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Buss A, Areia C, Biggs C, Edmundson H, Young L, Roman C, Santos M, Tarassenko L, Watkinson P, Vollam S. Using a novel ambulatory monitoring system to support patient safety on an acute infectious disease ward during an unfolding pandemic. J Adv Nurs 2024; 80:2452-2461. [PMID: 38054397 DOI: 10.1111/jan.15977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 10/16/2023] [Accepted: 11/09/2023] [Indexed: 12/07/2023]
Abstract
AIM To gain staff feedback on the implementation and impact of a novel ambulatory monitoring system to support coronavirus patient management on an isolation ward. DESIGN Qualitative service evaluation. METHODS Semi-structured interviews were conducted with 15 multidisciplinary isolation ward staff in the United Kingdom between July 2020 and May 2021. Interviews were audio-recorded, transcribed and analysed using thematic analysis. FINDINGS Adopting Innovation to Assist Patient Safety was identified as the overriding theme. Three interlinked sub-themes represent facets of how the system supported patient safety. Patient Selection was developed throughout the pandemic, as clinical staff became more confident in choosing which patients would benefit most. Trust In the System described how nurses coped with discrepancies between the ambulatory system and ward observation machines. Finally, Resource Management examined how, once trust was built, staff perceived the ambulatory system assisted with caseload management. This supported efficient personal protective equipment resource use by reducing the number of isolation room entries. Despite these reported benefits, face-to-face contact was still highly valued, despite the risk of coronavirus exposure. CONCLUSION Hospital wards should consider using ambulatory monitoring systems to support caseload management and patient safety. Patients in isolation rooms or at high risk of deterioration may particularly benefit from this additional monitoring. However, these systems should be seen as an adjunct to nursing care, not a replacement. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE Nurses valued ambulatory monitoring as a means of ensuring the safety of patients at risk of deterioration and prioritizing their workload. IMPACT The findings of this research will be useful to all those developing or considering implementation of ambulatory monitoring systems in hospital wards. REPORTING METHOD This manuscript follows the Consolidated criteria for Reporting Qualitative Research (COREQ) guidelines with inclusion of relevant SQUIRE guidelines for reporting quality improvement. PATIENT OR PUBLIC CONTRIBUTION No Patient or Public Contribution.
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Affiliation(s)
- Annika Buss
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Allied Health Professions Research & Innovation Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Carlos Areia
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Christopher Biggs
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Holly Edmundson
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Louise Young
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Cristian Roman
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Mauro Santos
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Lionel Tarassenko
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Peter Watkinson
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Sarah Vollam
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
- OXinAHR, Oxford Brookes University, Oxford, UK
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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] [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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Rivas E, López-Baamonde M, Sanahuja J, Del Rio E, Ramis T, Recasens A, López A, Arias M, Kampakis S, Lauteslager T, Awara O, Mascha EJ, Soriano A, Badía JR, Castro P, Sessler DI. Early detection of deterioration in COVID-19 patients by continuous ward respiratory rate monitoring: a pilot prospective cohort study. Front Med (Lausanne) 2023; 10:1243050. [PMID: 38020176 PMCID: PMC10645134 DOI: 10.3389/fmed.2023.1243050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 10/12/2023] [Indexed: 12/01/2023] Open
Abstract
Background Tachypnea is among the earliest signs of pulmonary decompensation. Contactless continuous respiratory rate monitoring might be useful in isolated COVID-19 patients admitted in wards. We therefore aimed to determine whether continuous monitoring of respiratory patterns in hospitalized patients with COVID-19 predicts subsequent need for increased respiratory support. Methods Single-center pilot prospective cohort study in COVID-19 patients who were cared for in routine wards. COVID-19 patients who had at least one escalation of pulmonary management were matched to three non-escalated patients. Contactless respiratory monitoring was instituted after patients enrolled, and continued for 15 days unless hospital discharge, initiation of invasive mechanical ventilation, or death occurred. Clinicians were blinded to respiratory rate data from the continuous monitor. The exposures were respiratory features over rolling periods of 30 min, 24 h, and 72 h before respiratory care escalation. The primary outcome was a subsequent escalation in ventilatory support beyond a Venturi mask. Results Among 125 included patients, 13 exhibited at least one escalation and were each matched to three non-escalated patients. A total of 28 escalation events were matched to 84 non-escalation episodes. The 30-min mean respiratory rate in escalated patients was 23 breaths per minute (bpm) ranging from 13 to 40 bpm, similar to the 22 bpm in non-escalated patients, although with less variability (range 14 to 31 bpm). However, higher respiratory rate variability, especially skewness over 1 day, was associated with higher incidence of escalation events. Our overall model, based on continuous data, had a moderate accuracy with an AUC 0.81 (95%CI: 0.73, 0.88) and a good specificity 0.93 (95%CI: 0.87, 0.99). Conclusion Our pilot observational study suggests that respiratory rate variability as detected with continuous monitoring is associated with subsequent care escalation during the following 24 h. Continuous respiratory monitoring thus appears to be a valuable increment over intermittent monitoring. Strengths and limitations Our study was the initial evaluation of Circadia contactless respiratory monitoring in COVID-19 patients who are at special risk of pulmonary deterioration. The major limitation is that the analysis was largely post hoc and thus needs to be confirmed in an out-of-sample population.
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Affiliation(s)
- Eva Rivas
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
- Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States
| | - Manuel López-Baamonde
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Josep Sanahuja
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Elena Del Rio
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Tomeu Ramis
- Department of Anesthesiology and Critical Care, Hosptial Universitary Son Espases, Mallorca, Spain
| | - Anna Recasens
- Department of Anesthesiology, Hospital del Mar. Institut Hospital del Mar d’Investigacions Mèdiques (IMIM), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Antonio López
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Marilyn Arias
- Department of Anesthesia, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | | | | | - Osama Awara
- Circadia Technologies, Ltd., London, United Kingdom
| | - Edward J. Mascha
- Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, United States
| | - Alex Soriano
- Department of Infectious Disease, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, CIBERINF, Barcelona, Spain
| | - Joan Ramon Badía
- Department of Pneumology, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Pedro Castro
- Medical Intensive Care Unit, Hospital Clinic of Barcelona, IDIBAPS, Universidad de Barcelona, Barcelona, Spain
| | - Daniel I. Sessler
- Department of Outcomes Research, Cleveland Clinic, Cleveland, OH, United States
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Chau NVV, Trung TN, Khanh PNQK, Nhat PTH, Van HMT, Hai HB, Thuy DB, Tung NLN, Khoa DB, Vien TTD, Hao NV, Oanh PKN, Khoa TD, Phong NT, Nguyen NT, Huynh J, Walker TM, Van Nuil J, An LP, McKnight J, Toan LM, Tan LV, Dung NT, Truong NT, Thwaites CL. Wearable devices for remote monitoring of hospitalized patients with COVID-19 in Vietnam. Wellcome Open Res 2023; 7:257. [PMID: 38601327 PMCID: PMC11004598 DOI: 10.12688/wellcomeopenres.18026.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/07/2023] [Indexed: 04/12/2024] Open
Abstract
Patients with severe COVID-19 disease require monitoring with pulse oximetry as a minimal requirement. In many low- and middle- income countries, this has been challenging due to lack of staff and equipment. Wearable pulse oximeters potentially offer an attractive means to address this need, due to their low cost, battery operability and capacity for remote monitoring. Between July and October 2021, Ho Chi Minh City experienced its first major wave of SARS-CoV-2 infection, leading to an unprecedented demand for monitoring in hospitalized patients. We assess the feasibility of a continuous remote monitoring system for patients with COVID-19 under these circumstances as we implemented 2 different systems using wearable pulse oximeter devices in a stepwise manner across 4 departments.
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Affiliation(s)
| | | | | | - Phung Tran Huy Nhat
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Kings College, London, UK
| | | | - Ho Bich Hai
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | | | | | - Dao Bach Khoa
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | | | - Nguyen Van Hao
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
- University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
| | | | - Tran Dang Khoa
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | | | | | - Julie Huynh
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Timothy M Walker
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Jennifer Van Nuil
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - Luu Phuoc An
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Jacob McKnight
- Health Systems Collaborative, University of Oxford, Oxford, UK
| | - Le Mau Toan
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
| | - Le Van Tan
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | | | | | - C Louise Thwaites
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
| | - OUCRU COVID Research Group
- Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam
- Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Kings College, London, UK
- University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, University of Oxford, Oxford, UK
- Health Systems Collaborative, University of Oxford, Oxford, UK
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Peters GM, Peelen RV, Gilissen VJ, Koning MV, van Harten WH, Doggen CJM. Detecting Patient Deterioration Early Using Continuous Heart rate and Respiratory rate Measurements in Hospitalized COVID-19 Patients. J Med Syst 2023; 47:12. [PMID: 36692798 PMCID: PMC9871416 DOI: 10.1007/s10916-022-01898-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Revised: 11/25/2022] [Accepted: 12/05/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND Presenting symptoms of COVID-19 patients are unusual compared with many other illnesses. Blood pressure, heart rate, and respiratory rate may stay within acceptable ranges as the disease progresses. Consequently, intermittent monitoring does not detect deterioration as it is happening. We investigated whether continuously monitoring heart rate and respiratory rate enables earlier detection of deterioration compared with intermittent monitoring, or introduces any risks. METHODS When available, patients admitted to a COVID-19 ward received a wireless wearable sensor which continuously measured heart rate and respiratory rate. Two intensive care unit (ICU) physicians independently assessed sensor data, indicating when an intervention might be necessary (alarms). A third ICU physician independently extracted clinical events from the electronic medical record (EMR events). The primary outcome was the number of true alarms. Secondary outcomes included the time difference between true alarms and EMR events, interrater agreement for the alarms, and severity of EMR events that were not detected. RESULTS In clinical practice, 48 (EMR) events occurred. None of the 4 ICU admissions were detected with the sensor. Of the 62 sensor events, 13 were true alarms (also EMR events). Of these, two were related to rapid response team calls. The true alarms were detected 39 min (SD = 113) before EMR events, on average. Interrater agreement was 10%. Severity of the 38 non-detected events was similar to the severity of 10 detected events. CONCLUSION Continuously monitoring heart rate and respiratory rate does not reliably detect deterioration in COVID-19 patients when assessed by ICU physicians.
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Affiliation(s)
- Guido M Peters
- Clinical Research Center, Rijnstate Hospital, Arnhem, The Netherlands
- Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| | - Roel V Peelen
- Department of Anaesthesiology, Critical Care and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | - Vincent Jhs Gilissen
- Department of Anaesthesiology, Critical Care and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | - Mark V Koning
- Department of Anaesthesiology, Critical Care and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | - Wim H van Harten
- Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
- Rijnstate Hospital, Arnhem, The Netherlands
| | - Carine J M Doggen
- Clinical Research Center, Rijnstate Hospital, Arnhem, The Netherlands.
- Department of Health Technology and Services Research, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
- Scientific Bureau, Rijnstate Hospital, Wagnerlaan 55, PO Box 9555, 6800 TA, Arnhem, The Netherlands.
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Chau NVV, Trung TN, Khanh PNQK, Nhat PTH, Van HMT, Hai HB, Thuy DB, Tung NLN, Khoa DB, Vien TTD, Hao NV, Oanh PKN, Khoa TD, Phong NT, Nguyen NT, Huynh J, Walker TM, Van Nuil J, An LP, McKnight J, Toan LM, Tan LV, Dung NT, Truong NT, Thwaites CL. Wearable devices for remote monitoring of hospitalized patients with COVID-19 in Vietnam. Wellcome Open Res 2022. [DOI: 10.12688/wellcomeopenres.18026.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Patients with severe COVID-19 disease require monitoring with pulse oximetry as a minimal requirement. In many low- and middle- income countries, this has been challenging due to lack of staff and equipment. Wearable pulse oximeters potentially offer an attractive means to address this need, due to their low cost, battery operability and capacity for remote monitoring. Between July and October 2021, Ho Chi Minh City experienced its first major wave of SARS-CoV-2 infection, leading to an unprecedented demand for monitoring in hospitalized patients. We assess the feasibility of a continuous remote monitoring system for patients with COVID-19 under these circumstances as we implemented 2 different systems using wearable pulse oximeter devices in a stepwise manner across 4 departments.
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7
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Cheong SHR, Ng YJX, Lau Y, Lau ST. Wearable technology for early detection of COVID-19: A systematic scoping review. Prev Med 2022; 162:107170. [PMID: 35878707 PMCID: PMC9304072 DOI: 10.1016/j.ypmed.2022.107170] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 06/29/2022] [Accepted: 07/17/2022] [Indexed: 11/23/2022]
Abstract
Wearable technology is an emerging method for the early detection of coronavirus disease 2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and accuracy of wearable technology for the early detection of COVID-19. This review was conducted according to the five-step framework of Arksey and O'Malley. Studies published between December 31, 2019 and December 15, 2021 were obtained from 10 electronic databases, namely, PubMed, Embase, Cochrane, CINAHL, PsycINFO, ProQuest, Scopus, Web of Science, IEEE Xplore, and Taylor & Francis Online. Grey literature, reference lists, and key journals were also searched. All types of articles describing wearable technology for the detection of COVID-19 infection were included. Two reviewers independently screened the articles against the eligibility criteria and extracted the data using a data charting form. A total of 40 articles were included in this review. There are 22 different types of wearable technology used to detect COVID-19 infections early in the existing literature and are categorized as smartwatches or fitness trackers (67%), medical devices (27%), or others (6%). Based on deviations in physiological characteristics, anomaly detection models that can detect COVID-19 infection early were built using artificial intelligence or statistical analysis techniques. Reported area-under-the-curve values ranged from 75% to 94.4%, and sensitivity and specificity values ranged from 36.5% to 100% and 73% to 95.3%, respectively. Further research is necessary to validate the effectiveness and clinical dependability of wearable technology before healthcare policymakers can mandate its use for remote surveillance.
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Affiliation(s)
- Shing Hui Reina Cheong
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Yu Jie Xavia Ng
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Ying Lau
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
| | - Siew Tiang Lau
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
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8
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Kuo C, Patton D, Rooks T, Tierney G, McIntosh A, Lynall R, Esquivel A, Daniel R, Kaminski T, Mihalik J, Dau N, Urban J. On-Field Deployment and Validation for Wearable Devices. Ann Biomed Eng 2022; 50:1372-1388. [PMID: 35960418 DOI: 10.1007/s10439-022-03001-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 06/24/2022] [Indexed: 11/01/2022]
Abstract
Wearable sensors are an important tool in the study of head acceleration events and head impact injuries in sporting and military activities. Recent advances in sensor technology have improved our understanding of head kinematics during on-field activities; however, proper utilization and interpretation of data from wearable devices requires careful implementation of best practices. The objective of this paper is to summarize minimum requirements and best practices for on-field deployment of wearable devices for the measurement of head acceleration events in vivo to ensure data evaluated are representative of real events and limitations are accurately defined. Best practices covered in this document include the definition of a verified head acceleration event, data windowing, video verification, advanced post-processing techniques, and on-field logistics, as determined through review of the literature and expert opinion. Careful use of best practices, with accurate acknowledgement of limitations, will allow research teams to ensure data evaluated is representative of real events, will improve the robustness of head acceleration event exposure studies, and generally improve the quality and validity of research into head impact injuries.
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Affiliation(s)
- Calvin Kuo
- The University of British Columbia, Vancouver, Canada
| | - Declan Patton
- Children's Hospital of Philadelphia, Philadelphia, USA
| | - Tyler Rooks
- United States Army Aeromedical Research Laboratory, Fort Rucker, USA
| | | | - Andrew McIntosh
- McIntosh Consultancy and Research, Sydney, Australia.,Monash University Accident Research Centre Monash University, Melbourne, Australia.,School of Engineering Edith Cowan University, Perth, Australia
| | | | | | - Ray Daniel
- United States Army Aeromedical Research Laboratory, Fort Rucker, USA
| | | | - Jason Mihalik
- University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Nate Dau
- Biocore, LLC, Charlottesville, USA
| | - Jillian Urban
- Wake Forest University School of Medicine, 575 Patterson Ave, Suite 530, Winston-Salem, NC, 27101, USA.
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9
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Circadian patterns of heart rate, respiratory rate and skin temperature in hospitalized COVID-19 patients. PLoS One 2022; 17:e0268065. [PMID: 35797369 PMCID: PMC9262173 DOI: 10.1371/journal.pone.0268065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 04/22/2022] [Indexed: 12/15/2022] Open
Abstract
Rationale
Vital signs follow circadian patterns in both healthy volunteers and critically ill patients, which seem to be influenced by disease severity in the latter. In this study we explored the existence of circadian patterns in heart rate, respiratory rate and skin temperature of hospitalized COVID-19 patients, and aimed to explore differences in circadian rhythm amplitude during patient deterioration.
Methods
We performed a retrospective study of COVID-19 patients admitted to the general ward of a tertiary hospital between April 2020 and March 2021. Patients were continuously monitored using a wireless sensor and fingertip pulse oximeter. Data was divided into three cohorts: patients who recovered, patients who developed respiratory insufficiency and patients who died. For each cohort, a population mean cosinor model was fitted to detect rhythmicity. To assess changes in amplitude, a mixed-effect cosinor model was fitted.
Results
A total of 429 patients were monitored. Rhythmicity was observed in heartrate for the recovery cohort (p<0.001), respiratory insufficiency cohort (p<0.001 and mortality cohort (p = 0.002). Respiratory rate showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.18 and p = 0.51). Skin temperature also showed rhythmicity in the recovery cohort (p<0.001), but not in the other cohorts (p = 0.22 and p = 0.12). For respiratory insufficiency, only the amplitude of heart rate circadian pattern increased slightly the day before (1.2 (99%CI 0.16–2.2, p = 0.002)). In the mortality cohort, the amplitude of heart rate decreased (-1.5 (99%CI -2.6- -0.42, p<0.001)) and respiratory rate amplitude increased (0.72 (99%CI 0.27–1.3, p = 0.002) the days before death.
Conclusion
A circadian rhythm is present in heart rate of COVID-19 patients admitted to the general ward. For respiratory rate and skin temperature, rhythmicity was only found in patients who recover, but not in patients developing respiratory insufficiency or death. We found no consistent changes in circadian rhythm amplitude accompanying patient deterioration.
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van Goor HMR, Vernooij LM, Breteler MJM, Kalkman CJ, Kaasjager KAH, van Loon K. Continuously Measured Vital Signs and their Association with Respiratory Insufficiency in Hospitalised COVID-19 Patients: a Retrospective Cohort study (Preprint). Interact J Med Res 2022; 11:e40289. [DOI: 10.2196/40289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/06/2022] [Accepted: 09/30/2022] [Indexed: 11/07/2022] Open
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11
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L Poisson J, O'Leary MF. Improving our reaction time - Using technology to identify transfusion reactions sooner. Transfusion 2022; 62:923-927. [PMID: 35485170 DOI: 10.1111/trf.16881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 04/06/2022] [Indexed: 11/29/2022]
Affiliation(s)
- Jessica L Poisson
- Department of Pathology, Duke University, Durham, North Carolina, USA
| | - Mandy Flannery O'Leary
- Department of Pathology, Moffitt Medical Group, H. Lee Moffitt Cancer Center, Tampa, Florida, USA.,Department of Oncologic Sciences, University of South Florida, Tampa, Florida, USA
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12
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Areia C, King E, Ede J, Young L, Tarassenko L, Watkinson P, Vollam S. Experiences of current vital signs monitoring practices and views of wearable monitoring: A qualitative study in patients and nurses. J Adv Nurs 2021; 78:810-822. [PMID: 34655093 PMCID: PMC9293408 DOI: 10.1111/jan.15055] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/07/2021] [Accepted: 09/23/2021] [Indexed: 11/26/2022]
Abstract
Aims To understand current experiences of vital signs monitoring of patients and clinical staff on a surgical ward, and views on the introduction of wearable ambulatory monitoring into the general ward environment. Design Qualitative study. Methods Semi‐structured interviews using topic guides were conducted with 15 patients and 15 nurses on a surgical ward between July 2018 and August 2019. The concept of ambulatory wearable devices for clinical monitoring was introduced at the end of the interview. Results Three interconnected themes were identified. Vital sign data as evidence for escalation, examined nurses' use of data to support escalation of care and the implications for patients perceived to be deteriorating who have not reached the threshold for escalation. The second theme, Trustworthiness of vital sign data, described nurses’ practice of using manual measurements to recheck or confirm automated vital signs readings when concerned. The final theme, finding a balance between continuous and intermittent monitoring, both patients and nurses agreed that although continuous monitoring may improve safety and reassurance, these needed to be balanced with multiple limitations. Factors to be considered included noise pollution, comfort, and impact on patient mobility and independence. Introduction of the concept of ambulatory wearable devices was viewed positively by both groups as offering solutions to some of the issues identified with traditional monitoring. However, most agreed that this would not be suitable for all patients and should not replace direct nurse/patient contact. Conclusion Both patients and staff identified the benefits of continuous monitoring to improve patient safety but, due to limitations, use should be carefully considered and patient‐centred. Impact Feedback from nurses and patients suggests there is scope for ambulatory monitoring systems to be integrated into the hospital environment; however, both groups emphasized these should not add more noise to the ward nor replace direct nursing contact.
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Affiliation(s)
- Carlos Areia
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK
| | - Elizabeth King
- Therapies Clinical Service Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jody Ede
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK
| | - Louise Young
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK
| | - Lionel Tarassenko
- National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK.,Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK
| | - Peter Watkinson
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK.,Kadoorie Centre for Critical Care Research and Education, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Sarah Vollam
- Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford, UK
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