this, but exposes the patient to additional radiation and requires complex acquisition techniques. HeartFlow have used fluid dynamics computational models to calculate coronary blood flow and derive a FFRCT from a ‘standard’ CTA image. This has several practical advantages; utilizing the previously acquired CTA allows for a one-stop functional and anatomical assessment, reduced radiation and greater potential for widespread use, as the only requirement is good image quality and use of sub-lingual nitrates. The evidence for FFRCT is increasing. Initial results suggested greater diagnostic accuracy compared to CCTA alone but still with a low specificity (54%).10 HeartFlow improved their FFRCT physiological modelling and image processing and subsequent trials demonstrated higher specificity (FFRCT 84% vs. CCTA alone 34%) compared to invasive FFR measurements (Figure 1).11 This per-patient diagnostic accuracy is now comparable to other non-invasive functional modalities. FFRCT remains accurate in the instance of high Agatston scores and there is the prospect of improved diagnostic accuracy with per vessel analysis.12 HeartFlow are further developing their FFRCT technology; advances include 4-h turnaround times, 3D modelling that measures vessel size, lesion length and even ‘virtual stenting’ applications that derive estimated FFRCT post stenting. Figure 1 Open in new tabDownload slide Fractional flow reserveCT in a 61-year-old male with typical angina, hypertension, and hyperlipidaemia. Coronary computed tomography angiography demonstrated intermediate coronary stenoses (50–70%) of both the LAD and RCA. The fractional flow reserveCT results (RCA 0.71; LAD 0.86) correlated well to the invasive coronary angiography fractional flow reserve (RCA 0.76; LAD 0.88). Figure 1 Open in new tabDownload slide Fractional flow reserveCT in a 61-year-old male with typical angina, hypertension, and hyperlipidaemia. Coronary computed tomography angiography demonstrated intermediate coronary stenoses (50–70%) of both the LAD and RCA. The fractional flow reserveCT results (RCA 0.71; LAD 0.86) correlated well to the invasive coronary angiography fractional flow reserve (RCA 0.76; LAD 0.88). PROMISE (Outcomes of Anatomical vs. Functional Testing for Coronary Artery Disease) and SCOT-HEART (CT coronary angiography in patients with suspected angina due to coronary heart disease) have shown that a CCTA chest pain pathway is equivalent to other non-invasive strategies and has the potential to improve outcomes.13,14 Concern remains about CCTA as the primary diagnostic modality, centred on the fear of increased downstream tests, inappropriate ICA, and revascularisations.13,15 Could FFRCT reduce this risk and therefore be integral to the implementation of a CCTA diagnostic strategy? (Figure 2). Figure 2 Open in new tabDownload slide A 61-year old female with typical angina and a stress CMR that was reported as possible perfusion defect (A). The CCTA showed heavy calcified LAD with probable significant stenosis (B). FFRCT was positive in the LAD (<0.50) (C). The ICA showed a 90% mid LAD stenosis (D) and a PCI was performed (E). Figure 2 Open in new tabDownload slide A 61-year old female with typical angina and a stress CMR that was reported as possible perfusion defect (A). The CCTA showed heavy calcified LAD with probable significant stenosis (B). FFRCT was positive in the LAD (<0.50) (C). The ICA showed a 90% mid LAD stenosis (D) and a PCI was performed (E). PLATFORM (Prospective Longitudinal Trial of FFRCT: Outcomes and Resource Impacts) reported a FFRCT strategy when compared to invasive strategy, reduced non-obstructive stenoses at ICA by 83% without affecting total revascularizations.16 However, there was no difference compared to other non-invasive approaches. So does the advantage of FFRCT pertain more to a rapid diagnosis, reduced downstream testing, and lower costs? There are significant costs savings of using a FFRCT strategy compared to ICA, but potentially increased costs compared to non-invasive tests.17 NICE however modelled per patient costs of a HeartFlow FFRCT pathway and reported a significant cost-benefit of £214 per patient compared to all functional imaging tests. Fractional flow reserveCT the future There is great enthusiasm for the potential of FFRCT based on a clear clinical need. Is NICE by recommending the primary use of CCTA and approving HeartFlow FFRCT simply reflecting the evidence or is it another sign of ‘Brexit’, Britain drifting away from continental Europe? Fractional flow reserveCT technology is in its infancy and there are several requirements before it is universally accepted and clinically implemented. Randomized trials looking at long-term outcomes are essential. Diagnostic accuracy comparisons to other non-invasive modalities will be important, as will understanding any inaccuracies of the technique (microvascular disease, reduced coronary flow reserve, the role of volume to mass ratio). Costs of implementing an FFRCT diagnostic strategy into a chest pain pathway related to other non-invasive tests will inform discussions with healthcare commissioners and medical insurers. Incorporating FFRCT into standard clinical practice will take time and there will be a learning curve in the interpretation of results and integration into patient management. The ADVANCE (assessing diagnostic value of non-invasive FFRCT in Coronary Care) registry will help us understand how FFRCT impacts decision making in routine clinical practice.18 The UK by ‘advancing’ to clinically implement CCTA and FFRCT chest pain pathways may be able to provide essential clinical experience and knowhow. Conflict of interest: TAF is a PI for the ADVANCE study. References References are available as supplementary material at European Heart Journal online. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Siddiqi, Omar K.; Ruberg, Frederick L.

doi: 10.1093/eurheartj/ehx210pmid: 28444296

This editorial refers to ‘Diagnostic sensitivity of abdominal fat aspiration in cardiac amyloidosis’†, by C.C. Quarta et al., on page 1905 and ‘Clinical characteristics of wild-type transthyretin cardiac amyloidosis: disproving myths’‡, by E. González-López et al., on page 1895. The scientific history of systemic amyloidosis is replete with reports of incremental advancements reflecting developments in diagnostic tools and therapies, punctuated by frequent paradigm shifts that challenge the conventional wisdom of the day. First identified as a carbohydrate in the 19th century by Virchow, amyloid was subsequently reclassified as a protein, and then later as a category of proteins.1 Clinically too, the field of amyloidosis has evolved to represent a growing spectrum of disease manifestations. While the principal proteins that cause systemic amyloidosis were initially thought to be derived from immunoglobulin light chain fragments (AL amyloidosis) or from acute phase reactants (AA amyloidosis), it was soon discovered that pre-albumin (now known as transthyretin amyloid or ATTR) was the culprit in familial amyloidotic polyneuropathy2 and cardiomyopathy.3 We now know that ATTR amyloidosis can result from genetically abnormal TTR protein (ATTRm) and, at present, >100 TTR mutations have been identified.4 ATTR amyloidosis can also result from genetically normal or wild-type TTR, resulting in ATTRwt (formerly known as senile cardiac) amyloidosis. Cardiac amyloidosis is an infiltrative cardiomyopathy characterized by increased biventricular wall thickness, restrictive left ventricular (LV) filling, and, often, a non-dilated LV cavity with preserved or mildly depressed LV systolic function.5 AL amyloidosis typically affects multiple organ systems including renal and gastrointestinal systems, with cardiac involvement seen as a common manifestation in up to 70% of cases.6 In contrast, cardiac involvement in ATTRm amyloidosis is variable and depends on the specific mutation.7 While AL cardiac amyloidosis is rightly considered a rare disease (estimated incidence 1:100 000),8 recent evidence suggests that ATTRwt amyloidosis is probably much more common than is widely appreciated in elderly patients with heart failure with preserved ejection fraction (HFpEF).9,10 The diagnosis and appropriate typing of cardiac amyloidosis is critical for the clinical management of these patients so that life-extending chemotherapy can be administered in AL amyloidosis, and the TTR-stabilizing agent tafamidis (Vyndaqel, Pfizer Inc., available in Europe but not the USA) in ATTR amyloidosis. With the development of promising new therapies for systemic amyloidosis, early and accurate diagnosis of the precursor protein has tremendous potential to prolong survival and improve outcomes. Diagnosis is challenging, however, because features of cardiac amyloidosis must be disentangled from other more common ‘hypertrophic’ processes including hypertensive remodelling, hypertrophy in response to aortic stenosis, or hypertrophic cardiomyopathy (HCM). The diagnostic algorithm requires different clinical inputs including history, physical findings, and imaging, including echocardiography, cardiac magnetic resonance imaging (CMR), and, most recently, the highly ATTR-specific bone avid nuclear tracers 99mTc-PYP (pyrophosphate) and 99mTc-DPD (3,3-diphosphono-1,2-propanodicarboxylic acid).11,12 This issue of the journal features two distinct but complementary studies that separately refine the methodology employed for diagnosis of cardiac amyloidosis and identify heretofore less appreciated clinical features of the most common form of the disease (ATTRwt amyloidosis). In the first study, Quarta et al. assessed the diagnostic performance of an abdominal fat aspirate, perhaps the most easily accessible tissue biopsy, for the identification of cardiac amyloidosis.13 While advances in imaging have made it possible to definitively diagnose ATTR cardiac amyloidosis non-invasively, a tissue diagnosis remains important, particularly in AL disease, to confirm the type of the protein involved. In the early 1980s, Libbey and colleagues at Boston University first reported that Congo Red staining of abdominal fat obtained by fine needle aspiration diagnosed amyloidosis in 95% of patients with AL amyloidosis and 86% of patients with ATTRm amyloidosis.14 Unlike cardiac or gastrointestinal biopsy, the procedure is easily performed in the clinical exam room, with local anaesthesia, and minimal complication. Six hundred patients (an exceptionally large cohort) with an established diagnosis of cardiac amyloidosis referred to the National Amyloidosis Centre in London, UK, underwent fine needle aspiration of their abdominal fat. Congo Red staining identified amyloidosis in 84% of patients with AL amyloidosis, as compared with 45% of patients with ATTRm amyloidosis, and only 15% of those with ATTRwt amyloidosis. Immunohistochemistry of the fat aspirates correctly identified light chain fragments in 56% of AL amyloidosis patients who were Congo Red positive (Figure 1). While much smaller studies have examined the feasibility and diagnostic yield of immune techniques as a means to type precursor protein from abdominal fat aspirates,15 the present report is by far the largest to assess the diagnostic sensitivity of Congo Red staining and immunohistochemical typing of abdominal fat aspirates in patients with cardiac amyloidosis. The sensitivity of amyloid detection by fat aspirate in AL amyloidosis patients was proportionate to the burden of systemic amyloidosis by [123I]serum amyloid P (SAP) scintigraphy, suggesting that a larger whole-body amyloid burden increased the likelihood of detection by abdominal fat aspirate. The authors also found that in ATTRm amyloidosis, the specific mutation was associated with the likelihood of positive needle aspirate. As discussed by the authors, this probably reflects the higher systemic burden of amyloid in patients with mutations that cause polyneuropathy and cardiomyopathy (such as Thr60Ala) as opposed to those that cause cardiac-restricted amyloidosis (Val122Ile). Consistent with this observation, patients with cardiac-restricted ATTRwt amyloidosis were unlikely to have positive aspirates, suggesting that for this particular type of disease, further testing, such as CMR, 99mTc-PYP, or 99mTc-DPD, is a necessity. Furthermore, in equivocal cases, for example patients with a positive DPD scan and monoclonal gammopathy (seen in 10% of cases),16,17 an endomyocardial biopsy may be necessary to establish the correct diagnosis. Finally, while the authors report successful typing of the precursor amyloidogenic protein in 47% of all AL cases, 33% of all ATTRm amyloidosis cases, and 10% of all ATTRwt amyloidosis cases by immunohistochemistry, it is important to remember that this technique requires sufficient pathological experience and expertise, and as such a similar diagnostic yield may not be attainable in other centres. Figure 1 Open in new tabDownload slide Salient features of the two studies reviewed in this Editorial. The left panel describes the diagnostic yield from abdominal fat fine needle aspiration in patients with AL, mutant ATTR, and wild-type ATTR cardiac amyloidosis from the study by Quarta et al. The right panel summarizes the main results from the study by Gonzalez-Lopez et al. that revise our present understanding of wild-type ATTR cardiac amyloidosis. In the second study, Gonzalez-Lopez et al. challenge some of the currently held ‘myths’ of ATTRwt cardiac amyloidosis with the report of a retrospective cohort of 108 patients from two amyloid referral centres in Europe (Figure 1).17 Myth #1: ATTRwt amyloidosis is typically held to be most commonly a disease of elderly males, with the average proportion of females in the largest cohorts published to date between 2% and 11%.16,18,19 However, in the current report, 18.5% of the ATTRwt amyloidosis cohort studied were female, suggesting that ATTRwt amyloidosis may be almost twice as common in women than is presently appreciated. Women with ATTRwt amyloidosis were more likely to have been diagnosed by non-invasive 99mTc-DPD scintigraphy (75% of women were diagnosed in this manner), suggesting that the advent and accessibility of this new imaging test may permit a more accurate determination of the true gender distribution of this disease. Interestingly, female cases were also older at the time of symptom onset and diagnosis (by ∼6 years), arguing for a delayed presentation or ‘protective’ effect of gender. Myth #2: cardiac amyloidosis is widely held to be a symmetric wall thickening process as distinct from HCM, which is more commonly asymmetric. In contrast, Gonzalez-Lopez et al. found that LV wall thickening was asymmetric in 23% of patients, as defined by echocardiography. The pattern of asymmetry was not defined further, but is illustrated in figure 4 of this report. While asymmetry mimicking HCM has been reported in AL amyloidosis by echocardiography,20 asymmetry is not well appreciated in ATTRwt amyloidosis, and therefore its presence should no longer be utilized to favour HCM strongly over amyloidosis. In addition, other observations made in this cohort reaffirm the challenge of identification of ATTRwt amyloidosis by standard testing that includes the findings of lower overall LVEF (in fact, 9% of patients had an LVEF <30%) and LV hypertrophy by ECG (10%), both of which are not commonly associated with cardiac amyloidosis. Another important point made by the authors is the high degree of misdiagnosis (35%) prior to accurate ATTRwt amyloidosis diagnosis. Not surprisingly, hypertensive heart disease and HCM were the most frequently made diagnoses prior to the accurate one. On one hand, misdiagnosis clearly results in delay of definitive treatment, and probably negatively impacts mortality. On the other, given the age-dependent penetrance of ATTRwt amyloidosis, it is interesting to consider that prior disease diagnoses were indeed accurate, but that ATTRwt amyloidosis later ensued with advancing age, changing the cardiac pathophysiology. This is likely to be the case with low-gradient aortic stenosis and the observed 6% ATTRwt amyloidosis incidence as has been recently reported.21 With respect to survival, Gonzalez-Lopez et al. observed a median time to death of ∼6.1 years, which is roughly twice that of the Boston University (3.9 years),16 London (2.7 years),18 and Mayo (3.6 years) cohorts.19 This is probably due to a skew of this cohort toward earlier disease, with incidentally identified cases (11%) and a sizeable proportion of asymptomatic patients (18%). As in any chronic disease, the true survival depends upon the time of diagnosis. Through this lens, the findings of Gonzalez-Lopez et al. are encouraging, because they suggest that if diagnosed earlier, survival is indeed likely to be better. Finally, and with more reason for optimism, we can anticipate that administration of ATTR amyloidosis-stabilizing therapy might result in even better outcomes when instituted at earlier stages of disease. Cardiac amyloidosis (particularly ATTRwt and ATTRm amyloidosis) is an important cause of heart failure in the elderly that, as informed by the studies published in this issue, is marked by clinical heterogeneity. Fine needle aspiration of abdominal fat is an easy and relatively reliable method for obtaining a tissue diagnosis, especially in the case of AL amyloidosis. This method is variably sensitive for diagnosis of ATTRm amyloidosis, and particularly insensitive for ATTRwt amyloidosis, yet is certainly advisable as a first site of biopsy before proceeding to more invasive procedures. Integration of the findings reported here with a currently accepted clinical diagnostic algorithm can be found in Figure 2. Early diagnosis and proper classification of cardiac amyloidosis are especially important given that the specific treatments for AL22 and ATTR cardiac amyloidosis23 hold great promise for improving survival in these otherwise fatal diseases. Investigations such as those reported in this issue of the journal advance our understanding of the clinical features of cardiac amyloidosis and provide validation of tools that clinicians can use to diagnose this disease accurately. Figure 2 Open in new tabDownload slide Diagnostic algorithm for cardiac amyloidosis. CAD, coronary artery diseas; DPD, 99mTc 3,3-diphosphono-1,2-propanodicarboxylic acid scan; LC/MS2, liquid chromatography–tandem mass spectrometry; CR, Congo red; LGE, late gadolinium enhancement; LV, left ventricular; MRI, magnetic resonance imaging; Pyrophosphate, 99mTc pyrophosphate scan; SIFE, serum immunofixation electrophoresis; UIFE, urine immunofixation electrophoresis. *Grading scale for pyrophosphate/DPD scans: positive = heart uptake: contralateral lung uptake ratio ≥1.5 (after 1 h) or Perugini visual score of 2 or 3; negative = heart uptake: contralateral lung uptake ratio <1.0 or Perugini visual score of 0; intermediate = heart uptake: contralateral lung uptake ratio between 1.0 and 1.5 or Perugini visual score of 1. Conflicts of interest: F.L.R. is a consultant to Prothena Pharmaceuticals and Alnylam Pharmaceuticals. O.K.S. has no conflicts to declare. References 1 Cohen AS. General introduction and a brief history of the amyloid fibril. In: van Rijswijk MH, Marrink J, eds. Amyloidosis . Dordrecht : Nijhoff ; 1986 . p 3 – 19 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 2 Skinner M , Cohen AS. The prealbumin nature of the amyloid protein in familial amyloid polyneuropathy (FAP)-Ewedish variety . Biochem Biophys Res Commun 1981 ; 99 : 1326 – 1332 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Hesse A , Altland K, Linke RP, Almeida MR, Saraiva MJ, Steinmetz A, Maisch B. Cardiac amyloidosis: a review and report of a new transthyretin (prealbumin) variant . Br Heart J 1993 ; 70 : 111 – 115 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Connors LH , Lim A, Prokaeva T, Roskens VA, Costello CE. Tabulation of human transthyretin (TTR) variants, 2003 . Amyloid 2003 ; 10 : 160 – 184 . Google Scholar Crossref Search ADS PubMed WorldCat 5 Rapezzi C , Merlini G, Quarta CC, Riva L, Longhi S, Leone O, Salvi F, Ciliberti P, Pastorelli F, Biagini E, Coccolo F, Cooke RM, Bacchi-Reggiani L, Sangiorgi D, Ferlini A, Cavo M, Zamagni E, Fonte ML, Palladini G, Salinaro F, Musca F, Obici L, Branzi A, Perlini S. Systemic cardiac amyloidoses: disease profiles and clinical courses of the 3 main types . Circulation 2009 ; 120 : 1203 – 1212 . Google Scholar Crossref Search ADS PubMed WorldCat 6 Muchtar E , Gertz MA, Kumar SK, Lacy MQ, Dingli D, Buadi FK, Grogan M, Hayman SR, Kapoor P, Leung N, Fonder A, Hobbs M, Hwa YL, Gonsalves W, Warsame R, Kourelis TV, Russell S, Lust JA, Lin Y, Go RS, Zeldenrust S, Kyle RA, Rajkumar SV, Dispenzieri A. Improved outcomes for newly diagnosed AL amyloidosis over the years 2000 and 2014: cracking the glass ceiling of early death . Blood 2017 ; 129 : 2111 – 2119 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Ruberg FL , Berk JL. Transthyretin (TTR) cardiac amyloidosis . Circulation 2012 ; 126 : 1286 – 1300 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Kyle RA , Linos A, Beard CM, Linke RP, Gertz MA, O’Fallon WM, Kurland LT. Incidence and natural history of primary systemic amyloidosis in Olmsted County, Minnesota, 1950 through 1989 . Blood 1992 ; 79 : 1817 – 1822 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 9 Mohammed SF , Mirzoyev SA, Edwards WD, Dogan A, Grogan DR, Dunlay SM, Roger VL, Gertz MA, Dispenzieri A, Zeldenrust SR, Redfield MM. Left ventricular amyloid deposition in patients with heart failure and preserved ejection fraction . JACC Heart Fail 2014 ; 2 : 113 – 122 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Gonzalez-Lopez E , Gallego-Delgado M, Guzzo-Merello G, de Haro-Del Moral FJ, Cobo-Marcos M, Robles C, Bornstein B, Salas C, Lara-Pezzi E, Alonso-Pulpon L, Garcia-Pavia P. Wild-type transthyretin amyloidosis as a cause of heart failure with preserved ejection fraction . Eur Heart J 2015 ; 36 : 2585 – 2594 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Gillmore JD , Maurer MS, Falk RH, Merlini G, Damy T, Dispenzieri A, Wechalekar AD, Berk JL, Quarta CC, Grogan M, Lachmann HJ, Bokhari S, Castano A, Dorbala S, Johnson GB, Glaudemans AW, Rezk T, Fontana M, Palladini G, Milani P, Guidalotti PL, Flatman K, Lane T, Vonberg FW, Whelan CJ, Moon JC, Ruberg FL, Miller EJ, Hutt DF, Hazenberg BP, Rapezzi C, Hawkins PN. Nonbiopsy diagnosis of cardiac transthyretin amyloidosis . Circulation 2016 ; 133 : 2404 – 2012 . Google Scholar Crossref Search ADS PubMed WorldCat 12 Castano A , Haq M, Narotsky DL, Goldsmith J, Weinberg RL, Morgenstern R, Pozniakoff T, Ruberg FL, Miller EJ, Berk JL, Dispenzieri A, Grogan M, Johnson G, Bokhari S, Maurer MS. Multicenter study of planar technetium 99m pyrophosphate cardiac imaging: predicting survival for patients with ATTR cardiac amyloidosis . JAMA Cardiol 2016 ; 1 : 880 – 889 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Quarta CC, , Gonzalez-Lopez E,, Gilbertson JA,, Botcher N,, Rowczenio D,, Petrie A,, Rezk T,, Youngstein T,, Mahmood S,, Sachchithanantham S,, Lachmann HJ,, Fontata M,, Whelan CJ,, Wechalekar AD,, Hawkins PN,, Gillmore JD. Diagnostic sensitivity of abdominal fat aspiration in cardiac amyloidosis . Eur Heart J 2017 ; 38 : 1905 – 1908 . Google Scholar Crossref Search ADS WorldCat 14 Libbey CA , Skinner M, Cohen AS. Use of abdominal fat tissue aspirate in the diagnosis of systemic amyloidosis . Arch Intern Med 1983 ; 143 : 1549 – 1552 . Google Scholar Crossref Search ADS PubMed WorldCat 15 Olsen KE , Sletten K, Westermark P. The use of subcutaneous fat tissue for amyloid typing by enzyme-linked immunosorbent assay . Am J Clin Pathol 1999 ; 111 : 355 – 362 . Google Scholar Crossref Search ADS PubMed WorldCat 16 Connors LH , Sam F, Skinner M, Salinaro F, Sun F, Ruberg FL, Berk JL, Seldin DC. Heart failure resulting from age-related cardiac amyloid disease associated with wild-type transthyretin: a prospective, observational cohort study . Circulation 2016 ; 133 : 282 – 290 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 17 González-López E, , Gagliardi C,, Dominguez F,, Quarta CC,, de Haro-Del Moral FJ,, Milandri A,, Salas C,, Cinelli M,, Cobo-Marcos M,, Lorenzini M,, Lara-Pezzi E,, Foffi S,, Alanso-Pulpon L,, Rapezzi C,, Garcia-Pavia P. Clinical characteristics of wild-type transthyretin cardiac amyloidosis: disproving myths . Eur Heart J 2017 ; 38 : 1895 – 1904 . Google Scholar Crossref Search ADS WorldCat 18 Pinney JH, , Whelan CJ,, Petrie A,, Dungu J,, Banypersad SM,, Sattianayagam P,, Wechalekar A,, Gibbs SD,, Venner CP,, Wassef N,, McCarthy CA,, Gilbertson JA,, Rowczenio D,, Hawkins PN,, Gillmore JD,, Lachmann HJ. Senile systemic amyloidosis: clinical features at presentation and outcome . J Am Heart Assoc 2013 ; 2 : e000098 . Google Scholar Crossref Search ADS PubMed WorldCat 19 Grogan M , Scott CG, Kyle RA, Zeldenrust SR, Gertz MA, Lin G, Klarich KW, Miller WL, Maleszewski JJ, Dispenzieri A. Natural history of wild-type transthyretin cardiac amyloidosis and risk stratification using a novel staging system . J Am Coll Cardiol 2016 ; 68 : 1014 – 1020 . Google Scholar Crossref Search ADS PubMed WorldCat 20 Dinwoodey DL , Skinner M, Maron MS, Davidoff R, Ruberg FL. Light-chain amyloidosis with echocardiographic features of hypertrophic cardiomyopathy . Am J Cardiol 2008 ; 101 : 674 – 676 . Google Scholar Crossref Search ADS PubMed WorldCat 21 Treibel TA, , Fontana M,, Gilbertson JA,, Castelletti S,, White SK,, Scully PR,, Roberts N,, Hutt DF,, Rowczenio DM,, Whelan CJ,, Ashworth MA,, Gillmore JD,, Hawkins PN,, Moon JC. Occult transthyretin cardiac amyloid in severe calcific aortic stenosis: prevalence and prognosis in patients undergoing surgical aortic valve replacement . Circ Cardiovasc Imaging 2016 ; 9 : e005066 . Google Scholar Crossref Search ADS PubMed WorldCat 22 Palladini G , Merlini G. What is new in diagnosis and management of light chain amyloidosis? Blood 2016 ; 128 : 159 – 168 . Google Scholar Crossref Search ADS PubMed WorldCat 23 Mohty D , Damy T, Cosnay P, Echahidi N, Casset-Senon D, Virot P, Jaccard A. Cardiac amyloidosis: updates in diagnosis and management . Arch Cardiovasc Dis 2013 ; 106 : 528 – 540 . Google Scholar Crossref Search ADS PubMed WorldCat Author notes The opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology. † doi:10.1093/eurheartj/ehx047. ‡ doi:10.1093/eurheartj/ehx043. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected]. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Jhund, Pardeep S.

doi: 10.1093/eurheartj/ehw357pmid: 28369264

This editorial refers to ‘Body weight in adolescence and long-term risk of early heart failure in adulthood among men in Sweden’†, by A. Rosengren et al. on page 1926. The growing burden of obesity has been referred to as an ‘epidemic’. The World Health Organization estimates that 50% of adults living in Europe are overweight or obese,1 a population approximately equivalent to that of Germany, France, the UK, and Italy put together. This concerning statistic is made more terrifying by the data presented by Rosengren et al.2 in this issue of the journal. They examined the association between body weight mass and the development of heart failure in >1.5 million young men (mean age 18.6 years). They report that the incidence of heart failure in these young men, who had their body mass index (BMI) calculated as part of the physical examination for national service, was 5–7 per 100 000 person-years of follow-up in those of normal weight, rising to 12–40 per 100 000 person-years of follow-up in those who were overweight or obese as defined by their BMI. The risk of developing heart failure was nine times higher in the highest BMI category (≥35 kg/m2) compared with those with normal BMI even after adjustment. Behind this relatively simple (and perhaps unsurprising) message lies a complex story that underscores the difficulty we have in dealing with the obesity epidemic. Compared with those who were normal weight, in those who were obese, the relative risk of developing heart failure was higher than the risk of experiencing a myocardial infarction (MI) or stroke. This suggests that there may be a closer association between BMI and heart failure than either stroke or MI. Given that heart failure is commonly caused by ischaemic heart disease, this finding is somewhat counterintuitive. We might expect BMI to be more strongly linked to the most common precursor of heart failure, atherosclerotic heart disease, than heart failure itself. Obesity is associated with diabetes, high cholesterol, and inflammation, all risk factors for the development of atherosclerosis. However, there is evidence linking obesity directly to heart failure. Obesity has a number of effects on the cardiovascular system (Figure 1). Many of these are direct effects on the myocardium and are linked to the development of heart failure. Left ventricular mass and left atrial volume increase with increasing BMI, as does the degree of diastolic and systolic dysfunction,3 and ongoing myocardial injury may be detectable with newer high sensitivity troponin assays.4 Higher BMI is also associated with higher cardiac output, increased blood volume, and alterations in pressure–volume relationships in the heart that deal with these changes.5 Activation of various inflammatory pathways may explain some of the relationship between obesity and heart failure.6 Finally, cardiac steatosis is a recognized complication of obesity. Deposition of fat in the myocardium leads to progressive fibrosis, further altering cardiac function.7 Contrast this to the associations between obesity and ischaemic heart disease which are less direct (Figure 1). Although not all atherosclerotic disease culminates in a myocardial infarction, autopsy findings of young military personnel confirm that increasing BMI is associated with a greater burden of atherosclerosis.8 Therefore, despite the evidence linking obesity directly to the development of heart failure, could the association between obesity and heart failure simply be confounded by ischaemic heart disease? Figure 1 Open in new tabDownload slide Pathways linking obesity to the development of heart failure. Figure 1 Open in new tabDownload slide Pathways linking obesity to the development of heart failure. In the analysis by Rosengren et al.,2 subgroup and secondary analyses were used to explore this issue. The association between BMI and heart failure was examined according to the aetiology of heart failure. The risk of heart failure with a secondary diagnosis of coronary heart disease, hypertension, or diabetes mellitus was higher than the risk of heart failure without any of these diagnoses. For every one unit increase in BMI, the risk of heart failure, that occurred with coronary heart disease, diabetes, or hypertension was 1.21 [95% confidence interval (CI) 1.19–1.22]. Although this was stronger than the association between BMI and heart failure due to cardiomyopathy, i.e. heart failure without an obvious aetiology and intermediary pathway, [hazard ratio (HR) 1.11, 95% CI 1.08–1.14], the population-attributable fraction for obesity and heart failure due to cardiomyopathy was 15.4%, suggesting that the direct link between obesity and the development of heart failure is a substantial issue at a population level. However, we must be careful when trying to draw conclusions from these data, no matter how careful the analyses. The competing risk of death was not taken into account, nor was the occurrence of MI or other risk factors for heart failure occurring in the intervening period. Other findings from the analyses also merit consideration when interpreting these data. The mean age at diagnosis of heart failure (which was defined as a hospitalization for heart failure) was only 46 years. This may be a function of the length of follow-up of this young cohort, but it is much younger than in other cohorts that report the mean age at diagnosis.9,–11 Furthermore, the aetiology of heart failure in the young tends to be very different from that in the old.12 There were no data on other metrics of obesity such as waist and hip circumference. The distribution of body fat may be important in determining risk.13 This may be especially important in women whose body fat distribution is different from that of men. Similarly, there may be ethnic differences in body composition and the response to obesity that are important. Despite these limitations, how can we translate these epidemiological analyses into practice? Perhaps the most difficult and most important issue raised by the analyses is what is the ideal BMI? Although a number of interventions, at an individual and population level, are being explored as potential treatments for the obesity epidemic, what BMI should these interventions aim for? At a population level, the answer would seem to be a BMI of <22.5 kg/m2 in young men. Even a BMI in the range of 22.5 to < 25 kg/m2, which is classed as normal, was associated with a 58% higher risk of heart failure. Given that this group constituted nearly a quarter of the population studied, the absolute numbers of heart failure events in this group was one of the largest. The same was observed for MI (and to a lesser extent for stroke). The burden of heart failure, MI, and stroke was greatest in the group with a BMI in the higher range of normal. Given these observations, should the ‘normal’ range be redefined? Do BMI targets for weight loss interventions need to be lowered? However being underweight (BMI <18.5 kg/m2) was associated with a higher risk of events. Therefore, what happens to a person’s risk if they lose too much weight? Without further studies, on more heterogeneous populations, who are more fully characterized (allowing for more complete multivariable adjustment of potential confounders), these questions remain difficult to answer. While Rosengren et al.2 have presented a salutary warning, as with all good research they raise more questions than they have answered. We must gain a better understanding of how the population-level changes in the distribution of body mass are likely to influence rates of cardiovascular disease in the future. Otherwise we are in danger of finding ourselves dealing with both an obesity epidemic and the resurrection of epidemics of cardiovascular diseases that we had thought had begun to subside.9,–11,14 Conflict of interest: none declared. References 1 http://www.euro.who.int/en/health-topics/noncommunicable-diseases/obesity/data-and-statistics (30 May 2016). 2 Rosengren A, , Åberg M, Robertson J, Waern M, Schaufelberger M, Kuhn G, Åberg D, Schiöler L, Torén K. Body weight in adolescence and long-term risk of early heart failure in adulthood among men in Sweden . Eur Heart J 2017 ; 38 : 1926 – 1933 . OpenURL Placeholder Text WorldCat 3 Alpert MA , Lambert CR, Panayiotou H, Terry BE, Cohen MV, Massey CV, Hashimi MW, Mukerji V. Relation of duration of morbid obesity to left ventricular mass, systolic function, and diastolic filling, and effect of weight loss . Am J Cardiol 1995 ; 76 : 1194 – 1197 . 4 Ndumele CE , Coresh J, Lazo M, Hoogeveen RC, Blumenthal RS, Folsom AR, Selvin E, Ballantyne CM, Nambi V. Obesity, subclinical myocardial injury, and incident heart failure . JACC Heart Fail 2014 ; 2 : 600 – 607 . Google Scholar Crossref Search ADS PubMed WorldCat 5 Schwarzl M , Ojeda F, Zeller T, Seiffert M, Becher PM, Munzel T, Wild PS, Blettner M, Lackner KJ, Pfeiffer N, Beutel ME, Blankenberg S, Westermann D. Risk factors for heart failure are associated with alterations of the LV end-diastolic pressure–volume relationship in non-heart failure individuals: data from a large-scale, population-based cohort . Eur Heart J 2016 ; 37 : 1807 – 1814 . Google Scholar Crossref Search ADS PubMed WorldCat 6 Bahrami H , Bluemke DA, Kronmal R, Bertoni AG, Lloyd-Jones DM, Shahar E, Szklo M, Lima JA. Novel metabolic risk factors for incident heart failure and their relationship with obesity: the MESA (Multi-Ethnic Study of Atherosclerosis) study. J Am Coll Cardiol 2008 ; 51 : 1775 – 1783 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Schulze PC , Drosatos K, Goldberg IJ. Lipid use and misuse by the heart . Circ Res 2016 ; 118 : 1736 – 1751 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Webber BJ , Seguin PG, Burnett DG, Clark LL, Otto JL. Prevalence of and risk factors for autopsy-determined atherosclerosis among US service members, 2001–2011 . JAMA 2012 ; 308 : 2577 – 2583 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Jhund PS , Macintyre K, Simpson CR, Lewsey JD, Stewart S, Redpath A, Chalmers JWT, Capewell S, McMurray JJV. Long-term trends in first hospitalization for heart failure and subsequent survival between 1986 and 2003: a population study of 5.1 million people . Circulation 2009 ; 119 : 515 – 523 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Shafazand M , Schaufelberger M, Lappas G, Swedberg K, Rosengren A. Survival trends in men and women with heart failure of ischaemic and non-ischaemic origin: data for the period 1987–2003 from the Swedish Hospital Discharge Registry . Eur Heart J. 2009 ; 30 : 671 – 678 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Wasywich CA , Gamble GD, Whalley GA, Doughty RN. Understanding changing patterns of survival and hospitalization for heart failure over two decades in New Zealand: utility of ‘days alive and out of hospital’ from epidemiological data . Eur J Heart Fail 2010 ; 12 : 462 – 468 . Google Scholar Crossref Search ADS PubMed WorldCat 12 Wong CM , Hawkins NM, Petrie MC, Jhund PS, Gardner RS, Ariti CA, Poppe KK, Earle N, Whalley GA, Squire IB, Doughty RN, McMurray JJV; MAGGIC Investigators . Heart failure in younger patients: the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) . Eur Heart J 2014 ; 35 : 2714 – 2721 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Lee CM , Huxley RR, Wildman RP, Woodward M. Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 2008 ; 61 : 646 – 653 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Fox KA , Després JP, Richard AJ, Brette S, Deanfield JE; IDEA Steering Committee and National Co-ordinators . Does abdominal obesity have a similar impact on cardiovascular disease and diabetes? A study of 91 246 ambulant patients in 27 European countries. Eur Heart J 2009 ; 30 : 3055 – 3063 . Google Scholar Crossref Search ADS WorldCat Author notes " The opinions expressed in this article are not necessarily those of the Editors of the European Heart Journal or of the European Society of Cardiology. † " doi:10.1093/eurheartj/ehw221. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For Permissions, please email: [email protected].

Lüscher, Thomas F.

doi: 10.1093/eurheartj/ehx323pmid: 28863465

The prevalence and incidence of chronic heart failure have increased over the last decades due to increasing longevity of the population,1 chronic and not well controlled hypertension in many,2,3 increased survival after myocardial infarction,4 and recently the obesity epidemic.5 Besides the heart and its pump function, renal function is crucially involved in this syndrome and of relevance for its management.6 As pointed out in a clinical review entitled ‘Renal sodium avidity in heart failure: from pathophysiology to treatment strategies’ by Wilfried Mullens and colleagues from the Ziekenhuis Oost Limburg in Genk, Belgium, increased neurohumoral stimulation results in excessive sodium avidity and extracellular volume overload in decompensated heart failure.7 In the presence of renal dysfunction which often is present in such patients, the kidneys fail to provide effective natriuresis. Of note, serum creatinine—a surrogate for glomerular filtration—only represents part of the nephron’s function. Alterations in tubular sodium handling are equally important in the development of volume overload and congestion. Venous congestion and neurohumoral activation in advanced heart failure further promote renal sodium and water retention. Interestingly, even before clinical signs of heart failure are evident, intrinsic renal derangements already impair natriuresis. A better understanding of cardiorenal interactions which ultimately result in sodium avidity in heart failure might help to treat and prevent congestion in chronic and acute heart failure. A recently discussed risk factor for heart failure is obesity. The obesity epidemic is of great concern not only in adults, but also in children and adolescents.8 However, the impact of body weight in children and adolescents on the risk of developing heart failure in the long run is not known. In an article entitled ‘Body weight in adolescence and long-term risk of early heart failure in adulthood among men in Sweden’, Annika Rosengren from the Sahlgrenska University Hospital at Östra in Gothenburg, Sweden studied the relationship between body mass index and risk of early hospitalization due to heart failure in a prospective cohort of 1 610 437 young men 19 years of age followed for a median of 23 years.9 Overall, 5492 first hospitalizations for heart failure occurred at a mean age of 47 years. Compared with men with a body mass index of 18.5–20.0 kg/m2, men with a body mass index of 20.0–22.5 kg/m2 had an adjusted hazard ratio of 1.22. The risk rose incrementally with increasing body mass index such that men with a body mass index of 30–35 kg/m2 had an adjusted hazard ratio of 6.40 and those with a body mass index of ≥35 kg/m2 one of 9.53. The multiple-adjusted risk of heart failure per 1 unit increase in body mass index ranged from 1.06 in heart failure associated with valvular disease to 1.21 for cases associated with coronary heart disease, diabetes, or hypertension. There was a steeply rising risk of early heart failure detectable already at a normal body weight, increasing nearly 10-fold in the highest weight category. Given the current obesity epidemic, heart failure in the young may thus increase markedly in the future. The implications of these findings for weight management and prevention are reviewed in an Editorial by Pardeep Jhund from the University of Glasgow in Scotland.10 Heart failure may be due to ischaemia and infarction,11 valvular or congenital heart disease,12 as well as myocyte dysfunction13 or deposition of proteins and other molecules within the myocardial tissue. Infiltrative myocardial dysfunction is typical for different forms of amyloidosis.14 The diagnosis of amyloidosis is challenging, however; although typical echocardiographic findings may be leading to diagnosis, definitive confirmation requires detection of the protein in tissue. Although Congo red staining of an endomyocardial biopsy is the diagnostic gold standard in suspected cardiac amyloidosis, the procedure is invasive, and potentially associated with complications and sample bias. Thus, fat pad fine needle aspiration has been introduced for the work up of such patients. In an EHJ Brief Communication ‘Diagnostic sensitivity of abdominal fat aspiration in cardiac amyloidosis’, Julian Gillmore and colleagues from the University College London Medical School in London, UK note that although abdominal fat pad fine needle aspiration is a simple, safe, and well-established procedure in systemic amyloidosis, its diagnostic sensitivity in suspected cardiac amyloidosis has not been established.15 The authors therefore assessed the diagnostic sensitivity of fat pad fine needle aspiration in 600 consecutive patients diagnosed with cardiac amyloidosis, i.e. 216 amyloid light-chain, 113 hereditary transthyretin, and 271 wild-type transthyretin amyloidosis. Amyloid was detected on Congo red staining of fat pad fine needle aspirations in 84% patients with cardiac light-chain amyloidosis, including 100, 97, and 78% of those with a large, moderate, and small whole-body amyloid burden, respectively, as assessed by serum amyloid P component scintigraphy. The deposits were successfully typed as amyloid light-chain by immunohistochemistry in 47% of the cases. Amyloid was detected in fat pad fine needle aspirations of 45% with hereditary transthyretin cardiac amyloidosis, and in only 15% with wild-type transthyretin cardiac amyloidosis. The authors conclude that fat pad fine needle aspiration has reasonable diagnostic sensitivity in cardiac light-chain amyloidosis, particularly in patients with a large whole-body amyloid burden. The diagnostic sensitivity of fat pad fine needle aspiration is substantially lower in transthyretin cardiac amyloidosis, particularly wild-type transthyretin amyloidosis. The diagnostic implications of these findings are discussed in an Editorial by Frederick Ruberg from the Boston University School of Medicine in Massachusetts, USA.16 This issue is further discussed in an article entitled ‘Clinical characteristics of wild-type transthyretin cardiacamyloidosis: disproving myths’ by Pablo Garcia-Pavia and colleagues from the Hospital Universitario Puerta de Hierro in Majadahonda, in Madrid.17 They remind us that wild-type transthyretin amyloidosis is mostly considered a disease predominantly of elderly males, characterized by concentric left ventricular hypertrophy, preserved left ventricular ejection fraction, and low QRS voltages.14 They therefore sought to describe the characteristics of a large cohort of wild-type transthyretin amyloidosis patients to better define the disease. Wild-type transthyretin amyloidosis was diagnosed histologically or non-invasively based on left ventricular hypertrophy of ≥12 mm, intense cardiac uptake at 99mTc-DPD scintigraphy, and exclusion of amyloid light-chain amyloidosis. Mutations in transthyretin were excluded in all 108 cases. An asymmetric hypertrophy pattern was observed in 23% (Figure 1). Left ventricular ejection fraction was 52%, with 37% presenting with a value <50%. On ECG, 56% had atrial fibrillation and 63% had a pseudo-infarct pattern. Only 20% fulfilled QRS low-voltage criteria, while 9% showed left ventricular hypertrophy. Although heart failure was the leading symptom to diagnosis in 68%, 7% presented with atrioventricular block and 11% were diagnosed incidentally. Almost one-third were previously misdiagnosed. Thus, the clinical spectrum of wild-type transthyretin amyloidosis is heterogeneous and differs from the classic phenotype in that women are affected in a significant proportion, asymmetric left ventricular hypertrophy and impaired ejection fraction are not rare, and only a minority have low QRS voltages. Clinicians should therefore be aware of the broad clinical spectrum of wild-type transthyretin amyloidosis to identify correctly an entity for which several disease-modifying treatments are under investigation. The implications of these findings are further discussed in the Editorial by Frederick Ruberg cited above.16 Figure 1 Open in new tabDownload slide Asymmetric left ventricular hypertrophy. Echocardiographic parasternal basal (A) and mid cavity (B) short axis views showing asymmetric left ventricular hypertrophy with anteroseptal predominance and a trace of posterior pericardial effusion. (From González-López E, Gagliardi C, Dominguez F, Quarta CC, de Haro-del Moral JF, Milandri A, Salas C, Cinelli M, Cobo-Marcos M, Lorenzini M, Lara-Pezzi E, Foffi S, Alonso-Pulpon L, Rapezzi C, Garcia-Pavia P. Clinical characteristics of wild-type transthyretin cardiac amyloidosis: disproving myths. See pages: 1895–1904). Figure 1 Open in new tabDownload slide Asymmetric left ventricular hypertrophy. Echocardiographic parasternal basal (A) and mid cavity (B) short axis views showing asymmetric left ventricular hypertrophy with anteroseptal predominance and a trace of posterior pericardial effusion. (From González-López E, Gagliardi C, Dominguez F, Quarta CC, de Haro-del Moral JF, Milandri A, Salas C, Cinelli M, Cobo-Marcos M, Lorenzini M, Lara-Pezzi E, Foffi S, Alonso-Pulpon L, Rapezzi C, Garcia-Pavia P. Clinical characteristics of wild-type transthyretin cardiac amyloidosis: disproving myths. See pages: 1895–1904). The major haemodynamic mechanism of heart failure is pressure or volume overload.18 Of note, short-term studies have reported left ventricular dilatation following surgical creation of arteriovenous fistulas or arteriovenous grafts in renal patients, but chronic cardiac structural and functional changes have not been examined or related to clinical outcomes. In their article ‘Long-term cardiovascular changes following creation of arteriovenous fistulasin patients withend-stage renal disease’, Barry A. Borlaug and colleagues from the Mayo Clinic in Rochester, MN, USA characterized the long-term changes in cardiac structure and function in 137 renal patients undergoing shunt creation for haemodialysis.19 Following arteriovenous fistulas and dialysis initiation, there were reductions in blood pressure, body weight, and estimated plasma volume, coupled with modest reverse left ventricular remodelling. In contrast, arteriovenous fistula or arteriovenous graft creation was associated with significant right ventricular dilatation and deterioration in right ventricular function. Incident heart failure developed in 43% of patients in concordance with right ventricular remodelling. The development of right ventricular dilation following surgical arteriovenous fistulas or arteriovenous grafts was independently associated with increased risk of death, with a hazard ratio of 3.9. Thus, right ventricular remodelling and dysfunction develops following creation of arteriovenous fistulas or arteriovenous grafts and dialysis initiation, despite improved control of left ventricular pressure load through dialysis. The deleterious effects on right heart structure and function are coupled with the development of incident heart failure and increased risk of death. These findings may also have important implications for the evaluation of the recently introduced central arteriovenous fistula procedure for resistant hypertension.20 Further implications of these provocative findings are discussed to an Editorial by Peter A. McCullough from Baylor University Medical Center at Dallas in Texas.21 Morbidity and mortality from chronic heart failure has been substantially reduced over the last decades due to the introduction of inhibitors of the renin–angiotensin system, particularly if combined with a neprilysin inhibitor,22 beta-blockers, and aldosterone antagonists,23 as well as more recently cardiac resynchronization therapy.24 However, despite clear guidelines recommendations, most patients with heart failure and reduced ejection fraction do not attain guideline-recommended target dosages25 of live-saving drugs. In their research article ‘Determinants and clinical outcome of up-titration of ACE-inhibitorsand beta-blockersin patients with heart failure: a prospective European study’, Adriaan Voors and colleagues from the University Medical Center Groningen in The Netherlands report the results of BIOSTAT-CHF analysing 2516 heart failure patients from 69 centres in 11 European countries during 21 months. They investigated characteristics and treatment indication bias-corrected clinical outcome of patients with heart failure and reduced ejection fraction that did not reach recommended treatment doses of ACE inhibitors, angiotensin receptor blockers, and/or beta-blockers.26 Of the eventually 2100 patients with heart failure and reduced ejection fraction available, only 22% achieved the recommended treatment dosages for ACE inhibitors or angiotensin receptor antagonists and 12% for beta-blockers. Reaching <50% of the recommended ACE inhibitor, angiotensin receptor antagonist, and beta-blocker dose was associated with an increased risk of death and/or heart failure hospitalization. Patients reaching 50–99% of the recommended ACE inhibitor, angiotensin receptor antagonist, and/or beta-blocker dose had risk of death and/or heart failure hospitalization comparable with those reaching 100% (Figure 2). Patients not reaching recommended dosages because of symptoms, side effects, and non-cardiac organ dysfunction had the highest mortality rate, with a hazard ratio for an ACE inhibitor or angiotensin receptor antagonist of 1.72, and 1.70 for beta-blockers. The authors conclude that patients with heart failure and reduced ejection fraction who were treated with <50% of recommended dosages of ACE inhibitors or angiotensin receptor blockers and beta-blockers have a greater risk of death and/or heart failure hospitalization compared with those reaching target dosages. These clinically important findings are discussed in an Editorial by Luigi Tavazzi from the Maria Cecilia Hospital in Cotignola, Italy.27 Figure 2 Open in new tabDownload slide Adjusted mortality rate for patients achieving or ≥ 100% for both ACE-inhibitor and angiotensin receptor blockers and beta-blocker recommended dose, ≥50% recommended ACE-inhibitor and beta-blocker dose, ≥50% of at least ACE-inhibitor and angiotensin receptor blockers or beta-blocker recommended dose, and for patients achieving <50% of recommended ACE-inhibitor/ARB and beta-blocker dose. (From Ouwerkerk W, Voors AA, Anker SD, Cleland JG, Dickstein K, Filippatos G, van der Harst P, Hillege HL, Lang CC, ter Maaten JM, Ng LL, Ponikowski P, Samani NJ, van Veldhuisen DJ, Zannad F, Metra M, Zwinderman AH. Determinants and clinical outcome of uptitration of ACE-inhibitor and beta-blocker in patients with heart failure: a prospective European study. See pages: 1883–1890). Figure 2 Open in new tabDownload slide Adjusted mortality rate for patients achieving or ≥ 100% for both ACE-inhibitor and angiotensin receptor blockers and beta-blocker recommended dose, ≥50% recommended ACE-inhibitor and beta-blocker dose, ≥50% of at least ACE-inhibitor and angiotensin receptor blockers or beta-blocker recommended dose, and for patients achieving <50% of recommended ACE-inhibitor/ARB and beta-blocker dose. (From Ouwerkerk W, Voors AA, Anker SD, Cleland JG, Dickstein K, Filippatos G, van der Harst P, Hillege HL, Lang CC, ter Maaten JM, Ng LL, Ponikowski P, Samani NJ, van Veldhuisen DJ, Zannad F, Metra M, Zwinderman AH. Determinants and clinical outcome of uptitration of ACE-inhibitor and beta-blocker in patients with heart failure: a prospective European study. See pages: 1883–1890). The editors hope that readers of this issue of the European Heart Journal will find it of interest to them. References 1 Camici GG , Savarese G, Akhmedov A, Luscher TF. Molecular mechanism of endothelial and vascular ageing: implications for cardiovascular disease . Eur Heart J 2015 ; 36 : 3392 – 3403 . Google Scholar Crossref Search ADS PubMed WorldCat 2 Luscher TF , Sudano I. SPRINT: the race for optimal blood pressure control . Eur Heart J 2016 ; 37 : 937 – 941 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Mancia G , Kjeldsen SE, Zappe DH, Holzhauer B, Hua TA, Zanchetti A, Julius S, Weber MA. Cardiovascular outcomes at different on-treatment blood pressures in the hypertensive patients of the VALUE trial . Eur Heart J 2016 ; 37 : 955 – 964 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Bebb O , Hall M, Fox KAA, Dondo TB, Timmis A, Bueno H, Schiele F, Gale CP. Performance of hospitals according to the ESC ACCA quality indicators and 30-day mortality for acute myocardial infarction: national cohort study using the United Kingdom Myocardial Ischaemia National Audit Project (MINAP) register . Eur Heart J 2017 ; 38 : 974 – 982 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 5 Persson CE , Bjorck L, Lagergren J, Lappas G, Giang KW, Rosengren A. Risk of heart failure in obese patients with and without bariatric surgery in Sweden—a registry-based study . J Cardiac Fail 2017 ;doi: 10.1016/j.cardfail.2017.05.005. OpenURL Placeholder Text WorldCat 6 van Veldhuisen DJ , Ruilope LM, Maisel AS, Damman K. Biomarkers of renal injury and function: diagnostic, prognostic, and therapeutic implications in heart failure . Eur Heart J 2016 ; 37 : 2577 – 2585 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Mullens W, , Verbrugge FH,, Nijst P,, Tang WHW. Renal sodium avidity in heart failure: from pathophysiology to treatment strategies . Eur Heart J 2017 ; 38 : 1872 – 1882 . OpenURL Placeholder Text WorldCat 8 Ayer J , Charakida M, Deanfield JE, Celermajer DS. Lifetime risk: childhood obesity and cardiovascular risk . Eur Heart J 2015 ; 36 : 1371 – 1376 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Rosengren A, , Åberg M,, Robertson J,, Waern M,, Schaufelberger M,, Kuhn G, Åberg D,, Schiöler L,, Torén K. Body weight in adolescence and long-term risk of early heart failure in adulthood among men in Sweden . Eur Heart J 2017 ; 38 : 1926 – 1933 . OpenURL Placeholder Text WorldCat 10 Jhund PS. Obesity and heart failure: when ‘epidemics’ collide . Eur Heart J 2017 ; 38 : 1934 – 1936 . OpenURL Placeholder Text WorldCat 11 Wang N , Hung CL, Shin SH, Claggett B, Skali H, Thune JJ, Køber L, Shah A, McMurray JJ, Pfeffer MA, Solomon SD; VALIANT Investigators . Regional cardiac dysfunction and outcome in patients with left ventricular dysfunction, heart failure, or both after myocardial infarction . Eur Heart J 2016 ; 37 : 466 – 472 . Google Scholar Crossref Search ADS PubMed WorldCat 12 Cohen S , Houyel L, Guillemain R, Varnous S, Jannot AS, Ladouceur M, Boudjemline Y, Bonnet D, Iserin L. Temporal trends and changing profile of adults with congenital heart disease undergoing heart transplantation . Eur Heart J 2016 ; 37 : 783 – 789 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Elliott P , Charron P, Blanes JR, Tavazzi L, Tendera M, Konté M, Laroche C, Maggioni AP; EORP Cardiomyopathy Registry Pilot Investigators . European Cardiomyopathy Pilot Registry: EURObservational Research Programme of the European Society of Cardiology . Eur Heart J 2016 ; 37 : 164 – 173 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Damy T , Costes B, Hagege AA, Donal E, Eicher JC, Slama M, Guellich A, Rappeneau S, Gueffet JP, Logeart D, Planté-Bordeneuve V, Bouvaist H, Huttin O, Mulak G, Dubois-Randé JL, Goossens M, Canoui-Poitrine F, Buxbaum JN. Prevalence and clinical phenotype of hereditary transthyretin amyloid cardiomyopathy in patients with increased left ventricular wall thickness . Eur Heart J 2016 ; 37 : 1826 – 1834 . Google Scholar Crossref Search ADS PubMed WorldCat 15 Quarta CC, , Gonzalez-Lopez E,, Gilbertson JA,, Botcher N,, Rowczenio D,, Petrie A,, Rezk T,, Youngstein T,, Mahmood S,, Sachchithanantham S,, Lachmann HJ,, Fontata M,, Whelan CJ,, Wechalekar AD,, Hawkins PN,, Gillmore JD. Diagnostic sensitivity of abdominal fat aspiration in cardiac amyloidosis . Eur Heart J 2017 ; 38 : 1905 – 1908 . OpenURL Placeholder Text WorldCat 16 Siddiqi OK , Ruberg FL. Challenging the myths of cardiac amyloidosis . Eur Heart J 2017 ; 38 : 1909 – 1912 . OpenURL Placeholder Text WorldCat 17 González-López E, , Gaglardi C,, Dominguez F,, Quarta CC,, de Haro-del Moral JF,, Milandri A,, Salas C,, Cinelli M,, Cobo-Marcos M,, Lorenzini M,, Lara-Pezzi E,, Foffi S,, Alanso-Pulpon L,, Rapezzi C,, Garcia-Pavia P. Clinical characteristics of wild-type transthyretin cardiac amyloidosis: disproving myths . Eur Heart J 2017 ; 38 : 1895 – 1904 . OpenURL Placeholder Text WorldCat 18 Schwarzl M , Ojeda F, Zeller T, Seiffert M, Becher PM, Munzel T, Wild PS, Blettner M, Lackner KJ, Pfeiffer N, Beutel ME, Blankenberg S, Westermann D. Risk factors for heart failure are associated with alterations of the LV end-diastolic pressure–volume relationship in non-heart failure individuals: data from a large-scale, population-based cohort . Eur Heart J 2016 ; 37 : 1807 – 1814 . Google Scholar Crossref Search ADS PubMed WorldCat 19 Reddy YNV, , Obokata M,, Dean PG,, Melenovsky V,, Nath KA,, Borlaug BA. Long-term cardiovascular changes following creation of arteriovenous fistula in patients with end stage renal disease . Eur Heart J 2017 ; 38 : 1913 – 1923 . OpenURL Placeholder Text WorldCat 20 Lobo MD , Sobotka PA, Stanton A, Cockcroft JR, Sulke N, Dolan E, van der Giet M, Hoyer J, Furniss SS, Foran JP, Witkowski A, Januszewicz A, Schoors D, Tsioufis K, Rensing BJ, Scott B, Ng GA, Ott C, Schmieder RE; ROX CONTROL HTN Investigators . Central arteriovenous anastomosis for the treatment of patients with uncontrolled hypertension (the ROX CONTROL HTN study): a randomised controlled trial . Lancet 2015 ; 385 : 1634 – 1641 . Google Scholar Crossref Search ADS PubMed WorldCat 21 McCullough PA, , Rios A,, Smith B. Dialysis fistulas and heart failure . Eur Heart J 2017 ; 38 : 1924 – 1925 . OpenURL Placeholder Text WorldCat 22 Bohm M , Young R, Jhund PS, Solomon SD, Gong J, Lefkowitz MP, Rizkala AR, Rouleau JL, Shi VC, Swedberg K, Zile MR, Packer M, McMurray JJV. Systolic blood pressure, cardiovascular outcomes, and efficacy and safety of sacubitril/valsartan (LCZ696) in patients with chronic heart failure and reduced ejection fraction: results from PARADIGM-HF . Eur Heart J 2017 ; 38 : 1132 – 1143 . Google Scholar Crossref Search ADS PubMed WorldCat 23 Solomon SD , Claggett B, Lewis EF, Desai A, Anand I, Sweitzer NK, O’Meara E, Shah SJ, McKinlay S, Fleg JL, Sopko G, Pitt B, Pfeffer MA; TOPCAT Investigators . Influence of ejection fraction on outcomes and efficacy of spironolactone in patients with heart failure with preserved ejection fraction . Eur Heart J 2016 ; 37 : 455 – 462 . Google Scholar Crossref Search ADS PubMed WorldCat 24 Boriani G, , Diemberger I. Cardiac resynchronization therapy in the real world: need to focus on implant rates, patient selection, co-morbidities, type of devices, and complications . Eur Heart J 2017 ;doi: 10.1093/eurheartj/ehx137. OpenURL Placeholder Text WorldCat 25 Ponikowski P , Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, González-Juanatey JR, Harjola VP, Jankowska EA, Jessup M, Linde C, Nihoyannopoulos P, Parissis JT, Pieske B, Riley JP, Rosano GM, Ruilope LM, Ruschitzka F, Rutten FH, van der Meer P; Authors/Task Force Members . 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC . Eur Heart J 2016 ; 37 : 2129 – 2200 . Google Scholar Crossref Search ADS PubMed WorldCat 26 Ouwerkerk W, , Voors AA,, Anker SD,, Cleland JG,, Dickstein K,, Filippatos G, van der Harst P, Hillege HL, Lang CC, ter Maaten JM, Ng LL, Ponikowski P, Samani NJ, van Veldhuisen DJ, Zannad F, Metra M, Zwinderman AH. Determinants and clinical outcome of uptitration of ACE-inhibitors and beta-blockers in patients with heart failure: a prospective European study . Eur Heart J 2017 ; 38 : 1883 – 1890 . OpenURL Placeholder Text WorldCat 27 Tavazzi L. Observational research as a platform for evidence-based public health policies and learning health systems . Eur Heart J 2017 ; 38 : 1891 – 1894 . OpenURL Placeholder Text WorldCat Author notes " With thanks to Amelia Meier-Batschelet for help with compilation of this article. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Shah, Rashmee U.; Rumsfeld, John S.

doi: 10.1093/eurheartj/ehx284pmid: 28863461

Will big data lead to big improvements in cardiovascular care?  A 36-year-old woman presents with dyspnoea and dizziness. The clinician orders blood tests, an echocardiogram, an electrocardiogram, and documents the history in the electronic health record. A computer algorithm finds the patient’s prior test results, her genetic profile and demographic characteristics, and links in her wearable biosensor data. The algorithm creates a unique phenotype by processing all of the data sources, compares it with one million other patients, and suggests to the provider that the patient has hypertrophic cardiomyopathy, with an 83% predicted probability of sudden cardiac death in the next 10 years. The information supports an accurate and efficient diagnosis and provides individualized risk to inform shared decision making for a potential implantable cardioverter defibrillator (ICD). This scenario illustrates the promise of big data for cardiovascular clinicians—an automated system combining seemingly disparate data from various sources to provide decision support for diagnosis and treatment, as well as individualized, high-accuracy predictive analytics. How realistic is this future? Big data analytics—and more generally the field of data science—are not new. Other industries have already capitalized on the explosion in data availability, computing power, and analytic methods like machine learning. Yet the ‘big data era’ in healthcare is just beginning.1,2 Big data analytics support the concept of artificial intelligence and lie at the heart of many new digital health platforms and precision health tools. Ideally, utilization of big data analytic tools in cardiovascular care will translate into better care and outcomes at a lower cost. It is not yet clear, however, to what degree the promise will be fulfilled. In this brief article, we highlight three promising applications for big data in cardiovascular care, followed by ‘proof of concept’ challenges to be met if the promise of big data is to be realized. The promise of predictive analytics, phenomapping, and precision health The potential for more powerful predictive models is an appealing application of big data analytics.1,2 Historically, prediction models have relied on a limited number of specified variables, manually entered to estimate a ‘risk score’. Such models generally lack precision: they perform ‘reasonably well’ at the population level, but not at the individual patient level.3 And despite the existence of dozens of risk models related to cardiovascular conditions, few are utilized to make therapeutic decisions. Big data analytics may yield more powerful prediction of outcomes ranging from mortality to patient-reported outcomes to resource utilization, and thus could be more clinically actionable. Machine learning, for example, evaluates patterns associated with an outcome directly from the data, rather than from a pre-specified set of variables. A full range of associations and interactions among the data are assessed. Whereas traditional statistical models are ‘one and done’, machine learning uses a training process whereby the model is iteratively given varied data sets to explore many combinations of predictive features to optimize prediction. A hallmark of big data is combining disparate data sources and types. Current primary sources are electronic health records and administrative (claims) data. But wider ranges of data inputs are increasingly available to develop more robust ‘exposomes’ for each patient. For example, data from mobile health technology, biosensors, imaging, environmental data (e.g. air pollution), and information from social media networks, to name a few. In addition, ‘-omic’ data (genomic, proteomic, metabolomic) will be increasingly available, potentially fuelling more accurate outcome predictions as well as more robust disease classification and individualized treatment recommendations. Phenomapping, or deep phenotyping, is another promising big data application.2 Current disease classifications, or phenotypes, are imprecise and heterogeneous. Take, for example, non-ischemic cardiomyopathy: treatment guidelines lump treatment interventions, despite substantial within-group heterogeneity. Some patients have peripartum cardiomyopathy, whereas other have alcohol-related or non-compaction cardiomyopathy; each experience a different disease trajectory. Clinicians are keenly aware that patients with the ‘same’ disease respond differently to treatment—in other words, substantial heterogeneity is present. Big data analytics can identify similar patient clusters, creating multiple phenotypes within each disease entity. In theory, more refined phenomapping of disease states and trajectories should help inform more tailored-health decisions. Precision health is an important corollary of phenomapping. Patients and clinicians want to know if a specific patient is going to benefit (or be harmed) by an intervention. For example, guidelines for using ICD’s rely on a crude measurement, left ventricular ejection fraction. The majority of patients who receive ICDs never receive a life-saving shock and some are harmed by inappropriate shocks. Big data methods can support the combination of multiple data sources from large patient populations to better estimate the potential benefits of therapies such as ICD’s for individual patients. Indeed, big data analytic methods are central to the success of precision health, given the growing interest in incorporating ‘-omic’ data, which vastly increases the size and complexity of datasets. Such datasets require advanced analytic platforms and methods that are the hallmarks of big data analytics. Proof of concept challenges The development, validation, and integration of big data predictive models, phenomapping, and precision health tools into cardiovascular care are at a nascent stage.1,2 Despite proliferation of companies claiming to have big data ‘solutions’ that improve outcomes, it is hard to find published evidence of their impact or examples of successful integration into routine care. To that end, we propose the following ‘proof of concept’ challengers: Establish that big data models can have superior predictive power. Initial studies comparing big data methods to more traditional statistical methods and existing predictive models or risk scores suggest minimal or no significant incremental predictive benefit.2 Show that big data tools can provide ‘actionable’ insights. Limited studies of big data predictive tools largely reinforce that older, sicker, more complex patients have worse outcomes and have higher utilization of resources. Also, big data methods emphasize associations without consideration of causation, yet causal associations are often critical to inform medical decisions. Big data predictive models might, therefore, increase predictive power but provide no actionable insights to guide care decisions. Phenomapping studies do not yet support that novel phenotypes should be treated differently. And initial studies of precision medicine genetic markers have raised concern about accuracy and reproducibility; this does not support their readiness for clinical deployment.4 Demonstrate that big data ‘solutions’ are valid and stable over time when deployed. Most existing publications are initial validation studies using retrospective data. Before big data tools are used in routine care or health management, prospective evaluation of their validity and stability over time—even if they are constantly updated based on new data—is crucial. Outside of healthcare, less accurate or stable models may be acceptable, such as to guide consumer spending or entertainment choices. The stakes are much higher for health decisions. In addition, big data methods are generally tolerant of poor underlying data, especially where ‘all of the data’ is available. However, ‘all of the data’ are not available in healthcare. Missing healthcare data are often informative, and there may be treatment selection bias in existing data. Underlying data quality may be essential for big data analytics in healthcare compared to other sectors.2 Finally, many big data analytic companies use proprietary, ‘black box’, modelling approaches, which raise scepticism about validity and stability if they are to be used to inform care: proof of clinical utility will be essential. Prove that big data solutions improve care efficiency and outcomes. The initial development of big data tools isn’t sufficient to claim their effectiveness or cost effectiveness (since there is cost associated with the big data solutions). Evidence is needed that they can be successfully integrated into care, leading to more efficient and/or superior care outcomes, while avoiding unintended consequences. This evidence is lacking to date. In an era of exponential growth in technology, healthcare will change. But even as care moves away from episodic (e.g. clinic-based) to longitudinal, remote care supported by technology, human connection will remain at the centre of health care. The clinician–patient interface will still drive most health decisions. Big data carries the promise that these decisions may be informed by more powerful predictive analytics, better phenomapping of patients, and precision health tools that guide individualized care. However, hype without evidence is a threat to fulfilment of the promise of big data for cardiovascular care. Proof of concept must be evident. And while big data analytics are novel for cardiovascular care, successful integration into care harkens the challenges—and many examples of failure—of clinical decision support. Big data solutions will need to be coupled with successful strategies for clinical workflow change in order to succeed. At this point in the ‘era of big data’ in healthcare, there needs to be a shift in focus from what big data might do for cardiovascular care to proving what it can do, including careful planning of how to integrate these tools into evolving care models and demonstrating impact. Conflict of interest: none declared. References References are available as supplementary material at European Heart Journal online. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: [email protected].

Quarta, Candida Cristina; Gonzalez-Lopez, Esther; Gilbertson, Janet A.; Botcher, Nichola; Rowczenio, Dorota; Petrie, Aviva; Rezk, Tamer; Youngstein, Taryn; Mahmood, Shameem; Sachchithanantham, Sajitha; Lachmann, Helen J.; Fontana, Marianna; Whelan, Carol J.; Wechalekar, Ashutosh D.; Hawkins, Philip N.; Gillmore, Julian D.