Blood pressure response during exercise testing in individuals with and without hypertension: The value of the recovery phase.

BACKGROUND: Hypertension and exercise testing are essential for cardiovascular risk assessment. However, an exact description of blood pressure (BP) in patients with a hypertensive response during exercise (HRE), especially in the recovery phase is lacking. Herein, we aimed to analyse BP and heart rate during exercise testing and recovery in patients with an HRE. METHODS: 800 patients aged 17-90 with an HRE during a standardized bicycle ergometry test were recruited. The BP behaviour during exercise testing was correlated with clinical data. Furthermore, data were analysed according to the presence of pre-existent hypertension. RESULTS: Of the 800 patients included in this study 497 (62%) were previously diagnosed with hypertension. Analysis of covariance showed a significantly faster systolic (ß [95% CI] 8.0 [4.9-11.1]) and diastolic (2.4 [0.4-4.4]) BP recovery 3 min after maximal exercise in patients without hypertension in univariable models. These results remained robust in fully adjusted models taking into account age, sex, body mass index, cardiovascular disease, and antihypertensive treatment for systolic (5.3 [1.2-9.4]) and diastolic BP (4.5 [1.9-7.0]). Furthermore, patients with hypertension displayed higher systolic BP during maximal exercise in univariable (3.8 [0.1-7.5]) and fully adjusted (5.5 [1.1-10.0]) models. There was no difference in maximum diastolic BP between groups. CONCLUSION: In this large cohort study, patients without hypertension showed a faster systolic and diastolic BP recovery and lower maximal systolic BP compared to patients with hypertension. Overall, this study provides new insights into cardiovascular health during recovery phase.

Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.

IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) approaches, certain phenotypes may be confined to classify the affected population and to predict outcome. This study aimed to phenotype patients using unsupervised ML technique within the International Postgraduate Course Heart Failure Registry for patients hospitalized with COVID-19 and Cardiovascular disease and/or RF (PCHF-COVICAV). MATERIAL AND METHODS: Patients from the eight centres with follow-up data available from the PCHF-COVICAV registry were included in this ML analysis (K-medoids algorithm). RESULTS: Out of 617 patients included into the prospective part of the registry, 458 [median age: 76 (IQR:65-84) years, 55% male] were analyzed and 46 baseline variables, including demographics, clinical status, comorbidities and biochemical characteristics were incorporated into the ML. Three clusters were extracted by this ML method. Cluster 1 (n = 181) represents mainly women with the least number of overall comorbidities and cardiovascular RF. Cluster 2 (n = 227) is characterized mainly by men with non-CV conditions and less severe symptoms of infection. Cluster 3 (n=50) mainly represents men with the highest prevalence of cardiac comorbidities and RF, more extensive inflammation and organ dysfunction with the highest 6-month all-cause mortality risk. CONCLUSIONS: The ML process has identified three important clinical clusters from hospitalized COVID-19 CV and/or RF patients. The cluster of males with severe CV disease, particularly HF, and multiple RF presenting with increased inflammation had a particularly poor outcome.

Effect of a Hypertensive Response During Exercise on Growth Rates of Aortic Diameters.

BACKGROUND: Aortic diameters are related to age, sex, and body size. There is a scarcity of data on the long-term sequelae of a hypertensive response to exercise (HRE) on aortic diameters. In this retrospective cohort study, we aimed to evaluate the relationship between the growth rates of the aorta in individuals with a HRE. METHODS: Our analysis included follow-up data of 649 patients recruited between January 2009 and December 2014 with a HRE. Participants with known connective tissue disease or a history of acute aortic syndrome were excluded. Sinus of Valsalva (SoV) and ascending aorta (AscAo) diameters were measured by transthoracic echocardiography using leading edge to leading edge convention at end-diastole. RESULTS: At baseline, median age, maximum systolic blood pressure (BP), body mass index (BMI), diameter of the SoV, and AscAo were 62 years, 208 mm Hg, 26.9 kg/m2, 35 mm, and 35 mm respectively. 32% of patients were female and 67% had hypertension. After a median follow-up of 7.1 years, mean yearly growth rates (±SD) of the SoV and AscAo were 0.09 (0.41) mm and 0.13 (0.56) mm, respectively. No significant associations were observed between growth rates of aortic diameters and maximum systolic and diastolic BP or when considering only individuals with a baseline diameter >40 mm. CONCLUSIONS: In this large cohort study, maximum systolic and diastolic BP during exercise showed no association with growth rates of aortic diameters. Furthermore, the mean growth rates of aortic diameters in this population were in line with growth rates in a normal population.