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Khushhal AA, Mohamed AA, Elsayed ME. Accuracy of Apple Watch to Measure Cardiovascular Indices in Patients with Chronic Diseases: A Cross Sectional Study. J Multidiscip Healthc 2024; 17:1053-1063. [PMID: 38496326 PMCID: PMC10941792 DOI: 10.2147/jmdh.s449071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/04/2024] [Indexed: 03/19/2024] Open
Abstract
Background The validity of the Apple Watch to measure the heart rate (HR) and oxygen saturation (Spo2) for patients with chronic diseases such as diabetes mellitus (DM), dyslipidemia, and hypertension is still unclear. Therefore, this study aims to investigate the accuracy of the Apple Watch in measuring the Spo2 and HR in patients with chronic diseases. Methods Forty-one patients with chronic diseases, including 20 with hypertension, 10 with diabetes, and 11 with dyslipidemia, completed a cross-sectional study. All participants used the Apple Watch against the Polar chest strap and the pulse oximeter at rest and during moderate intensity exercise sessions to measure HR and the SpO2 at rest for 5 minutes, during exercise for 16 minutes, and followed by 3 minutes of rest. The HR was measured during all previous periods, but evaluation of the Spo2 included 5 measures, done only before and after exercise, with a minute interval between each measure. Results Overall, a strong correlation exists between measuring the SpO2 using the Apple Watch against the pulse oximeter (Contec) at rest (r = 0.92, p < 0.001) and after exercise (r = 0.86, p < 0.001) in all patients. The HR had a very strong correlation between the Apple Watch and the Polar chest strap (r = 0.99, p < 0.001) in all patients. There was no significant difference (p = 0.76) between the twenty-seven white and fourteen brown-skinned patients. Conclusion The Apple Watch is valid to measure the HR and SpO2 in patients with chronic diseases. Clinical Trial Registration No NCT05271864.
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Affiliation(s)
- Alaa Abdulhafiz Khushhal
- Department of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Ashraf Abdelaal Mohamed
- Department of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
- Department of Physical Therapy for Cardiovascular/ Respiratory Disorder and Geriatrics, Faculty of Physical Therapy, Cairo University, Cairo, Egypt
| | - Mahmoud Elshahat Elsayed
- Cardiology Department, Umm Al-Qura University Medical Center, Umm Al-Qura University, Makkah, Saudi Arabia
- Cardiology Department, Faculty of Medicine, Al Azhar University, Cairo, Egypt
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Schliess F, Affini Dicenzo T, Gaus N, Bourez JM, Stegbauer C, Szecsenyi J, Jacobsen M, Müller-Wieland D, Kulzer B, Heinemann L. The German Fast Track Toward Reimbursement of Digital Health Applications: Opportunities and Challenges for Manufacturers, Healthcare Providers, and People With Diabetes. J Diabetes Sci Technol 2024; 18:470-476. [PMID: 36059268 PMCID: PMC10973846 DOI: 10.1177/19322968221121660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Digital health applications (DiGA) supporting the management of diabetes are among the most commonly available digital health technologies. However, transparent quality assurance of DiGA and clinical proof of a positive healthcare effect is often missing, which creates skepticism of some stakeholders regarding the usage and reimbursement of these applications. METHODS This article reviews the recently established fast-track integration of DiGA in the German reimbursement market, with emphasis on the current impact for manufacturers, healthcare providers, and people with diabetes. The German DiGA fast track is contextualised with corresponding initiatives in Europe. RESULTS The option of a provisional prescription and reimbursement of DiGA while proving a positive healthcare effect in parallel may expedite the adoption of DiGA in Germany and beyond. However, hurdles for a permanent prescription and reimbursement of DiGA are high and only one of 12 that have achieved this status specifically addresses people with diabetes. CONCLUSION The DiGA fast track needs to be further enhanced to cope with remaining skepticism and contribute even more to a value-based diabetes care.
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Affiliation(s)
| | | | | | | | - Constance Stegbauer
- AQUA Institute for Applied Quality Improvement and Research in Healthcare GmbH, Göttingen, Germany
| | - Joachim Szecsenyi
- AQUA Institute for Applied Quality Improvement and Research in Healthcare GmbH, Göttingen, Germany
| | - Malte Jacobsen
- Department of Internal Medicine I, RWTH Aachen University Hospital, Aachen, Germany
| | - Dirk Müller-Wieland
- Department of Internal Medicine I, RWTH Aachen University Hospital, Aachen, Germany
| | | | - Lutz Heinemann
- Profil Institut für Stoffwechselforschung GmbH, Neuss, Germany
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3
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Pan Z, Liao S, Sun W, Zhou H, Lin S, Chen D, Jiang S, Long H, Fan J, Deng F, Zhang W, Chen B, Wang J, Huang Y, Li J, Chen Y. Screening and early warning system for chronic obstructive pulmonary disease with obstructive sleep apnoea based on the medical Internet of Things in three levels of healthcare: protocol for a prospective, multicentre, observational cohort study. BMJ Open 2024; 14:e075257. [PMID: 38418236 PMCID: PMC10910414 DOI: 10.1136/bmjopen-2023-075257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 02/12/2024] [Indexed: 03/01/2024] Open
Abstract
INTRODUCTION Chronic obstructive pulmonary disease (COPD) and obstructive sleep apnoea (OSA) are prevalent respiratory diseases in China and impose significant burdens on the healthcare system. Moreover, the co-occurrence of COPD and OSA exacerbates clinical outcomes significantly. However, comprehensive epidemiological investigations in China remain scarce, and the defining characteristics of the population affected by COPD and OSA, alongside their intrinsic relationship, remain ambiguous. METHODS AND ANALYSIS We present a protocol for a prospective, multicentre, observational cohort study based on a digital health management platform across three different healthcare tiers in five sites among Chinese patients with COPD. The study aims to establish predicative models to identify OSA among patients with COPD and to predict the prognosis of overlap syndrome (OS) and acute exacerbations of COPD through the Internet of Things (IoT). Moreover, it aims to evaluate the feasibility, effectiveness and cost-effectiveness of IoT in managing chronic diseases within clinical settings. Participants will undergo baseline assessment, physical examination and nocturnal oxygen saturation measuring. Specific questionnaires screening for OSA will also be administered. Diagnostic lung function tests and polysomnography will be performed to confirm COPD and OSA, respectively. All patients will undergo scheduled follow-ups for 12 months to record the changes in symptoms, lung functions and quality of life. Primary outcomes include the prevalence and characteristics of OS, while secondary outcomes encompass OS prognosis and the feasibility of the management model in clinical contexts. A total of 682 patients with COPD will be recruited over 12-24 months. ETHICS AND DISSEMINATION The study has been approved by Peking University Third Hospital, and all study participants will provide written informed consent. Study results will be published in an appropriate journal and presented at national and international conferences, as well as relevant social media and various stakeholder engagement activities. TRIAL REGISTRATION NUMBER NCT04833725.
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Affiliation(s)
- Zihan Pan
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
- General Practice Medicine, Peking University First Hospital, Beijing, China
| | - Sha Liao
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Wanlu Sun
- Department of Pulmonary and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Beijing, China
| | - Haoyi Zhou
- School of Software, Beihang University, Beijing, China
| | - Shuo Lin
- Air Liquide Healthcare (Beijing), Beijing, China
| | - Dian Chen
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Simin Jiang
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Huanyu Long
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Jing Fan
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Wenlou Zhang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Baiqi Chen
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Junyi Wang
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Yongwei Huang
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
- Sleep Monitoring Center, Peking University Third Hospital, Beijing, China
| | - Jianxin Li
- School of Computer Science and Engineering, Beihang University, Beijing, China
| | - Yahong Chen
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
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4
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Piet A, Jablonski L, Daniel Onwuchekwa JI, Unkel S, Weber C, Grzegorzek M, Ehlers JP, Gaus O, Neumann T. Non-Invasive Wearable Devices for Monitoring Vital Signs in Patients with Type 2 Diabetes Mellitus: A Systematic Review. Bioengineering (Basel) 2023; 10:1321. [PMID: 38002444 PMCID: PMC10669651 DOI: 10.3390/bioengineering10111321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/10/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Type 2 diabetes mellitus (T2D) poses a significant global health challenge and demands effective self-management strategies, including continuous blood glucose monitoring (CGM) and lifestyle adaptations. While CGM offers real-time glucose level assessment, the quest for minimizing trauma and enhancing convenience has spurred the need to explore non-invasive alternatives for monitoring vital signs in patients with T2D. Objective: This systematic review is the first that explores the current literature and critically evaluates the use and reporting of non-invasive wearable devices for monitoring vital signs in patients with T2D. Methods: Employing the PRISMA and PICOS guidelines, we conducted a comprehensive search to incorporate evidence from relevant studies, focusing on randomized controlled trials (RCTs), systematic reviews, and meta-analyses published since 2017. Of the 437 publications identified, seven were selected based on predetermined criteria. Results: The seven studies included in this review used various sensing technologies, such as heart rate monitors, accelerometers, and other wearable devices. Primary health outcomes included blood pressure measurements, heart rate, body fat percentage, and cardiorespiratory endurance. Non-invasive wearable devices demonstrated potential for aiding T2D management, albeit with variations in efficacy across studies. Conclusions: Based on the low number of studies with higher evidence levels (i.e., RCTs) that we were able to find and the significant differences in design between these studies, we conclude that further evidence is required to validate the application, efficacy, and real-world impact of these wearable devices. Emphasizing transparency in bias reporting and conducting in-depth research is crucial for fully understanding the implications and benefits of wearable devices in T2D management.
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Affiliation(s)
- Artur Piet
- Institute of Medical Informatics, University of Lübeck, 23562 Lübeck, Germany
| | - Lennart Jablonski
- Institute of Medical Informatics, University of Lübeck, 23562 Lübeck, Germany
| | | | - Steffen Unkel
- Department of Digital Health Sciences and Biomedicine, University of Siegen, 57076 Siegen, Germany
- Department of Medical Statistics, University Medical Center Göttingen, 37075 Göttingen, Germany
| | - Christian Weber
- Department of Digital Health Sciences and Biomedicine, University of Siegen, 57076 Siegen, Germany
| | - Marcin Grzegorzek
- Institute of Medical Informatics, University of Lübeck, 23562 Lübeck, Germany
- Department of Knowledge Engineering, University of Economics in Katowice, 40-287 Katowice, Poland
| | - Jan P. Ehlers
- Department of Didactics and Educational Research in Health Science, Witten/Herdecke University, 58455 Witten, Germany
| | - Olaf Gaus
- Department of Digital Health Sciences and Biomedicine, University of Siegen, 57076 Siegen, Germany
| | - Thomas Neumann
- Department of Digital Health Sciences and Biomedicine, University of Siegen, 57076 Siegen, Germany
- Faculty of Economics and Management, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany
- University Department of Neurology, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany
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5
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Drummond CK, Tandon A. Advancing Wearable Technology for Monitoring Heart Activity in Paediatric Populations. CJC PEDIATRIC AND CONGENITAL HEART DISEASE 2023; 2:196-197. [PMID: 37969856 PMCID: PMC10642130 DOI: 10.1016/j.cjcpc.2023.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 06/29/2023] [Indexed: 11/17/2023]
Affiliation(s)
- Colin K. Drummond
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Animesh Tandon
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Pediatric Cardiology, Children’s Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Department of Pediatrics, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio, USA
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
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6
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Clay I, De Luca V, Sano A. Editorial: Multimodal digital approaches to personalized medicine. Front Big Data 2023; 6:1242482. [PMID: 37469442 PMCID: PMC10352833 DOI: 10.3389/fdata.2023.1242482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 06/26/2023] [Indexed: 07/21/2023] Open
Affiliation(s)
- Ieuan Clay
- Vivosense Inc., Newport Coast, CA, United States
| | - Valeria De Luca
- Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Akane Sano
- Department of Electrical Computer Engineering, Computer Science, and Bioengineering, Rice University, Houston, TX, United States
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7
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Jacobsen M, Gholamipoor R, Dembek TA, Rottmann P, Verket M, Brandts J, Jäger P, Baermann BN, Kondakci M, Heinemann L, Gerke AL, Marx N, Müller-Wieland D, Möllenhoff K, Seyfarth M, Kollmann M, Kobbe G. Wearable based monitoring and self-supervised contrastive learning detect clinical complications during treatment of Hematologic malignancies. NPJ Digit Med 2023; 6:105. [PMID: 37268734 DOI: 10.1038/s41746-023-00847-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 05/19/2023] [Indexed: 06/04/2023] Open
Abstract
Serious clinical complications (SCC; CTCAE grade ≥ 3) occur frequently in patients treated for hematological malignancies. Early diagnosis and treatment of SCC are essential to improve outcomes. Here we report a deep learning model-derived SCC-Score to detect and predict SCC from time-series data recorded continuously by a medical wearable. In this single-arm, single-center, observational cohort study, vital signs and physical activity were recorded with a wearable for 31,234 h in 79 patients (54 Inpatient Cohort (IC)/25 Outpatient Cohort (OC)). Hours with normal physical functioning without evidence of SCC (regular hours) were presented to a deep neural network that was trained by a self-supervised contrastive learning objective to extract features from the time series that are typical in regular periods. The model was used to calculate a SCC-Score that measures the dissimilarity to regular features. Detection and prediction performance of the SCC-Score was compared to clinical documentation of SCC (AUROC ± SD). In total 124 clinically documented SCC occurred in the IC, 16 in the OC. Detection of SCC was achieved in the IC with a sensitivity of 79.7% and specificity of 87.9%, with AUROC of 0.91 ± 0.01 (OC sensitivity 77.4%, specificity 81.8%, AUROC 0.87 ± 0.02). Prediction of infectious SCC was possible up to 2 days before clinical diagnosis (AUROC 0.90 at -24 h and 0.88 at -48 h). We provide proof of principle for the detection and prediction of SCC in patients treated for hematological malignancies using wearable data and a deep learning model. As a consequence, remote patient monitoring may enable pre-emptive complication management.
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Affiliation(s)
- Malte Jacobsen
- Faculty of Health, University Witten/Herdecke, 58448, Witten, Germany.
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074, Aachen, Germany.
| | - Rahil Gholamipoor
- Department of Computer Science, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Till A Dembek
- Department of Neurology, Faculty of Medicine, University of Cologne, 50937, Cologne, Germany
| | - Pauline Rottmann
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Marlo Verket
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074, Aachen, Germany
| | - Julia Brandts
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074, Aachen, Germany
| | - Paul Jäger
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Ben-Niklas Baermann
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Mustafa Kondakci
- Department of Oncology and Hematology, St. Lukas Hospital Solingen, 42697, Solingen, Germany
| | | | - Anna L Gerke
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Nikolaus Marx
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074, Aachen, Germany
| | - Dirk Müller-Wieland
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074, Aachen, Germany
| | - Kathrin Möllenhoff
- Mathematical Institute, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
| | - Melchior Seyfarth
- Faculty of Health, University Witten/Herdecke, 58448, Witten, Germany
- Department of Cardiology, Helios University Hospital Wuppertal, 42117, Wuppertal, Germany
| | - Markus Kollmann
- Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany.
| | - Guido Kobbe
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
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8
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Huhn S, Axt M, Gunga HC, Maggioni MA, Munga S, Obor D, Sié A, Boudo V, Bunker A, Sauerborn R, Bärnighausen T, Barteit S. The Impact of Wearable Technologies in Health Research: Scoping Review. JMIR Mhealth Uhealth 2022; 10:e34384. [PMID: 35076409 PMCID: PMC8826148 DOI: 10.2196/34384] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/23/2021] [Accepted: 12/17/2021] [Indexed: 12/23/2022] Open
Abstract
Background Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. Objective In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. Methods We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. Results We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Conclusions Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.
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Affiliation(s)
- Sophie Huhn
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Miriam Axt
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Hanns-Christian Gunga
- Charité - Universitätsmedizin Berlin, Institute of Physiology, Center for Space Medicine and Extreme Environment, Berlin, Germany
| | - Martina Anna Maggioni
- Charité - Universitätsmedizin Berlin, Institute of Physiology, Center for Space Medicine and Extreme Environment, Berlin, Germany.,Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milano, Italy
| | | | - David Obor
- Kenya Medical Research Institute, Kisumu, Kenya
| | - Ali Sié
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.,Centre de Recherche en Santé Nouna, Nouna, Burkina Faso
| | | | - Aditi Bunker
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Rainer Sauerborn
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
| | - Till Bärnighausen
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany.,Harvard Center for Population and Development Studies, Cambridge, MA, United States.,Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - Sandra Barteit
- Heidelberg Institute of Global Health, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
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9
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Jacobsen M, Rottmann P, Dembek TA, Gerke AL, Gholamipoor R, Blum C, Hartmann NU, Verket M, Kaivers J, Jäger P, Baermann BN, Heinemann L, Marx N, Müller-Wieland D, Kollmann M, Seyfarth M, Kobbe G. Feasibility of Wearable-Based Remote Monitoring in Patients During Intensive Treatment for Aggressive Hematologic Malignancies. JCO Clin Cancer Inform 2022; 6:e2100126. [PMID: 35025669 DOI: 10.1200/cci.21.00126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
PURPOSE Intensive treatment protocols for aggressive hematologic malignancies harbor a high risk of serious clinical complications, such as infections. Current techniques of monitoring vital signs to detect such complications are cumbersome and often fail to diagnose them early. Continuous monitoring of vital signs and physical activity by means of an upper arm medical wearable allowing 24/7 streaming of such parameters may be a promising alternative. METHODS This single-arm, single-center observational trial evaluated symptom-related patient-reported outcomes and feasibility of a wearable-based remote patient monitoring. All wearable data were reviewed retrospectively and were not available to the patient or clinical staff. A total of 79 patients (54 inpatients and 25 outpatients) participated and received standard-of-care treatment for a hematologic malignancy. In addition, the wearable was continuously worn and self-managed by the patient to record multiple parameters such as heart rate, oxygen saturation, and physical activity. RESULTS Fifty-one patients (94.4%) in the inpatient cohort and 16 (64.0%) in the outpatient cohort reported gastrointestinal symptoms (diarrhea, nausea, and emesis), pain, dyspnea, or shivering in at least one visit. With the wearable, vital signs and physical activity were recorded for a total of 1,304.8 days. Recordings accounted for 78.0% (63.0-88.5; median [interquartile range]) of the potential recording time for the inpatient cohort and 84.6% (76.3-90.2) for the outpatient cohort. Adherence to the wearable was comparable in both cohorts, but decreased moderately over time during the trial. CONCLUSION A high adherence to the wearable was observed in patients on intensive treatment protocols for a hematologic malignancy who experience high symptom burden. Remote patient monitoring of vital signs and physical activity was demonstrated to be feasible and of primarily sufficient quality.
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Affiliation(s)
- Malte Jacobsen
- Faculty of Health, University Witten/Herdecke, Witten, Germany.,Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Pauline Rottmann
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Till A Dembek
- Department of Neurology, Faculty of Medicine, University of Cologne, Cologne, Germany
| | - Anna L Gerke
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Rahil Gholamipoor
- Department of Computer Science, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christopher Blum
- Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Niels-Ulrik Hartmann
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Marlo Verket
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Jennifer Kaivers
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Paul Jäger
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ben-Niklas Baermann
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Nikolaus Marx
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Dirk Müller-Wieland
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | - Markus Kollmann
- Department of Biology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Melchior Seyfarth
- Faculty of Health, University Witten/Herdecke, Witten, Germany.,Department of Cardiology, Helios University Hospital of Wuppertal, Wuppertal, Germany
| | - Guido Kobbe
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Düsseldorf, Germany.,Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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10
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Boyer J, Eckmann J, Strohmayer K, Koele W, Federspiel M, Schenk M, Weiss G, Krause R. Investigation of Non-invasive Continuous Body Temperature Measurements in a Clinical Setting Using an Adhesive Axillary Thermometer (SteadyTemp®). Front Digit Health 2022; 3:794274. [PMID: 34970650 PMCID: PMC8712449 DOI: 10.3389/fdgth.2021.794274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/23/2021] [Indexed: 11/13/2022] Open
Abstract
Since the human body reacts to a variety of different diseases with elevated body temperature, measurement of body temperature remains relevant in clinical practice. The absolute temperature value for fever definition is still arbitrary and depends on the measuring site, as well as underlying disease and individual factors. Hence, a simple threshold for fever definition is outdated and a definition which relies on the relative changes in the individual seems reasonable as it takes these individual factors into account. In this prospective multicentric study we validate an adhesive axillary thermometer (SteadyTemp®) which allows continuous non-invasive temperature measurements. It consists of a patch to measure temperature and a smartphone application to process and visualize gathered data. This article provides information of the new diagnostic possibilities when using this wearable device and where it could be beneficial. Furthermore, it discusses how to interpret the generated data and when it is not practical to use, based on its characteristics and physiological phenomena.
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Affiliation(s)
- Johannes Boyer
- Department of Infectious Diseases and Tropical Medicine, Medical University of Graz, Graz, Austria
| | | | | | | | | | | | - Gregor Weiss
- Das Kinderwunsch Institut Schenk GmbH, Dobl, Austria
| | - Robert Krause
- Department of Infectious Diseases and Tropical Medicine, Medical University of Graz, Graz, Austria.,BioTechMed Graz, Graz, Austria
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11
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Ellebrecht DB, Gola D, Kaschwich M. Evaluation of a Wearable in-Ear Sensor for Temperature and Heart Rate Monitoring: A Pilot Study. J Med Syst 2022; 46:91. [PMID: 36329338 PMCID: PMC9633487 DOI: 10.1007/s10916-022-01872-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 09/28/2022] [Indexed: 11/06/2022]
Abstract
In the context of the COVID-19 pandemic, wearable sensors are important for early detection of critical illness especially in COVID-19 outpatients. We sought to determine in this pilot study whether a wearable in-ear sensor for continuous body temperature and heart rate monitoring (Cosinuss company, Munich) is sufficiently accurate for body temperature and heart rate monitoring. Comparing with several anesthesiologic standard of care monitoring devices (urinary bladder and zero-heat flux thermometer and ECG), we evaluated the in-ear sensor during non-cardiac surgery (German Clinical Trials Register Reg.-No: DRKS00012848). Limits of Agreement (LoA) based on Bland-Altman analysis were used to study the agreement between the in-ear sensor and the reference methods. The estimated LoA of the Cosinuss One and bladder temperature monitoring were [-0.79, 0.49] °C (95% confidence intervals [-1.03, -0.65] (lower LoA) and [0.35, 0.73] (upper LoA)), and [-0.78, 0.34] °C (95% confidence intervals [-1.18, -0.59] (lower LoA) and [0.16, 0.74] (upper LoA)) of the Cosinuss One and zero-heat flux temperature monitoring. 89% and 79% of Cosinuss One temperature monitoring were within ± 0.5 °C limit of bladder and zero-heat flux monitoring, respectively. The estimated LoA of Cosinuss One and ECG heart rate monitoring were [-4.81, 4.27] BPM (95% confidence intervals [-5.09, -4.56] (lower LoA) and [4.01, 4.54] (upper LoA)). The proportion of detection differences within ± 2BPM was 84%. Body temperature and heart rate were reliably measured by the wearable in-ear sensor.
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Affiliation(s)
- David Benjamin Ellebrecht
- grid.412468.d0000 0004 0646 2097Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538 Luebeck, Germany ,grid.414769.90000 0004 0493 3289Department of Thoracic Surgery, LungenClinic Großhansdorf, Woehrendamm 80, 22927 Grosshansdorf, Germany
| | - Damian Gola
- grid.4562.50000 0001 0057 2672Institute of Medical Biometry and Statistics, University of Lübeck, Ratzeburger Allee 160, 23562 Luebeck, Germany
| | - Mark Kaschwich
- grid.412468.d0000 0004 0646 2097Department of Surgery, University Medical Center Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538 Luebeck, Germany ,Department of Vascular Medicine, University Heart & Vascular Centre Hamburg, Martinistraße 52, 20246 Hamburg, Germany
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12
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Fan EMPJ, Ang SY, Phua GC, Chen Ee L, Wong KC, Tan FCP, Tan LWH, Ayre TC, Chua CY, Tan BWB, Yeo KK. Factors to Consider in the Use of Vital Signs Wearables to Minimize Contact With Stable COVID-19 Patients: Experience of Its Implementation During the Pandemic. Front Digit Health 2021; 3:639827. [PMID: 34713111 PMCID: PMC8521954 DOI: 10.3389/fdgth.2021.639827] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 08/16/2021] [Indexed: 11/13/2022] Open
Abstract
The COVID-19 pandemic has created a huge burden on the healthcare industry worldwide. Pressures to increase the isolation healthcare facility to cope with the growing number of patients led to an exploration of the use of wearables for vital signs monitoring among stable COVID-19 patients. Vital signs wearables were chosen for use in our facility with the purpose of reducing patient contact and preserving personal protective equipment. The process of deciding on the wearable solution as well as the implementation of the solution brought much insight to the team. This paper presents an overview of factors to consider in implementing a vital signs wearable solution. This includes considerations before deciding on whether or not to use a wearable device, followed by key criteria of the solution to assess. With the use of wearables rising in popularity, this serves as a guide for others who may want to implement it in their institutions.
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Affiliation(s)
| | - Shin Yuh Ang
- Nursing Division, Singapore General Hospital, Singapore, Singapore
| | - Ghee Chee Phua
- Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore, Singapore
| | - Lee Chen Ee
- Organisational Transformation, SingHealth, Singapore, Singapore
| | - Kok Cheong Wong
- Nursing Division, Changi General Hospital, Singapore, Singapore
| | | | | | - Tracy Carol Ayre
- Nursing Division, Singapore General Hospital, Singapore, Singapore
| | - Chee Yong Chua
- Emerging Services and Capabilities Group, Integrated Health Information Systems, Singapore, Singapore
| | | | - Khung Keong Yeo
- Department of Cardiology, National Heart Centre Singapore, Singapore, Singapore.,Duke-National University of Singapore Medical School, Singapore, Singapore
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13
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Sidikova M, Martinek R, Kawala-Sterniuk A, Ladrova M, Jaros R, Danys L, Simonik P. Vital Sign Monitoring in Car Seats Based on Electrocardiography, Ballistocardiography and Seismocardiography: A Review. SENSORS 2020; 20:s20195699. [PMID: 33036313 PMCID: PMC7582509 DOI: 10.3390/s20195699] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/29/2020] [Accepted: 09/30/2020] [Indexed: 12/15/2022]
Abstract
This paper focuses on a thorough summary of vital function measuring methods in vehicles. The focus of this paper is to summarize and compare already existing methods integrated into car seats with the implementation of inter alia capacitive electrocardiogram (cECG), mechanical motion analysis Ballistocardiography (BCG) and Seismocardiography (SCG). In addition, a comprehensive overview of other methods of vital sign monitoring, such as camera-based systems or steering wheel sensors, is also presented in this article. Furthermore, this work contains a very thorough background study on advanced signal processing methods and their potential application for the purpose of vital sign monitoring in cars, which is prone to various disturbances and artifacts occurrence that have to be eliminated.
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Affiliation(s)
- Michaela Sidikova
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
- Correspondence: (M.S.); (R.M.)
| | - Radek Martinek
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
- Correspondence: (M.S.); (R.M.)
| | - Aleksandra Kawala-Sterniuk
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Proszkowska 76, 45-758 Opole, Poland;
| | - Martina Ladrova
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Rene Jaros
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Lukas Danys
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
| | - Petr Simonik
- Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17 Listopadu 15, 70800 Ostrava, Czech Republic; (M.L.); (R.J.); (L.D.); (P.S.)
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14
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Jacobsen M, Dembek TA, Ziakos AP, Gholamipoor R, Kobbe G, Kollmann M, Blum C, Müller-Wieland D, Napp A, Heinemann L, Deubner N, Marx N, Isenmann S, Seyfarth M. Reliable Detection of Atrial Fibrillation with a Medical Wearable during Inpatient Conditions. SENSORS 2020; 20:s20195517. [PMID: 32993132 PMCID: PMC7583973 DOI: 10.3390/s20195517] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 01/19/2023]
Abstract
Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study sims to evaluate the sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.
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Affiliation(s)
- Malte Jacobsen
- Faculty of Health, University Witten/Herdecke, 58448 Witten, Germany; (A.-P.Z.); (N.D.); (S.I.); (M.S.)
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (D.M.-W.); (A.N.); (N.M.)
- Correspondence: ; Tel.: +49-173-560-6980
| | - Till A. Dembek
- Department of Neurology, Faculty of Medicine, University of Cologne, 50937 Cologne, Germany;
| | - Athanasios-Panagiotis Ziakos
- Faculty of Health, University Witten/Herdecke, 58448 Witten, Germany; (A.-P.Z.); (N.D.); (S.I.); (M.S.)
- Department of Cardiology, Helios University Hospital of Wuppertal, 42117 Wuppertal, Germany
| | - Rahil Gholamipoor
- Department of Computer Science, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany;
| | - Guido Kobbe
- Department of Hematology, Oncology, and Clinical Immunology, University Hospital Düsseldorf, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany;
| | - Markus Kollmann
- Department of Biology, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; (M.K.); (C.B.)
| | - Christopher Blum
- Department of Biology, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany; (M.K.); (C.B.)
| | - Dirk Müller-Wieland
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (D.M.-W.); (A.N.); (N.M.)
| | - Andreas Napp
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (D.M.-W.); (A.N.); (N.M.)
| | | | - Nikolas Deubner
- Faculty of Health, University Witten/Herdecke, 58448 Witten, Germany; (A.-P.Z.); (N.D.); (S.I.); (M.S.)
- Department of Cardiology, Helios University Hospital of Wuppertal, 42117 Wuppertal, Germany
| | - Nikolaus Marx
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, 52074 Aachen, Germany; (D.M.-W.); (A.N.); (N.M.)
| | - Stefan Isenmann
- Faculty of Health, University Witten/Herdecke, 58448 Witten, Germany; (A.-P.Z.); (N.D.); (S.I.); (M.S.)
- Department of Neurology, St. Josef Hospital, 47441 Moers, Germany
| | - Melchior Seyfarth
- Faculty of Health, University Witten/Herdecke, 58448 Witten, Germany; (A.-P.Z.); (N.D.); (S.I.); (M.S.)
- Department of Cardiology, Helios University Hospital of Wuppertal, 42117 Wuppertal, Germany
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