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1.
J Clin Hypertens (Greenwich) ; 25(6): 521-533, 2023 06.
Article in English | MEDLINE | ID: covidwho-2313695

ABSTRACT

High blood pressure (BP) and type-2 diabetes (T2DM) are forerunners of chronic kidney disease and left ventricular dysfunction. Home BP telemonitoring (HTM) and urinary peptidomic profiling (UPP) are technologies enabling risk stratification and personalized prevention. UPRIGHT-HTM (NCT04299529) is an investigator-initiated, multicenter, open-label, randomized trial with blinded endpoint evaluation designed to assess the efficacy of HTM plus UPP (experimental group) over HTM alone (control group) in guiding treatment in asymptomatic patients, aged 55-75 years, with ≥5 cardiovascular risk factors. From screening onwards, HTM data can be freely accessed by all patients and their caregivers; UPP results are communicated early during follow-up to patients and caregivers in the intervention group, but at trial closure in the control group. From May 2021 until January 2023, 235 patients were screened, of whom 53 were still progressing through the run-in period and 144 were randomized. Both groups had similar characteristics, including average age (62.0 years) and the proportions of African Blacks (81.9%), White Europeans (16.7%), women 56.2%, home (31.2%), and office (50.0%) hypertension, T2DM (36.4%), micro-albuminuria (29.4%), and ECG (9.7%) and echocardiographic (11.5%) left ventricular hypertrophy. Home and office BP were 128.8/79.2 mm Hg and 137.1/82.7 mm Hg, respectively, resulting in a prevalence of white-coat, masked and sustained hypertension of 40.3%, 11.1%, and 25.7%. HTM persisted after randomization (48 681 readings up to 15 January 2023). In conclusion, results predominantly from low-resource sub-Saharan centers proved the feasibility of this multi-ethnic trial. The COVID-19 pandemic caused delays and differential recruitment rates across centers.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 2 , Hypertension , Humans , Female , Middle Aged , Blood Pressure , Hypertension/diagnosis , Hypertension/epidemiology , Research Report , Pandemics , Health Care Reform , Proteomics , Blood Pressure Monitoring, Ambulatory/methods , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiology
2.
Blood Press Monit ; 27(Suppl 1): e8, 2022 Dec 01.
Article in English | MEDLINE | ID: covidwho-2260659
3.
Cardiol J ; 29(5): 730-738, 2022.
Article in English | MEDLINE | ID: covidwho-2040289

ABSTRACT

Hypertension and lipid disorders are two of the main cardiovascular risk factors. Both risk factors - if detected early enough - can be controlled and treated with modern, effective drugs, devoid of significant side effects, available in four countries as different as Italy, Spain, Poland, and Uzbekistan. The aim herein, was to develop this TIMES TO ACT consensus to raise the awareness of the available options of the modern and intensified dyslipidemia and arterial hypertension treatments. The subsequent paragraphs involves consensus and discussion of the deleterious effects of COVID-19 in the cardiovascular field, the high prevalence of hypertension and lipid disorders in our countries and the most important reasons for poor control of these two factors. Subsequently proposed, are currently the most efficient and safe therapeutic options in treating dyslipidemia and arterial hypertension, focusing on the benefits of single-pill combination (SPCs) in both conditions. An accelerated algorithm is proposed to start the treatment with a PCSK9 inhibitor, if the target low-density-lipoprotein values have not been reached. As most patients with hypertension and lipid disorders present with multiple comorbidities, discussed are the possibilities of using new SPCs, combining modern drugs from different therapeutic groups, which mode of action does not confirm the "class effect". We believe our consensus strongly advocates the need to search for patients with cardiovascular risk factors and intensify their lipid-lowering and antihypertensive treatment based on SPCs will improve the control of these two basic cardiovascular risk factors in Italy, Spain, Poland and Uzbekistan.


Subject(s)
COVID-19 , Cardiovascular Diseases , Dyslipidemias , Hypertension , Antihypertensive Agents/therapeutic use , Cardiovascular Diseases/diagnosis , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/prevention & control , Dyslipidemias/diagnosis , Dyslipidemias/drug therapy , Dyslipidemias/epidemiology , Humans , Hypertension/diagnosis , Hypertension/drug therapy , Hypertension/epidemiology , Lipids , Lipoproteins , Poland , Proprotein Convertase 9 , Risk Factors
4.
Sci Rep ; 12(1): 14412, 2022 08 24.
Article in English | MEDLINE | ID: covidwho-2016837

ABSTRACT

This paper describes a novel way to measure, process, analyze, and compare respiratory signals acquired by two types of devices: a wearable sensorized belt and a microwave radar-based sensor. Both devices provide breathing rate readouts. First, the background research is presented. Then, the underlying principles and working parameters of the microwave radar-based sensor, a contactless device for monitoring breathing, are described. The breathing rate measurement protocol is then presented, and the proposed algorithm for octave error elimination is introduced. Details are provided about the data processing phase; specifically, the management of signals acquired from two devices with different working principles and how they are resampled with a common processing sample rate. This is followed by an analysis of respiratory signals experimentally acquired by the belt and microwave radar-based sensors. The analysis outcomes were checked using Levene's test, the Kruskal-Wallis test, and Dunn's post hoc test. The findings show that the proposed assessment method is statistically stable. The source of variability lies in the person-triggered breathing patterns rather than the working principles of the devices used. Finally, conclusions are derived, and future work is outlined.


Subject(s)
Microwaves , Radar , Algorithms , Humans , Monitoring, Physiologic/methods , Respiration , Respiratory Rate , Signal Processing, Computer-Assisted
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