Definition and management of arterial hypertension in children and adolescents are uncertain, due to different positions of current guidelines. The European Society of Cardiology task-force, constituted by Associations and Councils with interest in arterial hypertension, has reviewed current literature and evidence, to produce a Consensus Document focused on aspects of hypertension in the age range of 6–16 years, including definition, methods of measurement of blood pressure, clinical evaluation, assessment of hypertension-mediated target organ damage, evaluation of possible vascular, renal and hormonal causes, assessment and management of concomitant risk factors with specific attention for obesity, and anti-hypertensive strategies, especially focused on life-style modifications. The Consensus Panel also suggests aspects that should be studied with high priority, including generation of multi-ethnic sex, age and height specific European normative tables, implementation of randomized clinical trials on different diagnostic and therapeutic aspects, and long-term cohort studies to link with adult cardiovascular risk. Finally, suggestions for the successful implementation of the contents of the present Consensus document are also given.

Background: Regression of left ventricular ( LV ) hypertrophy ( LVH ) has been a goal in clinical trials. This study tests the external validity of results of clinical trials on LVH regression using a large registry from a tertiary care center, to identify phenotypes less likely to achieve regression of LVH . Methods and Results: Patients from the Campania Salute Network, free of prevalent cardiovascular disease, but with echocardiographic LVH (defined as LV mass index [LVMi] >47 g/m ^2.7 in women and >50 g/m ^2.7 in men) were included. During a median follow‐up of 67 months, clear‐cut regression of LVH was documented in 14% of patients (13±8% reduction of initial LVMi ) or 23% when also considering those with a reduction of LVMi ≥5 g/m ^2.7 . Patients with persistent LVH were older with longer duration of hypertension, suboptimal blood pressure (BP) control, larger body mass index, LV mass, and carotid intima‐media thickness and included more women and subjects with diabetes mellitus, isolated systolic hypertension, and metabolic syndrome (all P <0.05). Number and class of antihypertensive drugs during follow‐up did not differ between groups. In multiple logistic regression analysis, older age, female sex, obesity, higher baseline LVMi and carotid intima‐media thickness, and suboptimal BP control were significant covariates of persistent LVH (all P ≤0.01), independent of diabetes, duration of hypertension, isolated systolic hypertension, follow‐up time and number and class of antihypertensive drugs. Conclusions: Early initiation of antihypertensive treatment, aggressive BP control, and attention to metabolic aspects are critical to avoid irreversible LVH .

Background: Myocardial energetic efficiency (MEE), is a strong predictor of CV events in hypertensive patient and is reduced in patients with diabetes and metabolic syndrome. We hypothesized that severity of insulin resistance (by HOMA-IR) negatively influences MEE in participants from the Strong Heart Study (SHS). Methods: We selected non-diabetic participants (n = 3128, 47 ± 17 years, 1807 women, 1447 obese, 870 hypertensive) free of cardiovascular (CV) disease, by merging two cohorts (Strong Heart Study and Strong Heart Family Study, age range 18–93). MEE was estimated as stroke work (SW = systolic blood pressure [SBP] × stroke volume [SV])/“double product” of SBP × heart rate (HR), as an estimate of O₂ consumption, which can be simplified as SV/HR ratio and expressed in ml/sec. Due to the strong correlation, MEE was normalized by left ventricular (LV) mass (MEEi). Results: Linear trend analyses showed that with increasing quartiles of HOMA-IR patients were older, more likely to be women, obese and hypertensive, with a trend toward a worse lipid profile (all p for trend < 0.001), progressive increase in LV mass index, stroke index and cardiac index and decline of wall mechanics (all p < 0.0001). In multivariable regression, after adjusting for confounders, and including a kinship coefficient to correct for relatedness, MEEi was negatively associated with HOMA-IR, independently of significant associations with age, sex, blood pressure, lipid profile and central obesity (all p < 0.0001). Conclusions: Severity of insulin resistance has significant and independent negative impact on myocardial mechano-energetic efficiency in nondiabetic individual from a population study of American Indians. Trial registration number NCT00005134, Name of registry: Strong Heart Study, URL of registry: https://clinicaltrials.gov/ct2/show/NCT00005134, Date of registration: May 25, 2000, Date of enrolment of the first participant to the trial: September 1988

Arterial hypertension (AH) is a progressive issue that grows in importance with the increased average age of the world population. The potential role of artificial intelligence (AI) in its prevention and treatment is firmly recognized. Indeed, AI application allows personalized medicine and tailored treatment for each patient. Specifically, this article reviews the benefits of AI in AH management, pointing out diagnostic and therapeutic improvements without ignoring the limitations of this innovative scientific approach. Consequently, we conducted a detailed search on AI applications in AH: the articles (quantitative and qualitative) reviewed in this paper were obtained by searching journal databases such as PubMed and subject-specific professional websites, including Google Scholar. The search terms included artificial intelligence, artificial neural network, deep learning, machine learning, big data, arterial hypertension, blood pressure, blood pressure measurement, cardiovascular disease, and personalized medicine. Specifically, AI-based systems could help continuously monitor BP using wearable technologies; in particular, BP can be estimated from a photoplethysmograph (PPG) signal obtained from a smartphone or a smartwatch using DL. Furthermore, thanks to ML algorithms, it is possible to identify new hypertension genes for the early diagnosis of AH and the prevention of complications. Moreover, integrating AI with omics-based technologies will lead to the definition of the trajectory of the hypertensive patient and the use of the most appropriate drug. However, AI is not free from technical issues and biases, such as over/underfitting, the “black-box” nature of many ML algorithms, and patient data privacy. In conclusion, AI-based systems will change clinical practice for AH by identifying patient trajectories for new, personalized care plans and predicting patients’ risks and necessary therapy adjustments due to changes in disease progression and/or therapy response.

Myocardial mechano-energetic efficiency (MEE) can be easily approximated by the ratio of stroke work [i.e. SBP times stroke volume (SV)] to a rough estimate of energy consumption, the ‘double product’ [SBP times heart rate (HR)], which can be simplified as SV/HR. We evaluated whether MEE is associated with adverse prognosis in relation to the presence of left ventricular hypertrophy (LVH). Hypertensive participants of the Campania Salute Network (n = 12 353) without prevalent coronary or cerebrovascular disease and with ejection fraction more than 50% were cross-sectionally and longitudinally analyzed, over a median follow-up of 31 months. MEE was estimated by echocardiographic SV (z-derived)/(HR × 0.6). Due to the close relation with left ventricular mass (LVM) (P < 0.0001), MEE was normalized for LVM (MEEi) and divided into quartiles. The lowest quartile of MEEi (<0.29 ml/s per g) was considered ‘low MEEi’. MEEi was greater in women than in men (P < 0.0001). Progressively lower MEEi was associated with older age, male sex, obesity, diabetes, LVH, concentric geometry, inappropriate LVM and diastolic dysfunction, more use of antihypertensive therapy, and higher BP (all P < 0.002). In Cox regression, after controlling for LVH, age, sex, and average follow-up SBP, low MEEi exhibited increased hazard of composite fatal and nonfatal cardiovascular end-points (P < 0.01), independently of antihypertensive therapy and associated cardiovascular risk factors. A simple estimate of low myocardial mechano-energetic efficiency is associated with altered metabolic profile, LVH, concentric left ventricular geometry, and diastolic dysfunction and predicts cardiovascular end-points, independently of age, sex, LVH antihypertensive therapy, and cardiovascular risk factors.