by Keyword: Exercise

Blanco-Almazan, Dolores, Groenendaal, Willemijn, Lijnen, Lien, Onder, Rana, Smeets, Christophe, Ruttens, David, Catthoor, Francky, Jane, Raimon, (2022). Breathing Pattern Estimation Using Wearable Bioimpedance for Assessing COPD Severity Ieee Journal Of Biomedical And Health Informatics 26, 5983-5991

Breathing pattern has been shown to be different in chronic obstructive pulmonary disease (COPD) patients compared to healthy controls during rest and walking. In this study we evaluated respiratory parameters and the breathing variability of COPD patients as a function of their severity. Thoracic bioimpedance was acquired on 66 COPD patients during the performance of the six-minute walk test (6MWT), as well as 5 minutes before and after the test while the patients were seated, i.e. resting and recovery phases. The patients were classified by their level of airflow limitation into moderate and severe groups. We characterized the breathing patterns by evaluating common respiratory parameters using only wearable bioimpedance. Specifically, we computed the median and the coefficient of variation of the parameters during the three phases of the protocol, and evaluated the statistical differences between the two COPD severity groups. We observed significant differences between the COPD severity groups only during the sitting phases, whereas the behavior during the 6MWT was similar. Particularly, we observed an inverse relationship between breathing pattern variability and COPD severity, which may indicate that the most severely diseased patients had a more restricted breathing compared to the moderate patients.

JTD Keywords: 6mwt, activation, breathing pattern, burden, chronic obstructive pulmonary disease, exercise, muscles, pressure, pulmonary, signals, variability, volumes, wearables, Bioimpedance, Impedance pneumography

Romero, D, Calvo, M, Le Rolle, V, Behar, N, Mabo, P, Hernandez, A, (2022). Multivariate ensemble classification for the prediction of symptoms in patients with Brugada syndrome Medical & Biological Engineering & Computing 60, 81-94

Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients.

JTD Keywords: brugada syndrome, depolarization disorders, ensemble classifier, heart-rate recovery, Acute myocardial-ischemia, Autonomics, Brugada syndrome, Brugadum syndrome, Cardiac death, Depolarization, Depolarization disorder, Depolarization disorders, Dynamic ecg, Electrocardiography, Electrophysiology, Ensemble classifier, Ensemble-classifier, Events, Exercise, Forecasting, Heart, Heart-rate, Heart-rate recovery, Prognosis, Qrs, Quantification, Recovery, Repolarization, Sudden cardiac death

Romero, Daniel, Blanco-Almazán, Dolores, Groenendaal, Willemijn, Lijnen, Lien, Smeets, Christophe, Ruttens, David, Catthoor, Francky, Jané, Raimon, (2022). Predicting 6-minute walking test outcomes in patients with chronic obstructive pulmonary disease without physical performance measures Computer Methods And Programs In Biomedicine 225, 107020

Chronic obstructive pulmonary disease (COPD) requires a multifactorial assessment, evaluating the airflow limitation and symptoms of the patients. The 6-min walk test (6MWT) is commonly used to evaluate the functional exercise capacity in these patients. This study aims to propose a novel predictive model of the major 6MWT outcomes for COPD assessment, without physical performance measurements.Cardiopulmonary and clinical parameters were obtained from fifty COPD patients. These parameters were used as inputs of a Bayesian network (BN), which integrated three multivariate models including the 6-min walking distance (6MWD), the maximum HR (HRmax) after the walking, and the HR decay 3 min after (HRR3). The use of BN allows the assessment of the patients' status by predicting the 6MWT outcomes, but also inferring disease severity parameters based on actual patient's 6MWT outcomes.Firstly, the correlation obtained between the estimated and actual 6MWT measures was strong (R = 0.84, MAPE = 8.10% for HRmax) and moderate (R = 0.58, MAPE = 15.43% for 6MWD and R = 0.58, MAPE = 32.49% for HRR3), improving the classical methods to estimate 6MWD. Secondly, the classification of disease severity showed an accuracy of 78.3% using three severity groups, which increased up to 84.4% for two defined severity groups.We propose a powerful two-way assessment tool for COPD patients, capable of predicting 6MWT outcomes without the need for an actual walking exercise. This model-based tool opens the way to implement a continuous monitoring system for COPD patients at home and to provide more personalized care.Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

JTD Keywords: 6mwt, bayesian networks, copd, distance, exercise capacity, physical capacity, reference equations, severity, survival, wearables, 6mwt, Heart-rate recovery, Wearables

Rubies, C, Batlle, M, Sanz-de la Garza, M, Dantas, AP, Jorba, I, Fernandez, G, Sanguesa, G, Abuli, M, Brugada, J, Sitges, M, Navajas, D, Mont, L, Guasch, E, (2022). Long-Term Strenuous Exercise Promotes Vascular Injury by Selectively Damaging the Tunica Media Experimental Evidence Jacc Basic Transl Sci 7, 681-693

Moderate exercise has well-founded benefits in cardiovascular health. However, increasing, yet controversial, evidence suggests that extremely trained athletes may not be protected from cardiovascular events as much as moderately trained individuals. In our rodent model, intensive but not moderate training promoted aorta and carotid stiffening and elastic lamina ruptures, tunica media thickening of intramyocardial arteries, and an imbalance between vasoconstrictor and relaxation agents. An up-regulation of angiotensin-converter enzyme, miR-212, miR-132, and miR-146b might account for this deleterious remodeling. Most changes remained after a 4-week detraining. In conclusion, our results suggest that intensive training blunts the benefits of moderate exercise. (C) 2022 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.

JTD Keywords: atherosclerosis, cacs, coronary artery calcium score, cad, coronary artery disease, coronary artery disease, cv, cardiovascular, endurance exercise, extreme sport, mmp9, matrix metalloproteinase 9, no, nitric oxide, phe, phenylephrine, vsmc, vascular smooth muscle cell, Age, Atherosclerosis, Cacs, coronary artery calcium score, Cad, coronary artery disease, Coronary artery disease, Coronary atherosclerosis, Cv, cardiovascular, Disease, Endurance exercise, Extreme sport, Metalloproteinases, Micrornas, Mmp9, matrix metalloproteinase 9, No, nitric oxide, Phe, phenylephrine, Physical-activity, Prevalence, Rats, Relevance, Risk, Vascular stiffening, Vsmc, vascular smooth muscle cell