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Lazaro J, Reljin N, Bailon R, Gil E, Noh Y, Laguna P, Chon KH. Tracking Tidal Volume from Holter and Wearable Armband Electrocardiogram Monitoring. IEEE J Biomed Health Inform 2024; PP:1-9. [PMID: 38557616 DOI: 10.1109/jbhi.2024.3383232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
A novel method for tracking the tidal volume (TV) from electrocardiogram (ECG) is presented. The method is based on the amplitude of ECG-derived respiration (EDR) signals. Three different morphology-based EDR signals and three different amplitude estimation methods have been studied, leading to a total of 9 amplitude-EDR (AEDR) signals per ECG channel. The potential of these AEDR signals to track the changes in TV was analyzed. These methods do not need a calibration process. In addition, a personalized-calibration approach for TV estimation is proposed, based on a linear model that uses all AEDR signals from a device. All methods have been validated with two different ECG devices: a commercial Holter monitor, and a custom-made wearable armband. The lowest errors for the personalized-calibration methods, compared to a reference TV, were -3.48% [-17.41% / 12.93%] (median [first quartile / third quartile]) for the Holter monitor, and 0.28% [-10.90% / 17.15%] for the armband. On the other hand, medians of correlations to the reference TV were higher than 0.8 for uncalibrated methods, while they were higher than 0.9 for personal-calibrated methods. These results suggest that TV changes can be tracked from ECG using either a conventional (Holter) setup, or our custom-made wearable armband. These results also suggest that the methods are not as reliable in applications that induce small changes in TV, but they can be potentially useful for detecting large changes in TV, such as sleep apnea/hypopnea and/or exacerbations of a chronic respiratory disease.
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Armañac-Julián P, Martín-Montero A, Lázaro J, Hornero R, Laguna P, Kheirandish-Gozal L, Gozal D, Gil E, Bailón R, Gutiérrez-Tobal G. Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children. Pediatr Pulmonol 2024; 59:111-120. [PMID: 37850730 DOI: 10.1002/ppul.26720] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 09/20/2023] [Accepted: 09/26/2023] [Indexed: 10/19/2023]
Abstract
BACKGROUND Obstructive sleep apnea (OSA) is a risk factor for metabolic syndrome (MetS) in adults, but its association in prepubertal children is still questionable due to the relatively limited cardiometabolic data available and the phenotypic heterogeneity. OBJECTIVE To identify the role of OSA as a potential mediator of MetS in prepubertal children. METHODS A total of 255 prepubertal children from the Childhood Adenotonsillectomy Trial were included, with standardized measurements taken before OSA treatment and 7 months later. MetS was defined if three or more of the following criteria were present: adiposity, high blood pressure, elevated glycemia, and dyslipidemia. A causal mediation analysis was conducted to assess the effect of OSA treatment on MetS. RESULTS OSA treatment significantly impacted MetS, with the apnea-hypopnea index emerging as mediator (p = .02). This mediation role was not detected for any of the individual risk factors that define MetS. We further found that the relationship between MetS and OSA is ascribable to respiratory disturbance caused by the apnea episodes, while systemic inflammation as measured by C-reactive protein, is mediated by desaturation events and fragmented sleep. In terms of evolution, patients with MetS were significantly more likely to recover after OSA treatment (odds ratio = 2.56, 95% confidence interval [CI] 1.20-5.46; risk ratio = 2.06, 95% CI 1.19-3.54) than the opposite, patients without MetS to develop it. CONCLUSION The findings point to a causal role of OSA in the development of metabolic dysfunction, suggesting that persistent OSA may increase the risk of MetS in prepubertal children. This mediation role implies a need for developing screening for MetS in children presenting OSA symptoms.
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Affiliation(s)
- Pablo Armañac-Julián
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- BSICoS Group, University of Zaragoza, Zaragoza, Aragon, Spain
| | - Adrián Martín-Montero
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- GIB Group, University of Valladolid, Valladolid, Spain
| | - Jesús Lázaro
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- BSICoS Group, University of Zaragoza, Zaragoza, Aragon, Spain
| | - Roberto Hornero
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- GIB Group, University of Valladolid, Valladolid, Spain
| | - Pablo Laguna
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- BSICoS Group, University of Zaragoza, Zaragoza, Aragon, Spain
| | - Leila Kheirandish-Gozal
- Department of Neurology, University of Missouri School of Medicine, Columbia, Missouri, United States
| | - David Gozal
- Office of the Dean, Joan C. Edwards School of Medicine, Marshall University, Huntington, Virginia, United States
| | - Eduardo Gil
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- BSICoS Group, University of Zaragoza, Zaragoza, Aragon, Spain
| | - Raquel Bailón
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- BSICoS Group, University of Zaragoza, Zaragoza, Aragon, Spain
| | - Gonzalo Gutiérrez-Tobal
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- GIB Group, University of Valladolid, Valladolid, Spain
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Charlton PH, Allen J, Bailón R, Baker S, Behar JA, Chen F, Clifford GD, Clifton DA, Davies HJ, Ding C, Ding X, Dunn J, Elgendi M, Ferdoushi M, Franklin D, Gil E, Hassan MF, Hernesniemi J, Hu X, Ji N, Khan Y, Kontaxis S, Korhonen I, Kyriacou PA, Laguna P, Lázaro J, Lee C, Levy J, Li Y, Liu C, Liu J, Lu L, Mandic DP, Marozas V, Mejía-Mejía E, Mukkamala R, Nitzan M, Pereira T, Poon CCY, Ramella-Roman JC, Saarinen H, Shandhi MMH, Shin H, Stansby G, Tamura T, Vehkaoja A, Wang WK, Zhang YT, Zhao N, Zheng D, Zhu T. The 2023 wearable photoplethysmography roadmap. Physiol Meas 2023; 44:111001. [PMID: 37494945 PMCID: PMC10686289 DOI: 10.1088/1361-6579/acead2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 04/04/2023] [Accepted: 07/26/2023] [Indexed: 07/28/2023]
Abstract
Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.
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Affiliation(s)
- Peter H Charlton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, United Kingdom
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - John Allen
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5RW, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Raquel Bailón
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Stephanie Baker
- College of Science and Engineering, James Cook University, Cairns, 4878 Queensland, Australia
| | - Joachim A Behar
- Faculty of Biomedical Engineering, Technion Israel Institute of Technology, Haifa, 3200003, Israel
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, 518055 Guandong, People’s Republic of China
| | - Gari D Clifford
- Department of Biomedical Informatics, Emory University, Atlanta, GA 30322, United States of America
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States of America
| | - David A Clifton
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
| | - Harry J Davies
- Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Cheng Ding
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States of America
- Department of Biomedical Engineering, Emory University, Atlanta, GA 30322, United States of America
| | - Xiaorong Ding
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People’s Republic of China
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC 27708-0187, United States of America
- Duke Clinical Research Institute, Durham, NC 27705-3976, United States of America
| | - Mohamed Elgendi
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, 8008, Switzerland
| | - Munia Ferdoushi
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Daniel Franklin
- Institute of Biomedical Engineering, Translational Biology & Engineering Program, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, M5G 1M1, Canada
| | - Eduardo Gil
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Md Farhad Hassan
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Jussi Hernesniemi
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
- Tampere Heart Hospital, Wellbeing Services County of Pirkanmaa, Tampere, 33520, Finland
| | - Xiao Hu
- Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, 30322, Georgia, United States of America
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, 30322, Georgia, United States of America
- Department of Computer Sciences, College of Arts and Sciences, Emory University, Atlanta, GA 30322, United States of America
| | - Nan Ji
- Hong Kong Center for Cerebrocardiovascular Health Engineering (COCHE), Hong Kong Science and Technology Park, Hong Kong, 999077, People’s Republic of China
| | - Yasser Khan
- Department of Electrical and Computer Engineering, University of Southern California, 90089, Los Angeles, California, United States of America
- The Institute for Technology and Medical Systems (ITEMS), Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States of America
| | - Spyridon Kontaxis
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Ilkka Korhonen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
| | - Panicos A Kyriacou
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Jesús Lázaro
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon, University of Zaragoza, E-50018 Zaragoza, Spain
- CIBER-BBN, Instituto de Salud Carlos III, C/Monforte de Lemos 3-5, E-28029 Madrid, Spain
| | - Chungkeun Lee
- Digital Health Devices Division, Medical Device Evaluation Department, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Cheongju, 28159, Republic of Korea
| | - Jeremy Levy
- Faculty of Biomedical Engineering, Technion Israel Institute of Technology, Haifa, 3200003, Israel
- Faculty of Electrical and Computer Engineering, Technion Institute of Technology, Haifa, 3200003, Israel
| | - Yumin Li
- State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, People’s Republic of China
| | - Chengyu Liu
- State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, People’s Republic of China
| | - Jing Liu
- Analog Devices Inc, San Jose, CA 95124, United States of America
| | - Lei Lu
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
| | - Danilo P Mandic
- Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom
| | - Vaidotas Marozas
- Department of Electronics Engineering, Kaunas University of Technology, 44249 Kaunas, Lithuania
- Biomedical Engineering Institute, Kaunas University of Technology, 44249 Kaunas, Lithuania
| | - Elisa Mejía-Mejía
- Research Centre for Biomedical Engineering, City, University of London, London, EC1V 0HB, United Kingdom
| | - Ramakrishna Mukkamala
- Department of Bioengineering and Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Meir Nitzan
- Department of Physics/Electro-Optic Engineering, Lev Academic Center, 91160 Jerusalem, Israel
| | - Tania Pereira
- INESC TEC—Institute for Systems and Computer Engineering, Technology and Science, Porto, 4200-465, Portugal
- Faculty of Engineering, University of Porto, Porto, 4200-465, Portugal
| | | | - Jessica C Ramella-Roman
- Department of Biomedical Engineering and Herbert Wertheim College of Medicine, Florida International University, Miami, FL 33174, United States of America
| | - Harri Saarinen
- Tampere Heart Hospital, Wellbeing Services County of Pirkanmaa, Tampere, 33520, Finland
| | - Md Mobashir Hasan Shandhi
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
| | - Hangsik Shin
- Department of Digital Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Republic of Korea
| | - Gerard Stansby
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
- Northern Vascular Centre, Freeman Hospital, Newcastle upon Tyne, NE7 7DN, United Kingdom
| | - Toshiyo Tamura
- Future Robotics Organization, Waseda University, Tokyo, 1698050, Japan
| | - Antti Vehkaoja
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33720, Finland
- PulseOn Ltd, Espoo, 02150, Finland
| | - Will Ke Wang
- Department of Biomedical Engineering, Duke University, Durham, NC 27708-0187, United States of America
| | - Yuan-Ting Zhang
- Hong Kong Center for Cerebrocardiovascular Health Engineering (COCHE), Hong Kong Science and Technology Park, Hong Kong, 999077, People’s Republic of China
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, 999077, People’s Republic of China
| | - Ni Zhao
- Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, CV1 5RW, United Kingdom
| | - Tingting Zhu
- Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom
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Cajal D, Gil E, Laguna P, Varon C, Testelmans D, Buyse B, Jensen C, Hoare R, Bailon R, Lazaro J. Obstructive Sleep Apnea Screening by Joint Saturation Signal Analysis and PPG-derived Pulse Rate Oscillations. IEEE J Biomed Health Inform 2023; PP:1-11. [PMID: 37948138 DOI: 10.1109/jbhi.2023.3331947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Obstructive sleep apnea (OSA) is a high-prevalence disease in the general population, often underdiagnosed. The gold standard in clinical practice for its diagnosis and severity assessment is the polysomnography, although in-home approaches have been proposed in recent years to overcome its limitations. Today's ubiquitously presence of wearables may become a powerful screening tool in the general population and pulse-oximetry-based techniques could be used for early OSA diagnosis. In this work, the peripheral oxygen saturation together with the pulse-to-pulse interval (PPI) series derived from photoplethysmography (PPG) are used as inputs for OSA diagnosis. Different models are trained to classify between normal and abnormal breathing segments (binary decision), and between normal, apneic and hypopneic segments (multiclass decision). The models obtained 86.27% and 73.07% accuracy for the binary and multiclass segment classification, respectively. A novel index, the cyclic variation of the heart rate index (CVHRI), derived from PPI's spectrum, is computed on the segments containing disturbed breathing, representing the frequency of the events. CVHRI showed strong Pearson's correlation (r) with the apnea-hypopnea index (AHI) both after binary (r=0.94, p 0.001) and multiclass (r=0.91, p 0.001) segment classification. In addition, CVHRI has been used to stratify subjects with AHI higher/lower than a threshold of 5 and 15, resulting in 77.27% and 79.55% accuracy, respectively. In conclusion, patient stratification based on the combination of oxygen saturation and PPI analysis, with the addition of CVHRI, is a suitable, wearable friendly and low-cost tool for OSA screening at home.
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Sánchez-Cabo F, Fuster V, Silla-Castro JC, González G, Lorenzo-Vivas E, Alvarez R, Callejas S, Benguría A, Gil E, Núñez E, Oliva B, Mendiguren JM, Cortes-Canteli M, Bueno H, Andrés V, Ordovás JM, Fernández-Friera L, Quesada AJ, Garcia JM, Rossello X, Vázquez J, Dopazo A, Fernández-Ortiz A, Ibáñez B, Fuster JJ, Lara-Pezzi E. Subclinical atherosclerosis and accelerated epigenetic age mediated by inflammation: a multi-omics study. Eur Heart J 2023:ehad361. [PMID: 37339167 PMCID: PMC10393076 DOI: 10.1093/eurheartj/ehad361] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 04/28/2023] [Accepted: 05/23/2023] [Indexed: 06/22/2023] Open
Abstract
AIMS Epigenetic age is emerging as a personalized and accurate predictor of biological age. The aim of this article is to assess the association of subclinical atherosclerosis with accelerated epigenetic age and to investigate the underlying mechanisms mediating this association. METHODS AND RESULTS Whole blood methylomics, transcriptomics, and plasma proteomics were obtained for 391 participants of the Progression of Early Subclinical Atherosclerosis study. Epigenetic age was calculated from methylomics data for each participant. Its divergence from chronological age is termed epigenetic age acceleration. Subclinical atherosclerosis burden was estimated by multi-territory 2D/3D vascular ultrasound and by coronary artery calcification. In healthy individuals, the presence, extension, and progression of subclinical atherosclerosis were associated with a significant acceleration of the Grim epigenetic age, a predictor of health and lifespan, regardless of traditional cardiovascular risk factors. Individuals with an accelerated Grim epigenetic age were characterized by an increased systemic inflammation and associated with a score of low-grade, chronic inflammation. Mediation analysis using transcriptomics and proteomics data revealed key pro-inflammatory pathways (IL6, Inflammasome, and IL10) and genes (IL1B, OSM, TLR5, and CD14) mediating the association between subclinical atherosclerosis and epigenetic age acceleration. CONCLUSION The presence, extension, and progression of subclinical atherosclerosis in middle-aged asymptomatic individuals are associated with an acceleration in the Grim epigenetic age. Mediation analysis using transcriptomics and proteomics data suggests a key role of systemic inflammation in this association, reinforcing the relevance of interventions on inflammation to prevent cardiovascular disease.
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Affiliation(s)
- Fátima Sánchez-Cabo
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
| | - Valentín Fuster
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- The Zena and Michael A. Wiener Cardiovascular Institute/Marie-Josée and Henry R. Kravis Center for Cardiovascular Health, Mount Sinai School of Medicine, One Gustave L. Levy. Place, New York, NY 10029, USA
| | - Juan Carlos Silla-Castro
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Gema González
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Erika Lorenzo-Vivas
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Rebeca Alvarez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Sergio Callejas
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Alberto Benguría
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Eduardo Gil
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Estefanía Núñez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Belén Oliva
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | | | - Marta Cortes-Canteli
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Cardiology, IIS-Fundación Jiménez Díaz Hospital, Av. de los Reyes Católicos, 2, 28040 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Héctor Bueno
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Cardiology Department, Hospital Universitario 12 de Octubre and Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Avda. de Córdoba, s/n 28041 Madrid, Spain
| | - Vicente Andrés
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
| | - Jose María Ordovás
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Precision Nutrition and Obesity Research Program, IMDEA Food Institute, CEI UAM + CSIC, Carr. de Canto Blanco, nº 8 E, 28049 Madrid, Spain
- U.S. Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, 711 Washington Street, Boston, MA 02111, USA
| | - Leticia Fernández-Friera
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
- HM Hospitales-Centro Integral de Enfermedades Cardiovasculares HM CIEC, Av. de Montepríncipe, 25, 28660 Boadilla del Monte, Madrid, Spain
| | - Antonio J Quesada
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
| | - Jose Manuel Garcia
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Hospital Universitario Central de Oviedo, Av. Roma, s/n, 33011 Asturias, Spain
| | - Xavier Rossello
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
- Hospital Universitari Son Espases-IDISBA, Carretera de Valldemossa, 79, 07120 Palma de Mallorca, Mallorca, Islas Baleares (Balearic Islands), Spain
| | - Jesús Vázquez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
| | - Ana Dopazo
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
| | - Antonio Fernández-Ortiz
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
- Hospital Clínico San Carlos, Calle del Prof Martín Lagos, S/N, 28040 Madrid, Spain
| | - Borja Ibáñez
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
- Cardiology, IIS-Fundación Jiménez Díaz Hospital, Av. de los Reyes Católicos, 2, 28040 Madrid, Spain
| | - Jose Javier Fuster
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
| | - Enrique Lara-Pezzi
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro, 3, 28029 Madrid, Spain
- Centro de Investigacion Biomedica en Red en Enfermedades Cardiovasculares (CIBERCV), Spain
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Mellid S, García F, Leandro-García LJ, Díaz-Talavera A, Martínez-Montes ÁM, Gil E, Calsina B, Monteagudo M, Letón R, Roldán-Romero JM, Santos M, Lanillos J, Valdivia C, Martínez-Puente N, de Nicolás-Hernández J, Jiménez S, Pérez-Martínez M, Honrado E, Coloma J, Cerezo A, Santiveri CM, Esteller M, Campos-Olivas R, Caleiras E, Montero-Conde C, Rodríguez-Antona C, Muñoz J, Robledo M, Cascón A. DLST mutations in pheochromocytoma and paraganglioma cause proteome hyposuccinylation and metabolic remodeling. Cancer Commun (Lond) 2023. [PMID: 37139660 PMCID: PMC10354410 DOI: 10.1002/cac2.12427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 03/10/2023] [Accepted: 04/21/2023] [Indexed: 05/05/2023] Open
Affiliation(s)
- Sara Mellid
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Fernando García
- Proteomics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Alberto Díaz-Talavera
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | | | - Eduardo Gil
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Bruna Calsina
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - María Monteagudo
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Rocío Letón
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Juan María Roldán-Romero
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - María Santos
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Javier Lanillos
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Carlos Valdivia
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Natalia Martínez-Puente
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | | | - Scherezade Jiménez
- Monoclonal Antibodies Core Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Manuel Pérez-Martínez
- Confocal Microscopy Core Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Emiliano Honrado
- Anatomical Pathology Service, Hospital of León, León, Castilla y León, Spain
| | - Javier Coloma
- Structural Biology Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Ana Cerezo
- CNIO-Lilly Cell Signalling and Immunometabolism Section, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Clara María Santiveri
- Spectroscopy and Nuclear Magnetic Resonance Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Barcelona, Spain
- Centro de Investigacion Biomedica en Red Cancer (CIBERONC), Madrid, Spain
- Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), L'Hospitalet, Barcelona, Spain
| | - Ramón Campos-Olivas
- Spectroscopy and Nuclear Magnetic Resonance Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Eduardo Caleiras
- Histopathology Core Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Cristina Montero-Conde
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Javier Muñoz
- Proteomics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Cell Signaling and Clinical Proteomics Group, Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Mercedes Robledo
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Alberto Cascón
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain
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7
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Martín-Montero A, Armañac-Julián P, Gil E, Kheirandish-Gozal L, Álvarez D, Lázaro J, Bailón R, Gozal D, Laguna P, Hornero R, Gutiérrez-Tobal GC. Pediatric sleep apnea: Characterization of apneic events and sleep stages using heart rate variability. Comput Biol Med 2023; 154:106549. [PMID: 36706566 DOI: 10.1016/j.compbiomed.2023.106549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 12/19/2022] [Accepted: 01/11/2023] [Indexed: 01/16/2023]
Abstract
Heart rate variability (HRV) is modulated by sleep stages and apneic events. Previous studies in children compared classical HRV parameters during sleep stages between obstructive sleep apnea (OSA) and controls. However, HRV-based characterization incorporating both sleep stages and apneic events has not been conducted. Furthermore, recently proposed novel HRV OSA-specific parameters have not been evaluated. Therefore, the aim of this study was to characterize and compare classic and pediatric OSA-specific HRV parameters while including both sleep stages and apneic events. A total of 1610 electrocardiograms from the Childhood Adenotonsillectomy Trial (CHAT) database were split into 10-min segments to extract HRV parameters. Segments were characterized and grouped by sleep stage (wake, W; non-rapid eye movement, NREMS; and REMS) and presence of apneic events (under 1 apneic event per segment, e/s; 1-5 e/s; 5-10 e/s; and over 10 e/s). NREMS showed significant changes in HRV parameters as apneic event frequency increased, which were less marked in REMS. In both NREMS and REMS, power in BW2, a pediatric OSA-specific frequency domain, allowed for the optimal differentiation among segments. Moreover, in the absence of apneic events, another defined band, BWRes, resulted in best differentiation between sleep stages. The clinical usefulness of segment-based HRV characterization was then confirmed by two ensemble-learning models aimed at estimating apnea-hypopnea index and classifying sleep stages, respectively. We surmise that basal sympathetic activity during REMS may mask apneic events-induced sympathetic excitation, thus highlighting the importance of incorporating sleep stages as well as apneic events when evaluating HRV in pediatric OSA.
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Affiliation(s)
- Adrián Martín-Montero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain.
| | - Pablo Armañac-Julián
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain; Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Eduardo Gil
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain; Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Leila Kheirandish-Gozal
- Department of Child Health, The University of Missouri School of Medicine, Columbia, MO, USA
| | - Daniel Álvarez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain
| | - Jesús Lázaro
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain; Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Raquel Bailón
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain; Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - David Gozal
- Department of Child Health, The University of Missouri School of Medicine, Columbia, MO, USA
| | - Pablo Laguna
- CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain; Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain
| | - Gonzalo C Gutiérrez-Tobal
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Valladolid, Spain
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8
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Calsina B, Piñeiro-Yáñez E, Martínez-Montes ÁM, Caleiras E, Fernández-Sanromán Á, Monteagudo M, Torres-Pérez R, Fustero-Torre C, Pulgarín-Alfaro M, Gil E, Letón R, Jiménez S, García-Martín S, Martin MC, Roldán-Romero JM, Lanillos J, Mellid S, Santos M, Díaz-Talavera A, Rubio Á, González P, Hernando B, Bechmann N, Dona M, Calatayud M, Guadalix S, Álvarez-Escolá C, Regojo RM, Aller J, Del Olmo-Garcia MI, López-Fernández A, Fliedner SMJ, Rapizzi E, Fassnacht M, Beuschlein F, Quinkler M, Toledo RA, Mannelli M, Timmers HJ, Eisenhofer G, Rodríguez-Perales S, Domínguez O, Macintyre G, Currás-Freixes M, Rodríguez-Antona C, Cascón A, Leandro-García LJ, Montero-Conde C, Roncador G, García-García JF, Pacak K, Al-Shahrour F, Robledo M. Genomic and immune landscape Of metastatic pheochromocytoma and paraganglioma. Nat Commun 2023; 14:1122. [PMID: 36854674 PMCID: PMC9975198 DOI: 10.1038/s41467-023-36769-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 02/16/2023] [Indexed: 03/02/2023] Open
Abstract
The mechanisms triggering metastasis in pheochromocytoma/paraganglioma are unknown, hindering therapeutic options for patients with metastatic tumors (mPPGL). Herein we show by genomic profiling of a large cohort of mPPGLs that high mutational load, microsatellite instability and somatic copy-number alteration burden are associated with ATRX/TERT alterations and are suitable prognostic markers. Transcriptomic analysis defines the signaling networks involved in the acquisition of metastatic competence and establishes a gene signature related to mPPGLs, highlighting CDK1 as an additional mPPGL marker. Immunogenomics accompanied by immunohistochemistry identifies a heterogeneous ecosystem at the tumor microenvironment level, linked to the genomic subtype and tumor behavior. Specifically, we define a general immunosuppressive microenvironment in mPPGLs, the exception being PD-L1 expressing MAML3-related tumors. Our study reveals canonical markers for risk of metastasis, and suggests the usefulness of including immune parameters in clinical management for PPGL prognostication and identification of patients who might benefit from immunotherapy.
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Affiliation(s)
- Bruna Calsina
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
| | - Elena Piñeiro-Yáñez
- Bioinformatics Unit, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Ángel M Martínez-Montes
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Eduardo Caleiras
- Histopathology Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Ángel Fernández-Sanromán
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - María Monteagudo
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Rafael Torres-Pérez
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Bioinformatics for Genomics and Proteomics, National Centre for Biotechnology (CNB-CSIC), Madrid, Spain
| | - Coral Fustero-Torre
- Bioinformatics Unit, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Marta Pulgarín-Alfaro
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Eduardo Gil
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Rocío Letón
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Scherezade Jiménez
- Monoclonal Antibodies Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Santiago García-Martín
- Bioinformatics Unit, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Maria Carmen Martin
- Molecular Cytogenetics and Genome Engineering Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Juan María Roldán-Romero
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Javier Lanillos
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Sara Mellid
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - María Santos
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Alberto Díaz-Talavera
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Ángeles Rubio
- Genomics Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Patricia González
- Histopathology Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Barbara Hernando
- Computational Oncology Group, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Nicole Bechmann
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Margo Dona
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - María Calatayud
- Department of Endocrinology, 12 de Octubre University Hospital, Madrid, Spain
| | - Sonsoles Guadalix
- Department of Endocrinology, 12 de Octubre University Hospital, Madrid, Spain
| | | | - Rita M Regojo
- Department of Pathology, La Paz University Hospital, Madrid, Spain
| | - Javier Aller
- Department of Endocrinology, Puerta de Hierro University Hospital, Madrid, Spain
| | | | | | - Stephanie M J Fliedner
- Neuroendocrine Oncology and Metabolism, Medical Department I, Center of Brain, Behavior, and Metabolism, University Medical Center Schleswig-Holstein Lübeck, Lübeck, Germany
| | - Elena Rapizzi
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy
| | - Martin Fassnacht
- Department of Internal Medicine I, Division of Endocrinology and Diabetes, University Hospital Würzburg, University of Würzburg, Würzburg, Germany
- Comprehensive Cancer Center Mainfranken, University of Würzburg, Würzburg, Germany
| | - Felix Beuschlein
- Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Munich, Germany
- Klinik für Endokrinologie Diabetologie und Klinische Ernährung, Universitätsspital Zürich (USZ) und Universität Zürich (UZH), Zürich, Switzerland
| | - Marcus Quinkler
- Endocrinology in Charlottenburg Stuttgarter Platz 1, Berlin, Germany
| | - Rodrigo A Toledo
- Gastrointestinal and Endocrine Tumors, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Massimo Mannelli
- Department of Experimental and Clinical Biomedical Sciences, University of Florence, Florence, Italy
| | - Henri J Timmers
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Graeme Eisenhofer
- Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Sandra Rodríguez-Perales
- Molecular Cytogenetics and Genome Engineering Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Orlando Domínguez
- Genomics Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Geoffrey Macintyre
- Computational Oncology Group, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Maria Currás-Freixes
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Department of Endocrinology, Clínica Universidad de Navarra, Madrid, Spain
| | - Cristina Rodríguez-Antona
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Alberto Cascón
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Luis J Leandro-García
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Cristina Montero-Conde
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain
| | - Giovanna Roncador
- Monoclonal Antibodies Core Unit, Biotechnology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Karel Pacak
- Section of Medical Neuroendocrinology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Fátima Al-Shahrour
- Bioinformatics Unit, Structural Biology Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Mercedes Robledo
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Program, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Institute of Health Carlos III (ISCIII), Madrid, Spain.
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9
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Mellid S, Gil E, Letón R, Caleiras E, Honrado E, Richter S, Palacios N, Lahera M, Galofré JC, López-Fernández A, Calatayud M, Herrera-Martínez AD, Galvez MA, Matias-Guiu X, Balbín M, Korpershoek E, Lim ES, Maletta F, Lider S, Fliedner SMJ, Bechmann N, Eisenhofer G, Canu L, Rapizzi E, Bancos I, Robledo M, Cascón A. Co-occurrence of mutations in NF1 and other susceptibility genes in pheochromocytoma and paraganglioma. Front Endocrinol (Lausanne) 2023; 13:1070074. [PMID: 36760809 PMCID: PMC9905101 DOI: 10.3389/fendo.2022.1070074] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/09/2022] [Indexed: 01/26/2023] Open
Abstract
Introduction The percentage of patients diagnosed with pheochromocytoma and paraganglioma (altogether PPGL) carrying known germline mutations in one of the over fifteen susceptibility genes identified to date has dramatically increased during the last two decades, accounting for up to 35-40% of PPGL patients. Moreover, the application of NGS to the diagnosis of PPGL detects unexpected co-occurrences of pathogenic allelic variants in different susceptibility genes. Methods Herein we uncover several cases with dual mutations in NF1 and other PPGL genes by targeted sequencing. We studied the molecular characteristics of the tumours with co-occurrent mutations, using omic tools to gain insight into the role of these events in tumour development. Results Amongst 23 patients carrying germline NF1 mutations, targeted sequencing revealed additional pathogenic germline variants in DLST (n=1) and MDH2 (n=2), and two somatic mutations in H3-3A and PRKAR1A. Three additional patients, with somatic mutations in NF1 were found carrying germline pathogenic mutations in SDHB or DLST, and a somatic truncating mutation in ATRX. Two of the cases with dual germline mutations showed multiple pheochromocytomas or extra-adrenal paragangliomas - an extremely rare clinical finding in NF1 patients. Transcriptional and methylation profiling and metabolite assessment showed an "intermediate signature" to suggest that both variants had a pathological role in tumour development. Discussion In conclusion, mutations affecting genes involved in different pathways (pseudohypoxic and receptor tyrosine kinase signalling) co-occurring in the same patient could provide a selective advantage for the development of PPGL, and explain the variable expressivity and incomplete penetrance observed in some patients.
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Affiliation(s)
- Sara Mellid
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Eduardo Gil
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Rocío Letón
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Eduardo Caleiras
- Histopathology Core Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Susan Richter
- Institute for Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Nuria Palacios
- Endocrinology Department, University Hospital Puerta de Hierro, Madrid, Spain
| | - Marcos Lahera
- Endocrinology and Nutrition Department, La Princesa University Hospital, Madrid, Spain
| | - Juan C. Galofré
- Department of Endocrinology, Clínica Universidad de Navarra, Pamplona, Spain
| | - Adriá López-Fernández
- Hereditary Cancer Genetics Group, Vall d’Hebron Institute of Oncology (VHIO), Barcelona, Spain
| | - Maria Calatayud
- Department of Endocrinology and Nutrition, Hospital Universitario 12 de Octubre, Madrid, Spain
| | | | - María A. Galvez
- Endocrinology and Nutrition Service, Reina Sofia University Hospital, Cordoba, Spain
| | - Xavier Matias-Guiu
- Department of Pathology, Bellvitge University Hospital, Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
| | - Milagros Balbín
- Molecular Oncology Laboratory, Instituto Universitario de Oncologia del Principado de Asturias, Hospital Universitario Central de Asturias, Oviedo, Spain
| | - Esther Korpershoek
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, Netherlands
| | - Eugénie S. Lim
- Department of Endocrinology, William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - Francesca Maletta
- Pathology Unit , Department of Laboratory Medicine, Azienda Ospedaliero-Universitaria (AOU) Città della Salute e della Scienza di Torino, Torino, Italy
| | - Sofia Lider
- Endocrinology Department, National Institute of Endocrinology, Bucharest, Romania
| | | | - Nicole Bechmann
- Institute for Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Graeme Eisenhofer
- Institute for Clinical Chemistry and Laboratory Medicine, University Hospital Carl Gustav Carus, Medical Faculty Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Letizia Canu
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Elena Rapizzi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Irina Bancos
- Division of Endocrinology, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, United States
| | - Mercedes Robledo
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
| | - Alberto Cascón
- Hereditary Endocrine Cancer Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
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10
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García Pagès E, Arza A, Lazaro J, Puig C, Castro T, Ottaviano M, Arredondo MT, Bernal ML, López-Antón R, Cámara CDL, Gil E, Laguna P, Bailón R, Aguiló J, Garzón-Rey JM. Psychosomatic response to acute emotional stress in healthy students. Front Physiol 2023; 13:960118. [PMID: 36699693 PMCID: PMC9870289 DOI: 10.3389/fphys.2022.960118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 11/29/2022] [Indexed: 01/11/2023] Open
Abstract
The multidimensionality of the stress response has shown the complexity of this phenomenon and therefore the impossibility of finding a unique biomarker among the physiological variables related to stress. An experimental study was designed and performed to guarantee the correct synchronous and concurrent measure of psychometric tests, biochemical variables and physiological features related to acute emotional stress. The population studied corresponds to a group of 120 university students between 20 and 30 years of age, with healthy habits and without a diagnosis of chronic or psychiatric illnesses. Following the protocol of the experimental pilot, each participant reached a relaxing state and a stress state in two sessions of measurement for equivalent periods. Both states are correctly achieved evidenced by the psychometric test results and the biochemical variables. A Stress Reference Scale is proposed based on these two sets of variables. Then, aiming for a non-invasive and continuous approach, the Acute Stress Model correlated to the previous scale is also proposed, supported only by physiological signals. Preliminary results support the feasibility of measuring/quantifying the stress level. Although the results are limited to the population and stimulus type, the procedure and methodological analysis used for the assessment of acute stress in young people can be extrapolated to other populations and types of stress.
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Affiliation(s)
- Esther García Pagès
- Universitat Autònoma de Barcelona, UAB, Barcelona, Spain,*Correspondence: Esther García Pagès,
| | - Adriana Arza
- École Polytechnique Fédérale de Lausanne, EPFL, Lausanne, Switzerland
| | | | - Carlos Puig
- Universitat Autònoma de Barcelona, UAB, Barcelona, Spain
| | - Thais Castro
- Universitat Autònoma de Barcelona, UAB, Barcelona, Spain,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, CIBER-BBN, Madrid, Spain
| | - Manuel Ottaviano
- Life Supporting Technologies, Universidad Politécnica de Madrid, UPM, Madrid, Spain
| | | | | | | | | | - Eduardo Gil
- Universidad de Zaragoza, UZ, Zaragoza, Spain
| | - Pablo Laguna
- Universidad de Zaragoza, UZ, Zaragoza, Spain,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, CIBER-BBN, Madrid, Spain
| | - Raquel Bailón
- Universidad de Zaragoza, UZ, Zaragoza, Spain,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, CIBER-BBN, Madrid, Spain
| | - Jordi Aguiló
- Universidad de Zaragoza, UZ, Zaragoza, Spain,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, CIBER-BBN, Madrid, Spain
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Armañac-Julián P, Kontaxis S, Rapalis A, Marozas V, Laguna P, Bailón R, Gil E, Lázaro J. Reliability of pulse photoplethysmography sensors: Coverage using different setups and body locations. Front Electron 2022. [DOI: 10.3389/felec.2022.906324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Pulse photoplethysmography (PPG) is a simple and economical technique for obtaining cardiovascular information. In fact, PPG has become a very popular technology among wearable devices. However, the PPG signal is well-known to be very vulnerable to artifacts, and a good quality signal cannot be expected for most of the time in daily life. The percentage of time that a given measurement can be estimated (e.g., pulse rate) is denoted coverage (C), and it is highly dependent on the subject activity and on the configuration of the sensor, location, and stability of contact. This work aims to quantify the coverage of PPG sensors, using the simultaneously recorded electrocardiogram as a reference, with the PPG recorded at different places in the body and under different stress conditions. While many previous works analyzed the feasibility of PPG as a surrogate for heart rate variability analysis, there exists no previous work studying coverage to derive other cardiovascular indices. We report the coverage not only for estimating pulse rate (PR) but also for estimating pulse arrival time (PAT) and pulse amplitude variability (PAV). Three different datasets are analyzed for this purpose, consisting of a tilt-table test, an acute emotional stress test, and a heat stress test. The datasets include 19, 120, and 51 subjects, respectively, with PPG at the finger and at the forehead for the first two datasets and at the earlobe, in addition, for the latter. C ranges from 70% to 90% for estimating PR. Regarding the estimation of PAT, C ranges from 50% to 90%, and this is very dependent on the PPG sensor location, PPG quality, and the fiducial point (FP) chosen for the delineation of PPG. In fact, the delineation of the FP is critical in time for estimating derived series such as PAT due to the small dynamic range of these series. For the estimation of PAV, the C rates are between 70% and 90%. In general, lower C rates have been obtained for the PPG at the forehead. No difference in C has been observed between using PPG at the finger or at the earlobe. Then, the benefits of using either will depend on the application. However, different C rates are obtained using the same PPG signal, depending on the FP chosen for delineation. Lower C is reported when using the apex point of the PPG instead of the maximum flow velocity or the basal point, with a difference from 1% to even 10%. For further studies, each setup should first be analyzed and validated, taking the results and guidelines presented in this work into account, to study the feasibility of its recording devices with respect to each specific application.
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Montero‐Conde C, Leandro‐García LJ, Martínez‐Montes ÁM, Martínez P, Moya FJ, Letón R, Gil E, Martínez‐Puente N, Guadalix S, Currás‐Freixes M, García‐Tobar L, Zafon C, Jordà M, Riesco‐Eizaguirre G, González‐García P, Monteagudo M, Torres‐Pérez R, Mancikova V, Ruiz‐Llorente S, Pérez‐Martínez M, Pita G, Galofré JC, Gonzalez‐Neira A, Cascón A, Rodríguez‐Antona C, Megías D, Blasco MA, Caleiras E, Rodríguez‐Perales S, Robledo M. Comprehensive molecular analysis of immortalization hallmarks in thyroid cancer reveals new prognostic markers. Clin Transl Med 2022; 12:e1001. [PMID: 35979662 PMCID: PMC9386325 DOI: 10.1002/ctm2.1001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 07/08/2022] [Accepted: 07/12/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Comprehensive molecular studies on tumours are needed to delineate immortalization process steps and identify sensitive prognostic biomarkers in thyroid cancer. METHODS AND RESULTS In this study, we extensively characterize telomere-related alterations in a series of 106 thyroid tumours with heterogeneous clinical outcomes. Using a custom-designed RNA-seq panel, we identified five telomerase holoenzyme-complex genes upregulated in clinically aggressive tumours compared to tumours from long-term disease-free patients, being TERT and TERC denoted as independent prognostic markers by multivariate regression model analysis. Characterization of alterations related to TERT re-expression revealed that promoter mutations, methylation and/or copy gains exclusively co-occurred in clinically aggressive tumours. Quantitative-FISH (fluorescence in situ hybridization) analysis of telomere lengths showed a significant shortening in these carcinomas, which matched with a high proliferative rate measured by Ki-67 immunohistochemistry. RNA-seq data analysis indicated that short-telomere tumours exhibit an increased transcriptional activity in the 5-Mb-subtelomeric regions, site of several telomerase-complex genes. Gene upregulation enrichment was significant for specific chromosome-ends such as the 5p, where TERT is located. Co-FISH analysis of 5p-end and TERT loci showed a more relaxed chromatin configuration in short telomere-length tumours compared to normal telomere-length tumours. CONCLUSIONS Overall, our findings support that telomere shortening leads to a 5p subtelomeric region reorganization, facilitating the transcription and accumulation of alterations at TERT-locus.
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Hatcher J, Gil E, Storey N, Brown JR, Hartley JC, Breuer J, Lucchini G, Rao K, O'Connor D, Dunn H. Reactivation/relapse of SARS-CoV-2 in a child following haematopoietic stem cell transplantation, confirmed by whole genome sequencing, following apparent viral clearance. J Infect 2022; 85:e56-e58. [PMID: 35724755 PMCID: PMC9212430 DOI: 10.1016/j.jinf.2022.05.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 05/10/2022] [Indexed: 11/14/2022]
Affiliation(s)
- J Hatcher
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom.
| | - E Gil
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
| | - N Storey
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
| | - J R Brown
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
| | - J C Hartley
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
| | - J Breuer
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
| | - G Lucchini
- Department of Blood and Marrow Transplant, Great Ormond Street Hospital for Children, United Kingdom
| | - K Rao
- Department of Blood and Marrow Transplant, Great Ormond Street Hospital for Children, United Kingdom
| | - D O'Connor
- Department of Haematology, Great Ormond Street Hospital for Children and University College London Cancer Institute, United Kingdom
| | - H Dunn
- Department of Microbiology, Great Ormond Street Hospital for Children, United Kingdom
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Hernando A, Posada-Quintero H, Peláez-Coca MD, Gil E, Chon KH. Autonomic Nervous System characterization in hyperbaric environments considering respiratory component and non-linear analysis of Heart Rate Variability. Comput Methods Programs Biomed 2022; 214:106527. [PMID: 34879328 DOI: 10.1016/j.cmpb.2021.106527] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 11/05/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES an evaluation of Principal Dynamic Mode (PDM) and Orthogonal Subspace Projection (OSP) methods to characterize the Autonomic Nervous System (ANS) response in three different hyperbaric environments was performed. METHODS ECG signals were recorded in two different stages (baseline and immersion) in three different hyperbaric environments: (a) inside a hyperbaric chamber, (b) in a controlled sea immersion, (c) in a real reservoir immersion. Time-domain parameters were extracted from the RR series of the ECG. From the Heart Rate Variability signal (HRV), classic Power Spectral Density (PSD), PDM (a non-linear analysis of HRV which is able to separate sympathetic and parasympathetic activities) and OSP (an analysis of HRV which is able to extract the respiratory component) methods were used to assess the ANS response. RESULTS PDM and OSP parameters follows the same trend when compared to the PSD ones for the hyperbaric chamber dataset. Comparing the three hyperbaric scenarios, significant differences were found: i) heart rate decreased and RMSSD increased in the hyperbaric chamber and the controlled dive, but they had the opposite behavior during the uncontrolled dive; ii) power in the OSP respiratory component was lower than power in the OSP residual component in cases a and c; iii) PDM and OSP methods showed a significant increase in sympathetic activity during both dives, but parasympathetic activity increased only during the uncontrolled dive. CONCLUSIONS PDM and OSP methods could be used as an alternative measurement of ANS response instead of the PSD method. OSP results indicate that most of the variation in the heart rate variability cannot be described by changes in the respiration, so changes in ANS response can be assigned to other factors. Time-domain parameters reflect vagal activation in the hyperbaric chamber and in the controlled dive because of the effect of pressure. In the uncontrolled dive, sympathetic activity seems to be dominant, due to the effects of other factors such as physical activity, the challenging environment, and the influence of breathing through the scuba mask during immersion. In sum, a careful description of the changes in all the possible factors that could affect the ANS response between baseline and immersion stages in hyperbaric environments is needed for better interpretation of the results.
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Affiliation(s)
- Alberto Hernando
- Centro Universitario de Defensa (CUD), Academia General Militar (AGM), Zaragoza, Spain; BSICoS Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.
| | | | - María Dolores Peláez-Coca
- Centro Universitario de Defensa (CUD), Academia General Militar (AGM), Zaragoza, Spain; BSICoS Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Eduardo Gil
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; BSICoS Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Ki H Chon
- Department of Biomedical Engineering, University of Connecticut, Storrs CT, USA
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Lazazzera R, Laguna P, Gil E, Carrault G. Proposal for a Home Sleep Monitoring Platform Employing a Smart Glove. Sensors (Basel) 2021; 21:s21237976. [PMID: 34883979 PMCID: PMC8659764 DOI: 10.3390/s21237976] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 11/21/2021] [Accepted: 11/23/2021] [Indexed: 11/16/2022]
Abstract
The present paper proposes the design of a sleep monitoring platform. It consists of an entire sleep monitoring system based on a smart glove sensor called UpNEA worn during the night for signals acquisition, a mobile application, and a remote server called AeneA for cloud computing. UpNEA acquires a 3-axis accelerometer signal, a photoplethysmography (PPG), and a peripheral oxygen saturation (SpO2) signal from the index finger. Overnight recordings are sent from the hardware to a mobile application and then transferred to AeneA. After cloud computing, the results are shown in a web application, accessible for the user and the clinician. The AeneA sleep monitoring activity performs different tasks: sleep stages classification and oxygen desaturation assessment; heart rate and respiration rate estimation; tachycardia, bradycardia, atrial fibrillation, and premature ventricular contraction detection; and apnea and hypopnea identification and classification. The PPG breathing rate estimation algorithm showed an absolute median error of 0.5 breaths per minute for the 32 s window and 0.2 for the 64 s window. The apnea and hypopnea detection algorithm showed an accuracy (Acc) of 75.1%, by windowing the PPG in one-minute segments. The classification task revealed 92.6% Acc in separating central from obstructive apnea, 83.7% in separating central apnea from central hypopnea and 82.7% in separating obstructive apnea from obstructive hypopnea. The novelty of the integrated algorithms and the top-notch cloud computing products deployed, encourage the production of the proposed solution for home sleep monitoring.
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Affiliation(s)
- Remo Lazazzera
- Laboratoire Traitement du Signal et de l’Image (LTSI-Inserm UMR 1099), Université de Rennes 1, 35000 Rennes, France;
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, I3A, IIS Aragón, University of Zaragoza, and with the CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain; (P.L.); (E.G.)
| | - Eduardo Gil
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, I3A, IIS Aragón, University of Zaragoza, and with the CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain; (P.L.); (E.G.)
| | - Guy Carrault
- Laboratoire Traitement du Signal et de l’Image (LTSI-Inserm UMR 1099), Université de Rennes 1, 35000 Rennes, France;
- Correspondence:
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Kontaxis S, Lazaro J, Gil E, Laguna P, Bailon R. The Added Value of Nonlinear Cardiorespiratory Coupling Indices in the Assessment of Depression . Annu Int Conf IEEE Eng Med Biol Soc 2021; 2021:5473-5476. [PMID: 34892364 DOI: 10.1109/embc46164.2021.9631096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The present study investigates the differences in autonomic nervous system (ANS) function and stress response between patients with major depressive disorder (MDD) and healthy subjects by measuring changes in ANS biomarkers. ANS-related parameters are derived from various biosignals during a mental stress protocol consisting of a basal, stress, and recovery phase. The feature set consists of ANS biomarkers such as the heart rate (HR) derived from the electrocardiogram, the respiratory rate derived from the respiration signal, vascular parameters obtained from a model-based photoplethysmographic pulse waveform analysis, and cardiorespiratory coupling indices derived from the joint analysis of the heart rate variability (HRV) and respiratory signals. In particular, linear cardiorespiratory interactions are quantified by means of time-frequency coherence, while interactions of quadratic nonlinear nature between HRV and respiration are quantified by means of real wavelet biphase. The intra-subject difference of a feature value between two phases of the protocol, the so-called autonomic reactivity, is considered as a ANS biomarker as well. The performance of ANS biomarkers on discriminating MDD patients is evaluated using a classification pipeline. The results show that the most discriminative ANS biomarkers are related with differences in HR and autonomic reactivity of both vascular and nonlinear cardiorespiratory coupling indices. Differences in autonomic reactivity imply that MDD and healthy subjects differ in their ability to cope with stress. Considering only HR and vascular characteristics a linear support-vector machine classifier yields to accuracy 72.5% and F1-score 73.2%. However, taking into account the nonlinear cardiorespiratory coupling indices, the classification performance improves, yielding to accuracy 77.5% and F1-score 78.0%.Clinical relevance- Changes in the nonlinear properties of the cardiorespiratory system during stress may yield additional information on the assessment of depression.
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Armañac-Julián P, Hernando D, Lázaro J, de Haro C, Magrans R, Morales J, Moeyersons J, Sarlabous L, López-Aguilar J, Subirà C, Fernández R, Orini M, Laguna P, Varon C, Gil E, Bailón R, Blanch L. Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation. Sci Rep 2021; 11:16014. [PMID: 34362950 PMCID: PMC8346488 DOI: 10.1038/s41598-021-95282-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 07/20/2021] [Indexed: 02/07/2023] Open
Abstract
The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients' readiness, there is still around 15-20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome. Heart Rate Variability (HRV) and Cardiopulmonary Coupling (CPC) methods are evaluated as new complementary estimates to assess weaning readiness. The CPC is related to how the mechanisms regulating respiration and cardiac pumping are working simultaneously, and it is defined from HRV in combination with respiratory information. Three different techniques are used to estimate the CPC, including Time-Frequency Coherence, Dynamic Mutual Information and Orthogonal Subspace Projections. The cohort study includes 22 patients in pressure support ventilation, ready to undergo the SBT, analysed in the 24 h previous to the SBT. Of these, 13 had a successful weaning and 9 failed the SBT or needed reintubation -being both considered as failed weaning. Results illustrate that traditional variables such as heart rate, respiratory frequency, and the parameters derived from HRV do not differ in patients with successful or failed weaning. Results revealed that HRV parameters can vary considerably depending on the time at which they are measured. This fact could be attributed to circadian rhythms, having a strong influence on HRV values. On the contrary, significant statistical differences are found in the proposed CPC parameters when comparing the values of the two groups, and throughout the whole recordings. In addition, differences are greater at night, probably because patients with failed weaning might be experiencing more respiratory episodes, e.g. apneas during the night, which is directly related to a reduced respiratory sinus arrhythmia. Therefore, results suggest that the traditional measures could be used in combination with the proposed CPC biomarkers to improve weaning readiness.
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Affiliation(s)
- Pablo Armañac-Julián
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - David Hernando
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús Lázaro
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Candelaria de Haro
- Critical Care Center, Hospital Universitari Parc Taulí, Institut d'Investigació Parc Taulí I3PT, Universitat Autónoma de Barcelona, Sabadell, Spain
- CIBER de Enfermedades Respiratorias (CIBER-ES), Instituto de Salud Carlos III, Madrid, Spain
| | | | - John Morales
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
| | - Jonathan Moeyersons
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
| | - Leonardo Sarlabous
- Critical Care Center, Hospital Universitari Parc Taulí, Institut d'Investigació Parc Taulí I3PT, Universitat Autónoma de Barcelona, Sabadell, Spain
| | - Josefina López-Aguilar
- Critical Care Center, Hospital Universitari Parc Taulí, Institut d'Investigació Parc Taulí I3PT, Universitat Autónoma de Barcelona, Sabadell, Spain
- CIBER de Enfermedades Respiratorias (CIBER-ES), Instituto de Salud Carlos III, Madrid, Spain
| | - Carles Subirà
- Department of Intensive Care, Fundació Althaia, Universitat Internacional de Catalunya, Manresa, Spain
| | - Rafael Fernández
- CIBER de Enfermedades Respiratorias (CIBER-ES), Instituto de Salud Carlos III, Madrid, Spain
- Department of Intensive Care, Fundació Althaia, Universitat Internacional de Catalunya, Manresa, Spain
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, UK
- Barts Heart Centre, St Bartholomews Hospital, University College London, London, UK
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Carolina Varon
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium
- Circuits and Systems (CAS) group, Delft University of Technology, Delft, The Netherlands
| | - Eduardo Gil
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Raquel Bailón
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) group at the Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Lluís Blanch
- Critical Care Center, Hospital Universitari Parc Taulí, Institut d'Investigació Parc Taulí I3PT, Universitat Autónoma de Barcelona, Sabadell, Spain
- CIBER de Enfermedades Respiratorias (CIBER-ES), Instituto de Salud Carlos III, Madrid, Spain
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Milagro J, Soto-Retes L, Giner J, Varon C, Laguna P, Bailón R, Plaza V, Gil E. Asthmatic subjects stratification using autonomic nervous system information. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Pelaez-Coca MD, Hernando A, Lazaro J, Gil E. Impact of the PPG sampling rate in the pulse rate variability indices evaluating several fiducial points in different pulse waveforms. IEEE J Biomed Health Inform 2021; 26:539-549. [PMID: 34310329 DOI: 10.1109/jbhi.2021.3099208] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The main aim of this work is to study the effect of the sampling rate of the photoplethysmographic (PPG) signal for pulse rate variability (PRV) analysis in the time and frequency domains, in stationary conditions. Forehead and finger PPG signals were recorded at 1000 Hz during a rest state, with red and infrared wavelengths, simultaneously with the electrocardiogram (ECG). The PPG sampling rate has been reduced by decimation, obtaining signals at 500 Hz, 250 Hz, 125 Hz, 100 Hz, 50 Hz and 25 Hz. Five fiducial points were computed: apex, up-slope, medium, line-medium and medium interpolate point. The medium point is located in the middle of the up-slope of the pulse. The medium interpolate point is a new proposal as fiducial point that consider the abrupt up-slope of the PPG pulse, so it can be recovered by linear interpolation when the sampling rate is reduced. The error performed in the temporal location of the fiducial points was computed. Pulse period time interval series were obtained from all PPG signals and fiducial points, and compared with the RR intervals obtained from the ECG. Heart rate variability and PRV signals were estimated and classical time and frequency domain indices were computed. The results showed that the medium interpolate point of the PPG pulse was the most accurate fiducial point under different PPG morphologies and sensor locations, when sampling rate was reduced. The error in the temporal location points and in the estimation of time and frequency indices was always lower when medium interpolate point was used for all considered sampling rates and for both signals, finger and forehead. The results also showed that the sampling rate of PPG signal can be reduced up to 100 Hz without causing significant changes in the time and frequency indices, when medium interpolate point was used as fiducial point. Therefore, the use of the medium interpolate point is recommended when working at low sampling rates.
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Pelaez-Coca MD, Hernando A, Lozano MT, Sanchez C, Izquierdo D, Gil E. Photoplethysmographic Waveform and Pulse Rate Variability Analysis in Hyperbaric Environments. IEEE J Biomed Health Inform 2021; 25:1550-1560. [PMID: 32870804 DOI: 10.1109/jbhi.2020.3020743] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The main aim of this work is to identify alterations in the morphology of the pulse photoplethysmogram (PPG) signal, due to the exposure of the subjects to a hyperbaric environment. Additionally, their Pulse Rate Variability (PRV) is analysed to characterise the response of their Autonomic Nervous System (ANS). To do that, 28 volunteers are introduced into a hyperbaric chamber and five sequential stages with different atmospheric pressures from 1 atm to 5 atm are performed. In this work, nineteen morphological parameters of the PPG signal are analysed: the pulse amplitude; eight parameters related to pulse width; eight parameters related to pulse area; and the two two pulse slopes. Also, classical time and frequency parameters of PRV are computed. Notable widening of the pulses width is observed in the stages analysed. The PPG area increases with pressure, with no significant changes when the initial pressure is recovered. These changes in PPG waveform may be caused by an increase in the systemic vascular resistance as a consequence of of vasoconstriction in the extremities, suggesting a sympathetic activation. However, the PRV results show an augmented parasympathetic activity and a reduction in the parameters that characterise the sympathetic response. So, only a sympathetic activation is detected in the peripheral region, as reflected by PPG morphology. The information regarding the ANS and the cardiovascular response that can be extracted from the PPG signal, as well as its compatibility with wet conditions make this signal the most suitable for studying the physiological response in hyperbaric environments.
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Cordero-Barreal A, Caleiras E, López de Maturana E, Monteagudo M, Martínez-Montes ÁM, Letón R, Gil E, Álvarez-Escolá C, Regojo RM, Andía V, Marazuela M, Guadalix S, Calatayud M, Robles-Díaz L, Aguirre M, Cano JM, Díaz JÁ, Saavedra P, Lamas C, Azriel S, Sastre J, Aller J, Leandro-García LJ, Calsina B, Roldán-Romero JM, Santos M, Lanillos J, Cascón A, Rodríguez-Antona C, Robledo M, Montero-Conde C. CD133 Expression in Medullary Thyroid Cancer Cells Identifies Patients with Poor Prognosis. J Clin Endocrinol Metab 2020; 105:5892412. [PMID: 32791518 DOI: 10.1210/clinem/dgaa527] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 08/07/2020] [Indexed: 12/12/2022]
Abstract
CONTEXT The identification of markers able to determine medullary thyroid cancer (MTC) patients at high-risk of disease progression is critical to improve their clinical management and outcome. Previous studies have suggested that expression of the stem cell marker CD133 is associated with MTC aggressiveness. OBJECTIVE To evaluate CD133 impact on disease progression in MTC and explore the regulatory mechanisms leading to the upregulation of this protein in aggressive tumors. PATIENTS We compiled a series of 74 MTCs with associated clinical data and characterized them for mutations in RET and RAS proto-oncogenes, presumed to be related with disease clinical behavior. RESULTS We found that CD133 immunohistochemical expression was associated with adverse clinicopathological features and predicted a reduction in time to disease progression even when only RET-mutated cases were considered in the analysis (log-rank test P < 0.003). Univariate analysis for progression-free survival revealed CD133 expression and presence of tumor emboli in peritumoral blood vessels as the most significant prognostic covariates among others such as age, gender, and prognostic stage. Multivariate analysis identified both variables as independent factors of poor prognosis (hazard ratio = 16.6 and 2; P = 0.001 and 0.010, respectively). Finally, we defined hsa-miR-30a-5p, a miRNA downregulated in aggressive MTCs, as a CD133 expression regulator. Ectopic expression of hsa-miR-30a-5p in MZ-CRC-1 (RETM918T) cells significantly reduced CD133 mRNA expression. CONCLUSIONS Our results suggest that CD133 expression may be a useful tool to identify MTC patients with poor prognosis, who may benefit from a more extensive primary surgical management and follow-up.
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Affiliation(s)
| | | | - Evangelina López de Maturana
- Genetic & Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Basic Medical Sciences, Medical School, San Pablo-CEU University, Boadilla del Monte, Spain
- Biomedical Research Networking Centre on Oncology (CIBERONC), Madrid, Spain
| | | | | | - Rocío Letón
- Hereditary Endocrine Cancer Group, Madrid, Spain
| | - Eduardo Gil
- Hereditary Endocrine Cancer Group, Madrid, Spain
| | - Cristina Álvarez-Escolá
- Endocrinology and Nutrition Department and Pathological Anatomy Service, Hospital Universitario La Paz, Madrid, Spain
| | - Rita M Regojo
- Endocrinology and Nutrition Department and Pathological Anatomy Service, Hospital Universitario La Paz, Madrid, Spain
| | - Víctor Andía
- Endocrinology and Nutrition Department, Hospital Universitario Gregorio Marañón, Madrid, Spain
| | - Mónica Marazuela
- Endocrinology and Nutrition Department, Hospital Universitario La Princesa, Madrid, Spain
| | | | | | - Luis Robles-Díaz
- Medical Oncology Department, Hospital Universitario 12 de Octubre, Madrid, Spain
| | - Miguel Aguirre
- Endocrinology and Nutrition Department, Ciudad Real, Spain
| | - Juana M Cano
- Medical Oncology Department, Hospital Universitario de Ciudad Real, Ciudad Real, Spain
| | - José Ángel Díaz
- Endocrinology and Nutrition Department, Hospital Clínico San Carlos, Madrid, Spain
| | - Pilar Saavedra
- Endocrinology and Nutrition Department, Hospital Universitario Príncipe de Asturias, Alcalá de Henares, Spain
| | - Cristina Lamas
- Endocrinology and Nutrition Department, Complejo Hospitalario Universitario de Albacete, Albacete, Spain
| | - Sharona Azriel
- Endocrinology and Nutrition Department, Hospital Universitario Infanta Sofía, San Sebastián de los Reyes, Spain
| | - Julia Sastre
- Endocrinology and Nutrition Department, Hospital Virgen de la Salud, Toledo, Spain
| | - Javier Aller
- Endocrinology and Nutrition Department, Hospital Universitario Puerta de Hierro, Majadahonda, Spain
| | | | | | | | - María Santos
- Hereditary Endocrine Cancer Group, Madrid, Spain
| | | | - Alberto Cascón
- Hereditary Endocrine Cancer Group, Madrid, Spain
- Biomedical Research Networking Centre on Rare Diseases (CIBERER), Institute of Health Carlos III, Madrid, Spain
| | - Cristina Rodríguez-Antona
- Hereditary Endocrine Cancer Group, Madrid, Spain
- Biomedical Research Networking Centre on Rare Diseases (CIBERER), Institute of Health Carlos III, Madrid, Spain
| | - Mercedes Robledo
- Hereditary Endocrine Cancer Group, Madrid, Spain
- Biomedical Research Networking Centre on Rare Diseases (CIBERER), Institute of Health Carlos III, Madrid, Spain
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22
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Lazazzera R, Deviaene M, Varon C, Buyse B, Testelmans D, Laguna P, Gil E, Carrault G. Detection and Classification of Sleep Apnea and Hypopnea Using PPG and SpO 2 Signals. IEEE Trans Biomed Eng 2020; 68:1496-1506. [PMID: 32997622 DOI: 10.1109/tbme.2020.3028041] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In this work, a detection and classification method for sleep apnea and hypopnea, using photopletysmography (PPG) and peripheral oxygen saturation (SpO 2) signals, is proposed. The detector consists of two parts: one that detects reductions in amplitude fluctuation of PPG (DAP)and one that detects oxygen desaturations. To further differentiate among sleep disordered breathing events (SDBE), the pulse rate variability (PRV) was extracted from the PPG signal, and then used to extract features that enhance the sympatho-vagal arousals during apneas and hypopneas. A classification was performed to discriminate between central and obstructive events, apneas and hypopneas. The algorithms were tested on 96 overnight signals recorded at the UZ Leuven hospital, annotated by clinical experts, and from patients without any kind of co-morbidity. An accuracy of 75.1% for the detection of apneas and hypopneas, in one-minute segments,was reached. The classification of the detected events showed 92.6% accuracy in separating central from obstructive apnea, 83.7% for central apnea and central hypopnea and 82.7% for obstructive apnea and obstructive hypopnea. The low implementation cost showed a potential for the proposed method of being used as screening device, in ambulatory scenarios.
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Kontaxis S, Gil E, Marozas V, Lazaro J, Garcia E, Posadas-de Miguel M, Siddi S, Bernal ML, Aguilo J, Haro JM, de la Camara C, Laguna P, Bailon R. Photoplethysmographic Waveform Analysis for Autonomic Reactivity Assessment in Depression. IEEE Trans Biomed Eng 2020; 68:1273-1281. [PMID: 32960759 DOI: 10.1109/tbme.2020.3025908] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE In the present study, a photoplethysmographic (PPG) waveform analysis for assessing differences in autonomic reactivity to mental stress between patients with Major Depressive Disorder (MDD) and healthy control (HC) subjects is presented. METHODS PPG recordings of 40 MDD and 40 HC subjects were acquired at basal conditions, during the execution of cognitive tasks, and at the post-task relaxation period. PPG pulses are decomposed into three waves (a main wave and two reflected waves) using a pulse decomposition analysis. Pulse waveform characteristics such as the time delay between the position of the main wave and reflected waves, the percentage of amplitude loss in the reflected waves, and the heart rate (HR) are calculated among others. The intra-subject difference of a feature value between two conditions is used as an index of autonomic reactivity. RESULTS Statistically significant individual differences from stress to recovery were found for HR and the percentage of amplitude loss in the second reflected wave ( A13) in both HC and MDD group. However, autonomic reactivity indices related to A13 reached higher values in HC than in MDD subjects (Cohen's [Formula: see text]), implying that the stress response in depressed patients is reduced. A statistically significant ( ) negative correlation ( r=-0.5) between depression severity scores and A13 was found. CONCLUSION A decreased autonomic reactivity is associated with higher degree of depression. SIGNIFICANCE Stress response quantification by dynamic changes in PPG waveform morphology can be an aid for the diagnosis and monitoring of depression.
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Lazaro J, Reljin N, Bailon R, Gil E, Noh Y, Laguna P, Chon KH. Electrocardiogram Derived Respiratory Rate Using a Wearable Armband. IEEE Trans Biomed Eng 2020; 68:1056-1065. [PMID: 32746038 DOI: 10.1109/tbme.2020.3004730] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
A method for deriving respiratory rate from an armband, which records three-channel electrocardiogram (ECG) using three pairs of dry (no hydrogel) electrodes, is presented. The armband device is especially convenient for long-term (months-years) monitoring because it does not use obstructive leads nor hydrogels/adhesives, which cause skin irritation even after few days. An ECG-derived respiration (EDR) based on respiration-related modulation of QRS slopes and R-wave angle approach was used. Moreover, we modified the EDR algorithm to lower the computational cost. Respiratory rates were estimated with the armband-ECG and the reference plethysmography-based respiration signals from 15 subjects who underwent breathing experiment consisting of five stages of controlled breathing (at 0.1, 0.2, 0.3, 0.4, and 0.5 Hz) and one stage of spontaneous breathing. The respiratory rates from the armband obtained a relative error with respect to the reference (respiratory rate estimated from the plethysmography-based respiration signal) that was not higher than 2.26% in median nor interquartile range (IQR) for all stages of fixed and spontaneous breathing, and not higher than 3.57% in median nor IQR in the case when the low computational cost algorithm was applied. These results demonstrate that respiration-related modulation of the ECG morphology are also present in the armband ECG device. Furthermore, these results suggest that respiration-related modulation can be exploited by the EDR method based on QRS slopes and R-wave angles to obtain respiratory rate, which may have a wide range of applications including monitoring patients with chronic respiratory diseases, epileptic seizures detection, stress assessment, and sleep studies, among others.
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Rokadiya S, Gil E, Stubbs C, Bell D, Herbert R. COVID-19: Outcomes of patients with confirmed COVID-19 re-admitted to hospital. J Infect 2020; 81:e18-e19. [PMID: 32652166 PMCID: PMC7342032 DOI: 10.1016/j.jinf.2020.07.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 06/28/2020] [Accepted: 07/06/2020] [Indexed: 11/19/2022]
Affiliation(s)
- S Rokadiya
- Department of Microbiology and Infection, North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK.
| | - E Gil
- Department of Microbiology and Infection, North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK
| | - C Stubbs
- Department of Microbiology and Infection, North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK
| | - D Bell
- Department of Radiology, North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK
| | - R Herbert
- Department of Microbiology and Infection, North Middlesex University Hospital, Sterling Way, London, N18 1QX, UK
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Lazaro J, Reljin N, Bailon R, Gil E, Noh Y, Laguna P, Chon KH. Electrocardiogram Derived Respiration for Tracking Changes in Tidal Volume from a Wearable Armband. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:596-599. [PMID: 33018059 DOI: 10.1109/embc44109.2020.9175486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
A pilot study on tracking changes in tidal volume (TV) using ECG signals acquired by a wearable armband is presented. The wearable armband provides three ECG channels by using three pairs of dry electrodes, resulting in a device that is convenient for long-term daily monitoring. An additional ECG channel was derived by computing the first principal component of the three original channels (by means of principal component analysis). Armband and spirometer signals were simultaneously recorded from five healthy subjects who were instructed to breathe with varying TV. Three electrocardiogram derived respiration (EDR) methods based on QRS complex morphology were studied: the QRS slopes range (SR), the R-wave angle (Փ), and the R-S amplitude (RS). The peak-to-peak amplitudes of these EDR signals were estimated as surrogates for TV, and their correlations with the reference TV (estimated from the spirometer signal) were computed. In addition, a multiple linear regression model was calculated for each subject, using the peak-to-peak amplitudes from the three EDR methods from the four ECG channels. Obtained correlations between TV and EDR peak-to-peak amplitude ranged from 0.0448 up to 0.8491. For every subject, a moderate correlation (>0.5) was obtained for at least one EDR method. Furthermore, the correlations obtained for the subject-specific multiple linear regression model ranged from 0.8234 up to 0.9154, and the goodness of fit was 0.73±0.07 (median ± standard deviation). These results suggest that the peak-to-peak amplitudes of the EDR methods are linearly related to the TV. opening the possibility of estimating TV directly from an armband ECG device.Clinical Relevance- This opens the door to possible continuous monitoring of TV from the armband by using EDR.
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Corrochano M, Jiménez B, Millón J, Gich I, Rambla M, Gil E, Caparrós P, Macho R, Souto JC. Patient self-management of oral anticoagulation with vitamin K antagonists in everyday practice: clinical outcomes in a single centre cohort after long-term follow-up. BMC Cardiovasc Disord 2020; 20:166. [PMID: 32276619 PMCID: PMC7146979 DOI: 10.1186/s12872-020-01448-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 03/26/2020] [Indexed: 12/21/2022] Open
Abstract
Background Patient self-management (PSM) of vitamin K antagonists (VKA) seems a very promising model of care for oral anticoagulation in terms of efficacy and safety. In comparison with other management models of VKA therapy, the number of scientific publications supporting the advantages of PSM is more limited. Currently, most of the scarce information comes from randomized clinical trials. Moreover, a small number of studies have assessed PSM of VKA therapy in real life conditions. Methods We analyzed clinical outcomes of 927 patients in a single center (6018.6 patient-years of follow-up). Recruitment took place between 2002 and 2017. All patients followed a structured training program, conducted by specialized nurses. Results Fifty percent of individuals had a mechanical heart valve (MHV), 23% suffered from recurrent venous thromboembolism (VTE) or high-risk thrombophilia, and 13% received VKA therapy because of atrial fibrillation (AF). Median follow-up was 6.5 years (range 0.1–15.97 years), median age was 58.1 years (IQR 48–65.9) and 46.5% were women. The incidence of major complications (either hemorrhagic or thromboembolic) was 1.87% patient-years (pt-ys) with a 95% CI of 1.54–2.27. The incidence of major thromboembolic events was 0.86% pt-ys (95% CI 0.64–1.13) and that of major hemorrhagic events was 1.01% pt-ys (95% CI 0.77–1.31). The incidence of intracranial bleeding was 0.22% pt-ys (95% CI 0.12–0.38). In terms of clinical indication for VKA therapy, the incidence of total major complications was 2.4% pt-ys, 2.0% pt-ys, 0.9% pt-ys and 1.34% pt-ys for MHV, AF, VTE and other (including valvulopathies and myocardiopathies), respectively. Clinical outcomes were worse in patients with multiple comorbidities, previous major complications during conventional VKA therapy, and in older individuals. The percentage of time in therapeutic range (TTR) was available in 861 (93%) patients. Overall, the mean (SD) of TTR was 63.6 ± 13.4%, being higher in men (66.2 ± 13.1%) than women (60.6 ± 13.2%), p < 0.05. Conclusions In terms of clinically relevant outcomes (incidence of major complications and mortality), PSM in real life setting seems to be a very good alternative in properly trained patients.
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Affiliation(s)
- M Corrochano
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
| | - B Jiménez
- Institut de Recerca. Hospital de la Santa Creu i Sant Pau (IIB-Sant Pau), Barcelona, Spain
| | - J Millón
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - I Gich
- Clinical Epidemiology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - M Rambla
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - E Gil
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - P Caparrós
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - R Macho
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - J C Souto
- Haemostasis and Thrombosis Unit, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
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Varon C, Morales J, Lázaro J, Orini M, Deviaene M, Kontaxis S, Testelmans D, Buyse B, Borzée P, Sörnmo L, Laguna P, Gil E, Bailón R. A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG. Sci Rep 2020; 10:5704. [PMID: 32235865 PMCID: PMC7109157 DOI: 10.1038/s41598-020-62624-5] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 03/14/2020] [Indexed: 11/08/2022] Open
Abstract
Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress and sleep disorders. Therefore, the development of ambulatory systems providing continuous, comfortable, and inexpensive means for monitoring represents an important research topic. Several techniques have been proposed in the literature to derive respiratory information from the ECG signal. Ten methods to compute single-lead ECG-derived respiration (EDR) were compared under multiple conditions, including different recording systems, baseline wander, normal and abnormal breathing patterns, changes in breathing rate, noise, and artifacts. Respiratory rates, wave morphology, and cardiorespiratory information were derived from the ECG and compared to those extracted from a reference respiratory signal. Three datasets were considered for analysis, involving a total 59 482 one-min, single-lead ECG segments recorded from 156 subjects. The results indicate that the methods based on QRS slopes outperform the other methods. This result is particularly interesting since simplicity is crucial for the development of ECG-based ambulatory systems.
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Affiliation(s)
- Carolina Varon
- Delft University of Technology, Circuits and Systems (CAS) group, Delft, 2600 AA, the Netherlands.
- KU Leuven, Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven, 3001, Belgium.
| | - John Morales
- KU Leuven, Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven, 3001, Belgium
| | - Jesús Lázaro
- University of Connecticut, Department of Electrical Engineering, Storrs, CT, 06268, USA
- University of Zaragoza, BSICoS Group, Aragón Institute of Engineering Research (I3A), IISAragon, Zaragoza, 50015, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Michele Orini
- University College London, Institute of Cardiovascular Science, London, WC1E 6BT, UK
- University College London, Barts Heart centre at St Bartholomews Hospital, London, EC1A 7BE, UK
| | - Margot Deviaene
- KU Leuven, Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven, 3001, Belgium
| | - Spyridon Kontaxis
- University of Zaragoza, BSICoS Group, Aragón Institute of Engineering Research (I3A), IISAragon, Zaragoza, 50015, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | | | - Bertien Buyse
- UZ Leuven, Department of Pneumology, Leuven, 3001, Belgium
| | - Pascal Borzée
- UZ Leuven, Department of Pneumology, Leuven, 3001, Belgium
| | - Leif Sörnmo
- Lund University, Department of Biomedical Engineering, Lund, 118, 221 00, Sweden
| | - Pablo Laguna
- University of Zaragoza, BSICoS Group, Aragón Institute of Engineering Research (I3A), IISAragon, Zaragoza, 50015, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Eduardo Gil
- University of Zaragoza, BSICoS Group, Aragón Institute of Engineering Research (I3A), IISAragon, Zaragoza, 50015, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Raquel Bailón
- University of Zaragoza, BSICoS Group, Aragón Institute of Engineering Research (I3A), IISAragon, Zaragoza, 50015, Spain
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
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Pelaez Coca MD, Hernando A, Sanchez C, Albalate MTL, Izquierdo D, Gil E. Photoplethysmographic Waveform in Hyperbaric Environment. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2019:3490-3493. [PMID: 31946630 DOI: 10.1109/embc.2019.8856400] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The objective of this work is the identification of significant variations of morphological parameters of the photoplethysmographic (PPG) signal when the subjects are exposed to an increase in atmospheric pressure. To achieve this goal, the PPG signal of 26 subjects, exposed to a hyperbaric environment whose pressure increases up to 5 atm, has been recorded. From this record, segments of 4 minutes have been processed at 1 atm, 3 atm and 5 atm, both in the descending (D) and ascending (A) periods of the immersion. In total, four states (3D, 5, 3A and 1A) normalized to the basal state (1D) have been considered. In these segments, six morphological parameters of the PPG signal were studied. The width, the amplitude, the widths of the anacrotic and catacrotic phases, and the upward and downward slopes of each PPG pulse were extracted. The results showed significant increases in the three parameters related to the pulse width. This increase is significant in the four states analysed for the anacrotic phase width. Furthermore, a significant decrease in the amplitude and in both slopes (in the states 1A) was observed. These results show that the PPG width responds rapidly to the increase in pressure, indicating an activation of the sympathetic system, while amplitude and pulse slopes are decreased when the subjects are exposed to the hyperbaric environment for a considerable period of time.
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Perez-Martinez C, Pelaez-Coca MD, Hernando A, Gil E, Sanchez C. Multivariable relationships between autonomic nervous system related indices in hyperbaric environments. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2019:6789-6793. [PMID: 31947399 DOI: 10.1109/embc.2019.8856374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
The main aim of this work is to model the relationships between parameters extracted from the heart rate variability (HRV) signal, which is derived from the electrocardiogram (ECG), at different stages of a simulated immersion in a hyperbaric chamber. The response of the Autonomic Nervous System is known to be affected by changes in atmospheric pressure, reflected in changes in the HRV signal. A dataset consisting of ECG signals from 17 subjects exposed to a controlled hyperbaric environment, simulating depths from 0 m to 40 m, was used. Both linear and nonlinear dependences of HRV parameters were analysed using linear regression and Mutual Information (entropy-based) techniques. Furthermore, relationships between parameters of the HRV signals, biophysical variables of the subjects, and atmospheric pressure changes were characterized by artificial neural networks. In particular, self-organizing maps (SOM) were trained for modelling and clustering all the data. In the mid-term, these models could be the basis to create predictive models of HRV parameters at high depths in order to increase the safety for divers by warning them if some abnormal body response could be expected just by processing the ECG signal at sea level before immersion.
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Milagro J, Gracia-Tabuenca J, Seppa VP, Karjalainen J, Paassilta M, Orini M, Bailon R, Gil E, Viik J. Noninvasive Cardiorespiratory Signals Analysis for Asthma Evolution Monitoring in Preschool Children. IEEE Trans Biomed Eng 2019; 67:1863-1871. [PMID: 31670660 DOI: 10.1109/tbme.2019.2949873] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Despite its increasing prevalence, diagnosis of asthma in children remains problematic due to their difficulties in producing repeatable spirometric maneuvers. Moreover, low adherence to inhaled corticosteroids (ICS) treatment could result in permanent airway remodeling. The growing interest in a noninvasive and objective way for monitoring asthma, together with the apparent role of autonomic nervous system (ANS) in its pathogenesis, have attracted interest towards heart rate variability (HRV) and cardiorespiratory coupling (CRC) analyses. METHODS HRV and CRC were analyzed in 68 children who were prescribed ICS treatment due to recurrent obstructive bronchitis. They underwent three different electrocardiogram and respiratory signals recordings, during and after treatment period. After treatment completion, they were followed up during 6 months and classified attending to their current asthma status. RESULTS Vagal activity, as measured from HRV, and CRC, were reduced after treatment in those children at lower risk of asthma, whereas it kept unchanged in those with a worse prognosis. CONCLUSION Results suggest that HRV analysis could be useful for the continuous monitoring of ANS anomalies present in asthma, thus contributing to evaluate the evolution of the disease, which is especially challenging in young children. SIGNIFICANCE Noninvasive ANS assessment using HRV analysis could be useful in the continuous monitoring of asthma in children.
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Iozza L, Lázaro J, Cerina L, Silvestri D, Mainardi L, Laguna P, Gil E. Monitoring breathing rate by fusing the physiological impact of respiration on video-photoplethysmogram with head movements. Physiol Meas 2019; 40:094002. [DOI: 10.1088/1361-6579/ab4102] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Hernando A, Peláez-Coca MD, Lozano MT, Lázaro J, Gil E. Finger and forehead PPG signal comparison for respiratory rate estimation. Physiol Meas 2019; 40:095007. [DOI: 10.1088/1361-6579/ab3be0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Hernando D, Laguna P, Brophy C, Bailon R, Nardelli M, Hocking K, Lazaro J, Alvis B, Gil E, Scilingo EP, Brophy DR, Valenza G. Effect of yoga on pulse rate variability measured from a venous pressure waveform. Annu Int Conf IEEE Eng Med Biol Soc 2019; 2019:372-375. [PMID: 31945918 DOI: 10.1109/embc.2019.8856657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The benefits of yoga have been studied in different fields, from chronic health conditions to mental disorders, showing that it can help to improve the overall health. In particular, it has been proven that yoga also improves the autonomic function. Heart rate variability (HRV) at rest is commonly used as a non-invasive measure of autonomic regulation of heart rate. Alternatively, pulse rate variability (PRV) has been proposed as a surrogate of HRV. VoluMetrix has developed a novel technology that captures venous waveforms via sensors on the volar aspect of the wrist, called NIVAband. This study aims to assess the effect of yoga in the autonomic nervous system by analyzing the PRV obtained from the NIVA signal. Temporal (statistics of the normal-to-normal intervals), spectral (power in low and high frequency bands) and nonlinear (lagged Poincaré Plot analysis) parameters are analyzed before and after a yoga session in 20 healthy volunteers. The PRV analysis shows an increase in parameters related to parasympathetic activity and overall variability, and a decrease in parameters related to sympathetic activity and mean heart rate. These results support the beneficial effect of yoga in autonomic nervous system, increasing the parasympathetic activity.
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Wong-Arteta J, Rey M, Aragón L, Gil E, Bujanda L. Comprehensive diagnosis of neoplastic effusions from the clinical laboratory. Clin Chim Acta 2019. [DOI: 10.1016/j.cca.2019.03.919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Milagro J, Deviaene M, Gil E, Lázaro J, Buyse B, Testelmans D, Borzée P, Willems R, Van Huffel S, Bailón R, Varon C. Autonomic Dysfunction Increases Cardiovascular Risk in the Presence of Sleep Apnea. Front Physiol 2019; 10:620. [PMID: 31164839 PMCID: PMC6534181 DOI: 10.3389/fphys.2019.00620] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 05/02/2019] [Indexed: 01/08/2023] Open
Abstract
The high prevalence of sleep apnea syndrome (SAS) and its direct relationship with an augmented risk of cardiovascular disease (CVD) have raised SAS as a primary public health problem. For this reason, extensive research aiming to understand the interaction between both conditions has been conducted. The advances in non-invasive autonomic nervous system (ANS) monitoring through heart rate variability (HRV) analysis have revealed an increased sympathetic dominance in subjects suffering from SAS when compared with controls. Similarly, HRV analysis of subjects with CVD suggests altered autonomic activity. In this work, we investigated the altered autonomic control in subjects suffering from SAS and CVD simultaneously when compared with SAS patients, as well as the possibility that ANS assessment may be useful for the early stage identification of cardiovascular risk in subjects with SAS. The analysis was performed over 199 subjects from two independent datasets during night-time, and the effects of the physiological response following an apneic episode, sleep stages, and respiration on HRV were taken into account. Results, as measured by HRV, suggest a decreased sympathetic dominance in those subjects suffering from both conditions, as well as in subjects with SAS that will develop CVDs, which was reflected in a significantly reduced sympathovagal balance (p < 0.05). In this way, ANS monitoring could contribute to improve screening and diagnosis, and eventually aid in the phenotyping of patients, as an altered response might have direct implications on cardiovascular health.
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Affiliation(s)
- Javier Milagro
- Biomedical Signal Interpretation & Computational Simulation Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Margot Deviaene
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.,Interuniversity Microelectronics Centre (IMEC), Leuven, Belgium
| | - Eduardo Gil
- Biomedical Signal Interpretation & Computational Simulation Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Jesús Lázaro
- Biomedical Signal Interpretation & Computational Simulation Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.,Department of Biomedical Engineering, University of Connecticut, Storrs, CT, United States
| | - Bertien Buyse
- Department of Pneumology, UZ Leuven, Leuven, Belgium
| | | | - Pascal Borzée
- Department of Pneumology, UZ Leuven, Leuven, Belgium
| | - Rik Willems
- Department of Cardiovascular Sciences, UZ Leuven, Leuven, Belgium
| | - Sabine Van Huffel
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.,Interuniversity Microelectronics Centre (IMEC), Leuven, Belgium
| | - Raquel Bailón
- Biomedical Signal Interpretation & Computational Simulation Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
| | - Carolina Varon
- Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.,Interuniversity Microelectronics Centre (IMEC), Leuven, Belgium
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Abstract
Novel methods for assessing baroreflex sensitivity (BRS) using only pulse photoplethysmography (PPG) signals are presented. Proposed methods were evaluated with a data set containing electrocardiogram (ECG), blood pressure (BP), and PPG signals from 17 healthy subjects during a tilt table test. The methods are based on a surrogate of α index, which is defined as the power ratio of RR interval variability (RRV) and that of systolic arterial pressure series variability (SAPV). The proposed α index surrogates use pulse-to-pulse interval series variability (PPV) as a surrogate of RRV, and different morphological features of the PPG pulse which have been hypothesized to be related to BP, as series surrogates of SAPV. A time-frequency technique was used to assess BRS, taking into account the non-stationarity of the protocol. This technique identifies two time-varying frequency bands where RRV and SAPV (or their surrogates) are expected to be coupled: the low frequency (LF, inside 0.04-0.15 Hz range), and the high frequency (HF, inside 0.15-0.4 Hz range) bands. Furthermore, time-frequency coherence is used to identify the time intervals when the RRV and SAPV (or their surrogates) are coupled. Conventional α index based on RRV and SAPV was used as Gold Standard. Spearman correlation coefficients between conventional α index and its PPG-based surrogates were computed and the paired Wilcoxon statistical test was applied in order to assess whether the indices can find significant differences (p < 0.05) between different stages of the protocol. The highest correlations with the conventional α index were obtained by the α-index-surrogate based on PPV and pulse up-slope (PUS), with 0.74 for LF band, and 0.81 for HF band. Furthermore, this index found significant differences between rest stages and tilt stage in both LF and HF bands according to the paired Wilcoxon test, as the conventional α index also did. These results suggest that BRS changes induced by the tilt test can be assessed with high correlation by only a PPG signal using PPV as RRV surrogate, and PPG morphological features as SAPV surrogates, being PUS the most convenient SAPV surrogate among the studied ones.
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Affiliation(s)
- Jesús Lázaro
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, United States.,Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Eduardo Gil
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Michele Orini
- Department of Mechanical Engineering, University College London, London, United Kingdom
| | - Pablo Laguna
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Raquel Bailón
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
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Milagro J, Hernando D, Lazaro J, Casajus JA, Garatachea N, Gil E, Bailon R. Electrocardiogram-Derived Tidal Volume During Treadmill Stress Test. IEEE Trans Biomed Eng 2019; 67:193-202. [PMID: 30990416 DOI: 10.1109/tbme.2019.2911351] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Electrocardiogram (ECG) has been regarded as a source of respiratory information with the main focus in the estimation of the respiratory rate. Although little research concerning the estimation of tidal volume (TV) has been conducted, there are several ECG-derived features that have been related with TV in the literature, such as ECG-derived respiration, heart rate variability, and respiratory rate. In this paper, we exploited these features for estimating TV using a linear model. METHODS 25 young (33.4 ± 5.2 years) healthy male volunteers were recruited for performing a maximal (MaxT) and a submaximal (SubT) treadmill stress test, which were conducted on different days. Both tests were automatically segmented in stages attending to the heart rate. Afterwards, a subject-specific TV model was calibrated for each stage, employing features from MaxT, and the model was later used for estimating the TV in SubT. RESULTS During exercise, the different proposed approaches led to relative fitting errors lower than 14% in most of the cases and 6% in some of them. CONCLUSION Low achieved fitting errors suggest that TV can be estimated from ECG during a treadmill stress test. SIGNIFICANCE The results suggest that it is possible to estimate TV during exercise using only ECG-derived features.
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Peralta E, Lazaro J, Bailon R, Marozas V, Gil E. Optimal fiducial points for pulse rate variability analysis from forehead and finger photoplethysmographic signals. Physiol Meas 2019; 40:025007. [PMID: 30669123 DOI: 10.1088/1361-6579/ab009b] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The aim of this work is to evaluate and compare five fiducial points for the temporal location of each pulse wave from forehead and finger photoplethysmographic (PPG) pulse wave signals to perform pulse rate variability (PRV) analysis as a surrogate for heart rate variability (HRV) analysis. APPROACH Forehead and finger PPG signals were recorded during a tilt-table test simultaneously with the electrocardiogram (ECG). Artefacts were detected and removed and five fiducial points were computed: apex, middle-amplitude and foot points of the PPG signal, apex point of the first derivative signal and the intersection point of the tangent to the PPG waveform at the apex of the derivative PPG signal and the tangent to the foot of the PPG pulse, defined as the intersecting tangents method. Pulse period (PP) time interval series were obtained from both PPG signals and compared with the RR intervals obtained from the ECG. HRV and PRV signals were estimated and classical time and frequency domain indices were computed. MAIN RESULTS The middle-amplitude point of the PPG signal (n M ), the apex point of the first derivative ([Formula: see text]), and the tangent intersection point (n T ) are the most suitable fiducial points for PRV analysis, resulting in the lowest relative errors estimated between PRV and HRV indices and higher correlation coefficients and reliability indices. Statistically significant differences according to the Wilcoxon test between PRV and HRV signals were found for the apex and foot fiducial points of the PPG, as well as the lowest agreement between RR and PP series according to Bland-Altman analysis. Hence, these signals have been considered less accurate for variability analysis. In addition, the relative errors are significantly lower for n M and [Formula: see text] using Friedman statistics with a Bonferroni multiple-comparison test, and we propose that n M is the most accurate fiducial point. Based on our results, forehead PPG seems to provide more reliable information for a PRV assessment than finger PPG. SIGNIFICANCE The accuracy of the pulse wave detection depends on the morphology of the PPG. There is therefore a need to widely define the most accurate fiducial point for performing a PRV analysis under non-stationary conditions based on different PPG sensor locations and signal acquisition techniques.
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Affiliation(s)
- Elena Peralta
- Biomedical Signal Interpretation and Computational Simulation (BSICoS) Group, Aragon Institute of Engineering Research (I3A), IIS Aragon,University of Zaragoza, Zaragoza, Spain. Centro de Investigacion Biomedica en Red-Bioingenieria, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
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Varon C, Lazaro J, Bolea J, Hernando A, Aguilo J, Gil E, Van Huffel S, Bailon R. Unconstrained Estimation of HRV Indices After Removing Respiratory Influences From Heart Rate. IEEE J Biomed Health Inform 2018; 23:2386-2397. [PMID: 30507541 DOI: 10.1109/jbhi.2018.2884644] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE This paper proposes an approach to better estimate the sympathovagal balance (SB) and the respiratory sinus arrhythmia (RSA) after separating respiratory influences from the heart rate (HR). METHODS The separation is performed using orthogonal subspace projections and the approach is first tested using simulated HR and respiratory signals with different spectral properties. Then, RSA and SB are estimated during autonomic blockade and stress using the proposed approach and the classical heart rate variability (HRV) analysis. Both real- and ECG-derived respiration (EDR) are used and the reliability of the EDR is evaluated. RESULTS Mean absolute percentage errors lower than [Formula: see text] were obtained after removing previously known respiratory signals from simulated HR. The proposed indices were able to improve the quantification of SB during autonomic withdrawal. In the stress data, differences ( ) among relaxed and stressful phases were found with the proposed approach, using both the real respiration and the EDR, but they disappeared when using the classical HRV. CONCLUSION A better assessment of the autonomic nervous system' response to pharmacological blockade and stress can be achieved after removing respiratory influences from HR, and this can be done using either the real respiration or the EDR. SIGNIFICANCE This work can be used to better identify vagal withdrawal and increased sympathetic activation when the classical HRV analysis fails due to the respiratory influences on HR. Furthermore, it can be computed using only the ECG, which is an advantage when developing wearable systems with limited number of sensors.
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Pelaez MDC, Albalate MTL, Sanz AH, Valles MA, Gil E. Photoplethysmographic Waveform Versus Heart Rate Variability to Identify Low-Stress States: Attention Test. IEEE J Biomed Health Inform 2018; 23:1940-1951. [PMID: 30452382 DOI: 10.1109/jbhi.2018.2882142] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Our long-term goal is the development of an automatic identifier of attentional states. In order to accomplish it, we should first be able to identify different states based on physiological signals. So, the first aim of this paper is to identify the most appropriate features to detect a subject's high performance state. For that, a database of electrocardiographic (ECG) and photoplethysmographic (PPG) signals is recorded in two unequivocally defined states (rest and attention task) from up to 50 subjects as a sample of the population. Time and frequency parameters of heart/pulse rate variability have been computed from the ECG/PPG signals, respectively. Additionally, the respiratory rate has been estimated from both signals and also six morphological parameters from PPG. In total, 26 features are obtained for each subject. They provide information about the autonomic nervous system and the physiological response of the subject to an attention demand task. Results show an increase of sympathetic activation when the subjects perform the attention test. The amplitude and width of the PPG pulse were more sensitive than the classical sympathetic markers ([Formula: see text] and [Formula: see text]) for identifying this attentional state. State classification accuracy reaches a mean of [Formula: see text], a maximum of [Formula: see text], and a minimum of 85%, in the 100 classifications made by only selecting four parameters extracted from the PPG signal (pulse amplitude, pulsewidth, pulse downward slope, and mean pulse rate). These results suggest that attentional states could be identified by PPG.
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Zisberg A, Cohen Y, Gil E, Hait Y, Gur-Yash N, Shulyaev K, Agmon M. THE WALK-FOR INTERVENTION EFFECT ON PATIENTS’ OUTCOMES AT DISCHARGE AND 1-MONTH POST-DISCHARGE. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- A Zisberg
- The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel, Haifa, Hefa, Israel
| | - Y Cohen
- Department of Gerontology, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel
| | - E Gil
- Clalit Health Services, Israel
| | - Y Hait
- Clalit Health Services, Israel
| | - N Gur-Yash
- Oranim Academic College of Education, Israel
| | - K Shulyaev
- The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel
| | - M Agmon
- The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel
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Shulyaev K, Gur-Yaish N, Gil E, Zisberg A. DEPRESSION OF HOSPITALIZED SENIORS AND INFORMAL SUPPORT: THE MODERATING ROLE OF ATTACHMENT ANXIETY. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.1796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- K Shulyaev
- University of Haifa, Mount Carmel, Israel
| | | | | | - A Zisberg
- The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel
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Smichenko J, Gil E, Zisberg A. THE RELATIONSHIP BETWEEN HOSPITAL-ASSOCIATED COGNITIVE DECLINE AND SEDATIVE BURDEN AMONG MEDICAL OLDER PATIENTS. Innov Aging 2018. [DOI: 10.1093/geroni/igy023.2114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
| | - E Gil
- Clalit Health Services, Haifa and West Galilee
| | - A Zisberg
- The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Science, University of Haifa, Mount Carmel, Israel
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López-López V, Lynn PB, Gil J, García-Salom M, Gil E, González A, Muñoz IP, Cascales-Campos PA. Effect of Paclitaxel-based Hyperthermic Intraperitoneal Chemotherapy (HIPEC) on colonic anastomosis in a rat model. Clin Transl Oncol 2018; 21:505-511. [PMID: 30229392 DOI: 10.1007/s12094-018-1948-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2018] [Accepted: 09/07/2018] [Indexed: 12/24/2022]
Abstract
BACKGROUND Paclitaxel has been used frequently for Hyperthermic Intraperitoneal Chemotherapy (HIPEC) for ovarian carcinomatosis. Cytoreductive surgery and HIPEC are associated with high rates of morbidity being anastomotic dehiscence one of the most frequent. The objective of this study is to quantify the effect of Paclitaxel-based HIPEC on colonic anastomosis in an experimental rat model. METHODS After left colon resection and anastomosis, animals were randomized into four groups: Controls (C); Hyperthermia (H); Normothermic Intraperitoneal Paclitaxel (CP) and Paclitaxel-based HIPEC (HP). On postoperative day four, animals' peritoneal cavities were examined macroscopically, colon anastomosis burst pressures measured and specimens analyzed histologically. RESULTS Thirty-nine animals were randomized and 36 were included in the analysis. H group presented the highest burst pressure 105.11 ± 22.9 mmHg, which was 27% higher than C (77.89 ± 27.6 mmHg). On the other hand, HP presented the lowest burst pressure 64 ± 26 mmHg, 16% lower than C group and 39% lower than H, being this latter difference statistically significant (p = 0.004). There were no significant differences regarding weight loss, adhesion scores, perianastomotic abscesses and histological findings (inflammation, fibroblasts, neoangiogenesis, and collagen among groups). CONCLUSION Strength of colonic anastomosis was improved by isolated hyperthermia and negatively affected by Paclitaxel-based HIPEC.
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Affiliation(s)
- V López-López
- Virgen de la Arrixaca Clinic and University Hospital, General Surgery, IMIB, El Palmar, Murcia, Spain.
| | - P B Lynn
- Surgery Department, New York University School of Medicine, New York, NY, USA
| | - J Gil
- Virgen de la Arrixaca Clinic and University Hospital, General Surgery, IMIB, El Palmar, Murcia, Spain
| | - M García-Salom
- Virgen de la Arrixaca Clinic and University Hospital, General Surgery, IMIB, El Palmar, Murcia, Spain
| | - E Gil
- Virgen de la Arrixaca Clinic and University Hospital, General Surgery, IMIB, El Palmar, Murcia, Spain
| | - A González
- Gerencia del Area de Salud III (Lorca), Murcia, Spain
| | - I P Muñoz
- Hospital Virgen del Castillo (Yecla), Murcia, Spain
| | - P A Cascales-Campos
- Virgen de la Arrixaca Clinic and University Hospital, General Surgery, IMIB, El Palmar, Murcia, Spain
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Arza A, Garzón-Rey JM, Lázaro J, Gil E, Lopez-Anton R, de la Camara C, Laguna P, Bailon R, Aguiló J. Measuring acute stress response through physiological signals: towards a quantitative assessment of stress. Med Biol Eng Comput 2018; 57:271-287. [PMID: 30094756 DOI: 10.1007/s11517-018-1879-z] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 07/24/2018] [Indexed: 01/27/2023]
Abstract
Social and medical problems associated with stress are increasing globally and seriously affect mental health and well-being. However, an effective stress-level monitoring method is still not available. This paper presents a quantitative method for monitoring acute stress levels in healthy young people using biomarkers from physiological signals that can be unobtrusively monitored. Two states were induced to 40 volunteers, a basal state generated with a relaxation task and an acute stress state generated by applying a standard stress test that includes five different tasks. Standard psychological questionnaires and biochemical markers were utilized as ground truth of stress levels. A multivariable approach to comprehensively measure the physiological stress response is proposed using stress biomarkers derived from skin temperature, heart rate, and pulse wave signals. Acute physiological stress levels (total-range 0-100 au) were continuously estimated every 1 min showing medians of 29.06 au in the relaxation tasks, while rising from 34.58 to 47.55 au in the stress tasks. Moreover, using the proposed method, five statistically different stress levels induced by the performed tasks were also measured. Results obtained show that, in these experimental conditions, stress can be monitored from unobtrusive biomarkers. Thus, a more general stress monitoring method could be derived based on this approach. Graphical abstract Stress measurements of different healthy young people throughout a Stress Session that includes a pre-relax stage (BLs), memory test (ST and MT), stress anticipation time (SA), video display (VD) and arithmetic task.
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Affiliation(s)
- Adriana Arza
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain.
- Microelectronics and Electronic Systems Department, Autonomous University of Barcelona, Bellaterra, Spain.
- Embedded Systems Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, 1015, Switzerland.
| | - Jorge Mario Garzón-Rey
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
- Microelectronics and Electronic Systems Department, Autonomous University of Barcelona, Bellaterra, Spain
| | - Jesús Lázaro
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
- BSICoS Group, Aragon Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
- Department of Biomedical Engineering, University of Connecticut, Storrs, CT, 06269, USA
| | - Eduardo Gil
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
- BSICoS Group, Aragon Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Raul Lopez-Anton
- Psychology and Sociology Department of University of Zaragoza, Zaragoza, Spain
| | | | - Pablo Laguna
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
- BSICoS Group, Aragon Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Raquel Bailon
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain
- BSICoS Group, Aragon Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain
| | - Jordi Aguiló
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Zaragoza, Spain.
- Microelectronics and Electronic Systems Department, Autonomous University of Barcelona, Bellaterra, Spain.
- Microeletronics National Center, IMB-CNM, CSIC, Barcelona, Spain.
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Hernando A, Pelaez-Coca MD, Lozano MT, Aiger M, Izquierdo D, Sanchez A, Lopez-Jurado MI, Moura I, Fidalgo J, Lazaro J, Gil E. Autonomic Nervous System Measurement in Hyperbaric Environments Using ECG and PPG Signals. IEEE J Biomed Health Inform 2018; 23:132-142. [PMID: 29994358 DOI: 10.1109/jbhi.2018.2797982] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The main aim of this paper was to characterize the Autonomic Nervous System response in hyperbaric environments using electrocardiogram (ECG) and pulse-photoplethysmogram (PPG) signals. To that end, 26 subjects were introduced into a hyperbaric chamber and five stages with different atmospheric pressures (1 atm; descent to 3 and 5 atm; ascent to 3 and 1 atm) were recorded. Respiratory information was extracted from the ECG and PPG signals and a combined respiratory rate was studied. This information was also used to analyze Heart Rate Variability (HRV) and Pulse Rate Variability (PRV). The database was cleaned by eliminating those cases where the respiratory rate dropped into the low frequency band (LF: 0.04-0.15 Hz) and those in which there was a discrepancy between the respiratory rates estimated using the ECG and PPG signals. Classical temporal and frequency indices were calculated in such cases. The ECG results showed a time-related dependency, with the heart rate and sympathetic markers (normalized power in LF and LF/HF ratio) decreasing as more time was spent inside the hyperbaric environment. A dependence between the atmospheric pressure and the parasympathetic response, as reflected in the high-frequency band power (HF: 0.15-0.40 Hz), was also found, with power increasing with atmospheric pressure. The combined respiratory rate also reached a maximum in the deepest stage; thus, highlighting a significant difference between this stage and the first one. The PPG data gave similar findings and also allowed the oxygen saturation to be computed; therefore, we propose the use of this signal for future studies in hyperbaric environments.
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Lazaro J, Kontaxis S, Bailon R, Laguna P, Gil E. Respiratory Rate Derived from Pulse Photoplethysmographic Signal by Pulse Decomposition Analysis. Annu Int Conf IEEE Eng Med Biol Soc 2018; 2018:5282-5285. [PMID: 30441529 DOI: 10.1109/embc.2018.8513188] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A novel technique to derive respiratory rate from pulse photoplethysmographic (PPG) signals is presented. It exploits some morphological features of the PPG pulse that are known to be modulated by respiration: amplitude, slope transit time, and width of the main wave, and time to the first reflected wave. A pulse decomposition analysis technique is proposed to measure these features. This technique allows to decompose the PPG pulse into its main wave and its subsequent reflected waves, improving the robustness against noise and morphological changes that usually occur in long-term recordings. Proposed methods were evaluated with a data base containing PPG and plethysmography-based respiratory signals simultaneously recorded during a paced-breathing experiment. Results suggest that normal ranges of spontaneous respiratory rate (0.1-0.5 Hz) can be accurately estimated (median and interquartile range of relative error less than 5%) from PPG signals by using the studied features.
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Kontaxis S, Lazaro J, Gil E, Laguna P, Bailon R. Assessment of Quadratic Nonlinear Cardiorespiratory Couplings During Tilt-Table Test by Means of Real Wavelet Biphase. IEEE Trans Biomed Eng 2018; 66:187-198. [PMID: 29993448 DOI: 10.1109/tbme.2018.2821182] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE In this paper, a method for assessment of quadratic phase coupling (QPC) between respiration and heart rate variability (HRV) is presented. METHODS First, a method for QPC detection is proposed named real wavelet biphase (RWB). Then, a method for QPC quantification is proposed based on the normalized wavelet biamplitude (NWB). A simulation study has been conducted to test the reliability of RWB to identify QPC, even in the presence of constant delays between interacting oscillations, and to discriminate it from quadratic phase uncoupling. Significant QPC was assessed based on surrogate data analysis. Then, quadratic cardiorespiratory couplings were studied during a tilt-table test protocol of 17 young healthy subjects. RESULTS Simulation study showed that RWB is able to detect even weak QPC with delays in the range of [Formula: see text] s, which are usual in the autonomic nervous system (ANS) control of heart rate. Results from the database revealed a significant reduction ([Formula: see text]) of NWB between respiration and both low and high frequencies of HRV in head-up tilt position compared to early supine. CONCLUSION The proposed technique detects and quantifies robustly QPC and is able to track the coupling between respiration and various HRV components during ANS changes. SIGNIFICANCE The proposed method can help to assess alternations of nonlinear cardiorespiratory interactions related to ANS dysfunction and physiological regulation of HRV in cardiovascular diseases.
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Miranda-Fuentes A, Marucco P, González-Sánchez EJ, Gil E, Grella M, Balsari P. Developing strategies to reduce spray drift in pneumatic spraying in vineyards: Assessment of the parameters affecting droplet size in pneumatic spraying. Sci Total Environ 2018; 616-617:805-815. [PMID: 29111253 DOI: 10.1016/j.scitotenv.2017.10.242] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 10/23/2017] [Accepted: 10/23/2017] [Indexed: 06/07/2023]
Abstract
Pneumatic sprayers are widely used in vineyards due to their very fine droplet size, which makes the drift risk to become an important problem to be considered. The aim of this study was to assess the effect of the spout diameter at the release point on the spray droplet size and uniformity achieved for different liquid flow rates (LFR) and air flow rates (AFR). A test bench was developed to simulate a real pneumatic sprayer under laboratory conditions, and it was empirically adjusted to match the air pressure conditions as closely as possible to real working conditions. Two positions of insertion of the liquid hose, the conventional position (CP) and an alternative position (AP), were tested for three LFRs, 1.00, 1.64, and 2.67Lmin-1, and four AFRs, 0.280, 0.312, 0.345, and 0.376m3s-1. The air speed decrease between the two insertion points of the liquid hose was measured. A Malvern SprayTec® instrument was used to measure the droplet size, and the D50, D10, and D90 parameter values were obtained. The relative SPAN factor (RSF) was also calculated. A model to predict variations in D50 was fitted using the aforementioned parameters. The results show that variations in the diameter of the spout significantly change the droplet size, producing a mean increase of 59.45% in D50 and similar increases in D10 and D90. The model developed to predict variations in D50 has a very high degree of accuracy (R2=0.945). The relative decrease in the air speed along the spout did not present significant differences for the different airflow rates tested. The results of the study show that the droplet size produced in pneumatic spraying can be modified easily by varying the air spout dimensions. This should be taken into account by manufacturers from a design point of view.
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Affiliation(s)
- A Miranda-Fuentes
- Department of Rural Engineering, University of Córdoba, Ctra. Nacional IV, km 396, Campus de Rabanales, Córdoba 14014, Spain.
| | - P Marucco
- Department of Agricultural, Forest and Food Sciences (DiSAFA), University of Turin (UNITO), Largo Paolo Braccini 2, 10095 Grugliasco, TO, Italy
| | - E J González-Sánchez
- Department of Rural Engineering, University of Córdoba, Ctra. Nacional IV, km 396, Campus de Rabanales, Córdoba 14014, Spain
| | - E Gil
- Department of Agri Food Engineering and Biotechnology (DEAB), Universitat Politècnica de Catalunya (UPC), Esteve Terradas 8, Campus del Baix Llobregat D4, 08860 Castelledfels, Barcelona, Spain
| | - M Grella
- Department of Agricultural, Forest and Food Sciences (DiSAFA), University of Turin (UNITO), Largo Paolo Braccini 2, 10095 Grugliasco, TO, Italy
| | - P Balsari
- Department of Agricultural, Forest and Food Sciences (DiSAFA), University of Turin (UNITO), Largo Paolo Braccini 2, 10095 Grugliasco, TO, Italy
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