Hypertension: an undertreated known risk factor revisited

For the podcast associated with this article, please visit https://academic. oup.com/eurheartj/pages/Podcasts. Initially, hypertension was considered essential (in the German literature ‘Erfordernisblutdruck’), i.e. necessary to perfuse vital organs in those with cardiovascular disease. In the 1930s, Paul Dudley White, the Braunwald of the day, famously said ‘Hypertension may be an important compensatory mechanism which should not be tampered with, even were it certain that we could control it.’1 As such, Franklin D. Roosevelt’s hypertension was meticulously observed, but left untreated until his death due to a cerebral haemorrhage on 3 April 1945.2 Indeed, effective antihypertensives were unavailable at that time. Today we have all means available including antihypertensive drugs and, for selected patients, interventions using stents and renal nerve ablation.3 However, although raised blood pressure is widely known as being the largest contributor to mortality and disease burden worldwide4 and the effectiveness of blood pressure lowering is widely known,5 not all hypertensives are aware of it and many are suboptimally treated, particularly when the novel target values of recent guidelines are considered.6,7 In their Fast Track contribution entitled ‘May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension’,8 Neil Poulter and colleagues from Imperial College London in the UK report the results of their May Measurement Month global campaign. Up to 2018, a total of 1 504 963 adults from 89 countries participated and received three blood pressure measurements. Hypertension was defined as a blood pressure ≥140/90 mmHg or taking antihypertensive medication. After multiple imputation, 33% had hypertension, of whom 60% were aware of it and 55% were taking antihypertensives. Of those on medication, 60% were controlled and, of all hypertensives, only 33% were controlled. The authors detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (≥140/90 mmHg) hypertension. Thus, this campaign raising awareness of hypertension remains an unmet need even today. These devastating findings are put into context in an Editorial by Ross Feldman from the University of Manitoba in Winnipeg, Canada.9 Although after the seminal trial of Edward Fries, blood pressure control was widely adopted in the late 1970s and 1980s,10,11 this strategy remained controversial in the elderly. In their article entitled ‘Control of blood pressure and risk of mortality in a cohort of older adults: the Berlin Initiative Study’, Antonios Douros and colleagues from McGill University Faculty of Medicine in Montréal, Canada assess whether blood pressure values below 140/90 mmHg during antihypertensive treatment are associated with a decreased all-cause mortality in 1628 adults ≥70 years old recruited into the Berlin Initiative Study.12 Compared with non-normalized blood pressure, normalized blood pressure was associated with an increased risk of all-cause mortality with a hazard ratio of 1.26. Increased risks were observed in patients ≥80 years old (hazard ratio 1.40) and in those with previous cardiovascular events (hazard ratio 1.61), but not in those aged 70–79 years (hazard ratio 0.83) or without previous cardiovascular events (hazard ratio 1.16; Figure 1). Thus, blood pressures below 140/90 mmHg during antihypertensive treatment may be associated with an increased risk of mortality in octogenarians or elderly patients with previous cardiovascular events. These provocative findings are further discussed an informative Editorial by Michael Böhm from the Uniklinikum des Saarlandes in Homburg, Germany.13 Association of systolic blood pressure as categorical variable with the risk of all-cause mortality. Hazard ratios and 95% confidence intervals of the association between different ranges of systolic blood pressure and the risk of all-cause mortality (reference: 140 mmHg), adjusted for age, sex, body mass index, smoking, alcohol consumption, physical exercise, duration of treated hypertension, glomerular filtration rate, albuminuria, previous myocardial infarction, previous stroke, diabetes mellitus, and number of classes of antihypertensive drugs (from Douros A, Tölle M, Ebert N, Gaedeke J, Huscher D, Kreutz R, Kuhlmann MK, Martus P, Mielke N, Schneider A, Schuchardt M, van der Giet M, Schaeffner E. Control of blood pressure and risk of mortality in a cohort of older adults: the Berlin Initiative Study. See pages 2021–2028). Studies have shown a non-linear relationship between systolic and diastolic blood pressure and outcomes, with increased risk observed at both low and high blood pressure levels. In their article ‘Cardiovascular outcomes and achieved blood pressure in patients with and without diabetes at high cardiovascular risk’, Michael Böhm and colleagues from the Uniklinikum des Saarlandes in Homburg, Germany hypothesized that such a blood pressure–risk association may differ in 11 487 individuals with and 19 450 without diabetes at high cardiovascular risk followed for 56 months.14 Patients in ONTARGET had been randomized to ramipril 10 mg daily, telmisartan 80 mg daily, or the combination of both. Patients in TRANSCEND were angiotensin-converting enzyme intolerant and randomized to telmisartan 80 mg daily or matching placebo. In diabetics, event rates were higher across the whole spectrum of blood pressure compared with non-diabetics. Systolic blood pressure ≥160 mmHg was associated with increased events, with a hazard ratio of 2.31. Systolic blood pressure below 120 mmHg was associated with increased events of diabetics, with a hazard ratio of 1.53, and for cardiovascular and all-cause death in all patients. Diastolic blood pressure ≥90 mmHg was associated with increased events in diabetics, with a hazard ratio of 2.32. In-trial diastolic blood pressure below 70 mmHg was associated with increased events in all patients and also for all other endpoints except stroke. Thus, as expected, high on-treatment blood pressure is associated with worse cardiovascular outcomes, but also low blood pressures, with diabetics having consistently higher risks indicating that achieving optimal blood pressure goals is most impactful in this group. As outlined in a thought-provoking Editorial by Jawahar L. Mehta from the University of Arkansas in Little Rock, Arkansas USA,15 these data favour guidelines taking lower blood pressure boundaries into consideration, in particular in diabetics. Blood pressure and pulse wave velocity are of particular concern in patients with Marfan syndrome as the latter is associated with vascular dilatation.16 The life expectancy of Marfan patients has improved thanks to the early detection of aortic dilation, medical management, and prophylactic aortic root surgery, if indicated.17 Current international clinical guidelines support the use of aortic root diameter as a predictor of complications. However, other imaging markers are needed to improve risk stratification. In their article entitled ‘Proximal aorta longitudinal strain predicts aortic root dilation rate and aortic events in Marfan syndrome’, Gisela Teixido-Tura and colleagues from the Vall d’Hebron Institut de Recerca in Barcelona, Spain investigated whether proximal aorta longitudinal and circumferential strain and distensibility assessed by cardiac magnetic resonance (CMR) imaging would predict the aortic root dilation rate and events in 117 such patients over 86 months.18 The annual growth rate of aortic root diameter was 0.62 mm/year (Figure 2). Once corrected for baseline clinical and demographic characteristics and aortic root diameter, proximal aorta longitudinal strain, but not circumferential strain and distensibility, was an independent predictor of diameter growth and aortic events. These clinically important results are further explored in an Editorial by Christoph Nienaber from the Royal Brompton Hospital in London, UK.19 One hundred and seventeen Marfan patients with no previous aortic dissection, cardiac/aortic surgery, or moderate/severe aortic regurgitation were prospectively included. Proximal aorta longitudinal strain was computed by tracking the aortic valve throughout the cardiac cycle from a set of coronal, sagittal, and axial aortic valve cine images at baseline. Ascending aorta circumferential strain and distensibility were computed at baseline by registering time-resolved aortic contours in cine images in the ascending aorta. During follow-up (85.7 [75.0–93.2] months), the annual growth rate of aortic root diameter was 0.62 ± 0.65 mm/year, 21 patients had an aortic root dilation growth rate ≥1 mm/year, and 19 had surgical aortic root replacement or aortic dissection. Once corrected for baseline clinical and demographic characteristics and aortic root diameter, proximal aorta longitudinal strain, but not circumferential strain and distensibility, was an independent predictor of the aortic root diameter growth rate and aortic events. The bottom-left image shows superimposition of systolic (red) and diastolic (black) CT-based proximal aorta 3D segmentation of a Marfan syndrome patient and of of the cardiac magnetic resonance-based aortic valve movement tracking. (from Guala A, Teixidó-Tura G, Rodríguez-Palomares J, Ruiz-Muñoz A, Dux-Santoy L, Villalva N, Granato C, Galian L, Gutiérrez L, González-Alujas T, Sanchez V, Forteza A, García-Dorado D, Evangelista A. Proximal aorta longitudinal strain predicts aortic root dilation rate and aortic events in Marfan syndrome. See pages 2047–2054) The issue also contains a Review entitled ‘Deep learning for cardiovascular medicine: a practical primer’ by Chayakrit Krittanawong and colleagues from the Icahn School of Medicine at Mount Sinai in New York, USA.20 Deep learning is a branch of machine learning showing increasing promise in medicine, to assist in data classification, novel disease phenotyping, and complex decision-making.21–23 Deep learning is a form of machine learning typically implemented via multilayered neural networks. Deep learning has accelerated by recent advances in computer hardware and algorithms, and is increasingly applied in e-commerce, finance, and voice and image recognition to learn and classify complex data sets. Strengths of deep learning include its ability to automate medical image interpretation, enhance clinical decision-making, identify novel phenotypes, and select better treatment pathways in complex diseases. Deep learning may be well suited to capture haemodynamic and electrophysiological indices on a continuous basis by wearable devices as well as image segmentation in cardiac imaging. However, deep learning also has significant weaknesses including difficulties in interpreting its models, its need for extensive adjudicated data in training, lack of standardization in design, lack of data efficiency in training, limited applicability to clinical trials, and other factors. Thus, the optimal clinical application of deep learning requires careful formulation of solvable problems, selection of the most appropriate deep learning algorithms and data, and balanced interpretation of results. In a Special Article entitled ‘Standardized classification and framework for reporting, interpreting, and analysing medication non-adherence in cardiovascular clinical trials: a consensus report from the Non-adherence Academic Research Consortium (NARC)’, Marco Valgimigli from the University of Bern in Switzerland, and colleagues note that non-adherence has been well recognized for years to be a common issue that significantly impacts clinical outcomes and healthcare costs.24 Medication adherence is remarkably low even in the controlled environment of clinical trials where it has potentially complex major implications.25 Collection of non-adherence data diverges markedly among cardiovascular randomized trials and, even where collected, the data are rarely incorporated in the statistical analysis to test the consistency of the primary endpoint(s). The imprecision introduced by the inconsistent assessment of non-adherence in clinical trials might confound the estimate of the calculated efficacy of the study drug. Hence, clinical trials may not accurately answer the scientific question posed by regulators, who seek an accurate estimate of the true efficacy and safety of treatment, or the question posed by payers, who want a reliable estimate of the effectiveness of treatment in the marketplace after approval. This manscript is accompanied by an Editorial by Fortunato Senatore and Robert Califf.26 Finally, this issue contains Discussion Forum contributions. In a first contribution ‘How should treated hypertensive patients with systolic blood pressure below 120 mmHg be managed?’, Wilson Nadruz Junior and colleagues from the State University of Campinas in Campinas, São Paulo (Brazil) comments on the recently published ‘2018 ESC/ESH Guidelines for the management of arterial hypertension’.2,27 Dr Richard Kones and colleagues from the Cardiometabolic Research Institute in Houston, Texas also discuss the Guidelines in their contribution entitled ‘Concerning the degradation of beta-blocker use in the 2018 ESC/ESH hypertension guidelines’.28 A third contribution discussing these Guidelines is put forth by Karl Georg Haeusler and colleagues from the Universitätsklinikum Würzburg in Germany.29 This contribution is responded to by Giuseppe Mancia and colleagues from the Milano-Bicocca University in Italy.30 In a final Discussion Forum contribution entitled ‘Low on-treatment diastolic blood pressure is not independently associated with increased cardiovascular risk: an analysis of the SPRINT trial’, Maciej Sinski and colleagues from the Warszawski Uniwersytet Medyczny in Poland comment on the recently published manuscript entitled ‘Achieved diastolic blood pressure and pulse pressure at target systolic blood pressure (120–140 mmHg) and cardiovascular outcomes in high-risk patients: results from ONTARGET and TRANSCEND trials’ by Michael Böhm and colleagues from the Uniklinikum des Saarlandes in Homburg, Germany.31,32 The editors hope that this issue of the European Heart Journal will be of interest to its readers. With thanks to Amelia Meier-Batschelet for help with compilation of this article.