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      Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

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          Abstract

          Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in turn, may make 4P medicine (predictive, precise, preventive and personalized) a more attainable goal within dialysis patient care. This article discusses different use cases where WHD could be of relevance for dialysis patient care, i.e. measurement of heart rate, arrhythmia detection, blood pressure, hyperkalaemia, fluid overload and physical activity. After adequate validation of the different WHD in this specific population, data obtained from WHD could form part of a body area network (BAN), which could serve different purposes such as feedback on actionable parameters like physical inactivity, fluid overload, danger signalling or event prediction. For a BAN to become clinical reality, not only must technical issues, cybersecurity and data privacy be addressed, but also adequate models based on artificial intelligence and mathematical analysis need to be developed for signal optimization, data representation, data reliability labelling and interpretation. Moreover, the potential of WHD and BAN can only be fulfilled if they are part of a transformative healthcare system with a shared responsibility between patients, healthcare providers and the payors, using a step-up approach that may include digital assistants and dedicated ‘digital clinics’. The coming decade will be critical in observing how these developments will impact and transform dialysis patient care and will undoubtedly ask for an increased ‘digital literacy’ for all those implicated in their care.

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          Chronic kidney disease and premature ageing.

          Chronic kidney disease (CKD) shares many phenotypic similarities with other chronic diseases, including heart failure, chronic obstructive pulmonary disease, HIV infection and rheumatoid arthritis. The most apparent similarity is premature ageing, involving accelerated vascular disease and muscle wasting. We propose that in addition to a sedentary lifestyle and psychosocial and socioeconomic determinants, four major disease-induced mechanisms underlie premature ageing in CKD: an increase in allostatic load, activation of the 'stress resistance response', activation of age-promoting mechanisms and impairment of anti-ageing pathways. The most effective current interventions to modulate premature ageing-treatment of the underlying disease, optimal nutrition, correction of the internal environment and exercise training-reduce systemic inflammation and oxidative stress and induce muscle anabolism. Deeper mechanistic insight into the phenomena of premature ageing as well as early diagnosis of CKD might improve the application and efficacy of these interventions and provide novel leads to combat muscle wasting and vascular impairment in chronic diseases.
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            Wearable Health Devices—Vital Sign Monitoring, Systems and Technologies

            Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.
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              A validation study of Fitbit Charge 2™ compared with polysomnography in adults

              We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2™), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition in healthy adults. In-lab PSG and Fitbit Charge 2™ data were obtained from a single overnight recording at the SRI Human Sleep Research Laboratory in 44 adults (19-61 years; 26 women; 25 Caucasian). Participants were screened to be free from mental and medical conditions. Presence of sleep disorders was evaluated with clinical PSG. PSG findings indicated periodic limb movement of sleep (PLMS, > 15/h) in nine participants, who were analyzed separately from the main group (n = 35). PSG and Fitbit Charge 2™ sleep data were compared using paired t-tests, Bland-Altman plots, and epoch-by-epoch (EBE) analysis. In the main group, Fitbit Charge 2™ showed 0.96 sensitivity (accuracy to detect sleep), 0.61 specificity (accuracy to detect wake), 0.81 accuracy in detecting N1+N2 sleep ("light sleep"), 0.49 accuracy in detecting N3 sleep ("deep sleep"), and 0.74 accuracy in detecting rapid-eye-movement (REM) sleep. Fitbit Charge 2™ significantly (p < 0.05) overestimated PSG TST by 9 min, N1+N2 sleep by 34 min, and underestimated PSG SOL by 4 min and N3 sleep by 24 min. PSG and Fitbit Charge 2™ outcomes did not differ for WASO and time spent in REM sleep. No more than two participants fell outside the Bland-Altman agreement limits for all sleep measures. Fitbit Charge 2™ correctly identified 82% of PSG-defined non-REM-REM sleep cycles across the night. Similar outcomes were found for the PLMS group. Fitbit Charge 2™ shows promise in detecting sleep-wake states and sleep stage composition relative to gold standard PSG, particularly in the estimation of REM sleep, but with limitations in N3 detection. Fitbit Charge 2™ accuracy and reliability need to be further investigated in different settings (at-home, multiple nights) and in different populations in which sleep composition is known to vary (adolescents, elderly, patients with sleep disorders).
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                Author and article information

                Journal
                Nephrol Dial Transplant
                Nephrol. Dial. Transplant
                ndt
                Nephrology Dialysis Transplantation
                Oxford University Press
                0931-0509
                1460-2385
                March 2020
                12 March 2020
                12 March 2020
                : 35
                : Suppl 2 , Advancements in chronic kidney disease and dialysis care: a joint call for personalized therapy
                : ii43-ii50
                Affiliations
                [g1 ] Department of Internal Medicine, Division of Nephrology, University Hospital Maastricht , Maastricht, The Netherlands
                [g2 ] Connected Health Solutions , imec, Eindhoven, The Netherlands
                [g3 ] Faculty of Health, Medicine and Life Sciences, Maastricht University , Maastricht, The Netherlands
                [g4 ] Renal Research Institute , New York, NY, USA
                [g5 ] Global Medical Office, Fresenius Medical Care , Waltham, MA, USA
                Author notes
                Correspondence to: Jeroen P. Kooman; E-mail: Jeroen.kooman@ 123456mumc.nl
                Article
                gfaa015
                10.1093/ndt/gfaa015
                7066542
                32162666
                6db9e372-383e-4bdf-b57c-3b49b1373ee6
                © The Author(s) 2020. Published by Oxford University Press on behalf of ERA-EDTA.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 20 December 2019
                Page count
                Pages: 8
                Categories
                Reviews

                Nephrology
                blood pressure,dialysis,fluid overload,haemodialysis,physical activity
                Nephrology
                blood pressure, dialysis, fluid overload, haemodialysis, physical activity

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