Associations of Subjective Sleep Quality with Wearable Device-Derived Resting Heart Rate During REM Sleep and Non-REM Sleep in a Cohort of Japanese Office Workers

Olivia Sjöland,1,2 Thomas Svensson,1– 3 Kaushalya Madhawa,1 Hoang NT,1 Ung-Il Chung,1,3,4 Akiko Kishi Svensson1,2,5 1Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan; 2Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden; 3Graduate School of Health Innovation, Kanagawa University of Human Services, Kawasaki-Ku, Kawasaki-Shi, Kanagawa, Japan; 4Clinical Biotechnology, Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, Tokyo, Japan; 5Department of Diabetes and Metabolic Diseases, The University of Tokyo, Tokyo, JapanCorrespondence: Thomas Svensson, Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan, Tel +81-3-5841-4737, Email [email protected]: Associations between subjective sleep quality and stage-specific heart rate (HR) may have important clinical relevance when aiming to optimize sleep and overall health. The majority of previously studies have been performed during short periods under laboratory-based conditions. The aim of this study was to investigate the associations of subjective sleep quality with heart rate during REM sleep (HR REMS) and non-REM sleep (HR NREMS) using a wearable device (Fitbit Versa).Methods: This is a secondary analysis of data from the intervention group of a randomized controlled trial (RCT) performed between December 3, 2018, and March 2, 2019, in Tokyo, Japan. The intervention group consisted of 179 Japanese office workers with metabolic syndrome (MetS), Pre-MetS or a high risk of developing MetS. HR was collected with a wearable device and sleep quality was assessed with a mobile application where participants answered The St. Mary’s Hospital Sleep Questionnaire. Both HR and sleep quality was collected daily for a period of 90 days. Associations of between-individual and within-individual sleep quality with HR REMS and HR NREMS were analyzed with multi-level model regression in 3 multivariate models.Results: The cohort consisted of 92.6% men (n=151) with a mean age (± standard deviation) of 44.1 (± 7.5) years. A non-significant inverse between-individual association was observed for sleep quality with HR REMS (HR REMS − 0.18; 95% CI − 0.61, 0.24) and HR NREMS (HR NREMS − 0.23; 95% CI − 0.66, 0.21), in the final multivariable adjusted models; a statistically significant inverse within-individual association was observed for sleep quality with HR REMS (HR REMS − 0.21 95% CI − 0.27, − 0.15) and HR NREMS (HR NREMS − 0.21 95% CI − 0.27, − 0.14) after final adjustments for covariates.Conclusion: The present study shows a statistically significant within-individual association of subjective sleep quality with HR REMS and HR NREMS. These findings emphasize the importance of considering sleep quality on the individual level. The results may contribute to early detection and prevention of diseases associated with sleep quality which may have important implications on public health given the high prevalence of sleep disturbances in the population.Keywords: sleep quality, heart rate, sleep stages, REMS, NREMS, wearable devic

Identification of Markers that Distinguish Monocyte-Derived Fibrocytes from Monocytes, Macrophages, and Fibroblasts

The processes that drive fibrotic diseases are complex and include an influx of peripheral blood monocytes that can differentiate into fibroblast-like cells called fibrocytes. Monocytes can also differentiate into other cell types, such as tissue macrophages. The ability to discriminate between monocytes, macrophages, fibrocytes, and fibroblasts in fibrotic lesions could be beneficial in identifying therapies that target either stromal fibroblasts or fibrocytes. and in sections from human lung. We found that markers such as CD34, CD68, and collagen do not effectively discriminate between the four cell types. In addition, IL-4, IL-12, IL-13, IFN-γ, and SAP differentially regulate the expression of CD32, CD163, CD172a, and CD206 on both macrophages and fibrocytes. Finally, CD49c (α3 integrin) expression identifies a subset of fibrocytes, and this subset increases with time in culture.These results suggest that discrimination of monocytes, macrophages, fibrocytes, and fibroblasts in fibrotic lesions is possible, and this may allow for an assessment of fibrocytes in fibrotic diseases

Egenmonitorering : evidenskartläggning genom sammanställning av systematiska översikter för utvalda diagnosgrupper

Background In Region Västra Götaland (VGR), the development of remote patient monitoring is given high priority, aiming for improvements for patients and reduction of healthcare costs. In this report we defined remote patient monitoring as continuous follow-up of relevant health-related parameters of patients located outside healthcare facilities (e.g. at home). Measurements taken by analogue or digital devices, objective and/or subjective assessments, are delivered digitally to the patient and to a healthcare professional. The healthcare professional provides the patient with feedback on the reported data (feedback may be automatically generated if data are within a predefined range). The plan in VGR is to introduce remote monitoring in selected diagnosis groups – some of which already started using remote monitoring. Aim The aim of this report was to provide an overview of systematic reviews regarding remote monitoring(as add on or replacement of visits in current standard of care) compared to standard of care in 25 selected diagnosis groups. Method In order to clarify how remote monitoring is intended to be used in the 25 diagnosis groups, representatives from the respective clinical areas were interviewed. As the scope of this project covered many diagnosis groups, the search was limited to systematic reviews (SRs) of randomised (RCTs) or non-randomised clinical trials. The relevance of each identified SR for our PICO(Population, Intervention, Comparator and Outcomes) was assessed by at least two project members (one clinical representative and one from HTA-centrum). Relevant SRs were assessed by at least two project members using SNABBSTAR, a tool developed by The Swedish Agency for Health Technology Assessment and Assessment of Social Services (SBU) for assessment of risk of bias/systematic errors in SRs. The tool consists of six steps and assessment of an SR is stopped as soon as the criteria for a specific level are not met. The steps are: 1. Definition of PICO and literature search; 2. Inclusion/exclusion according to PICO, listing of included studies; 3. Risk of bias assessments; 4. Evidence synthesis/meta-analyses; 5. Certainty of evidence consideration; 6. Documentation of excluded studies, conflicts of interest, and an a priori published SR protocol. SNABBSTAR evaluates how useful an SR is by assessing the methodology used in the SR. In the current project, SRs reaching at least SNABBSTAR level 4 were considered to provide relevant data synthesis. As reaching SNABBSTAR level 5 or 6 is considered necessary for reliable conclusions, we cited key conclusions only from SRs reaching these levels. We did not extract any data from the included SRs.ResultsThe literature search resulted in 3,332 hits. Of these, 279 were read in full text to assess their relevance for the PICO. Seventy-five SRs were considered relevant and were included; these were assessed by SNABBSTAR.  [More about the abstract in fulltext

Egenmonitorering : evidenskartläggning genom sammanställning av systematiska översikter för utvalda diagnosgrupper

Background In Region Västra Götaland (VGR), the development of remote patient monitoring is given high priority, aiming for improvements for patients and reduction of healthcare costs. In this report we defined remote patient monitoring as continuous follow-up of relevant health-related parameters of patients located outside healthcare facilities (e.g. at home). Measurements taken by analogue or digital devices, objective and/or subjective assessments, are delivered digitally to the patient and to a healthcare professional. The healthcare professional provides the patient with feedback on the reported data (feedback may be automatically generated if data are within a predefined range). The plan in VGR is to introduce remote monitoring in selected diagnosis groups – some of which already started using remote monitoring. Aim The aim of this report was to provide an overview of systematic reviews regarding remote monitoring(as add on or replacement of visits in current standard of care) compared to standard of care in 25 selected diagnosis groups. Method In order to clarify how remote monitoring is intended to be used in the 25 diagnosis groups, representatives from the respective clinical areas were interviewed. As the scope of this project covered many diagnosis groups, the search was limited to systematic reviews (SRs) of randomised (RCTs) or non-randomised clinical trials. The relevance of each identified SR for our PICO(Population, Intervention, Comparator and Outcomes) was assessed by at least two project members (one clinical representative and one from HTA-centrum). Relevant SRs were assessed by at least two project members using SNABBSTAR, a tool developed by The Swedish Agency for Health Technology Assessment and Assessment of Social Services (SBU) for assessment of risk of bias/systematic errors in SRs. The tool consists of six steps and assessment of an SR is stopped as soon as the criteria for a specific level are not met. The steps are: 1. Definition of PICO and literature search; 2. Inclusion/exclusion according to PICO, listing of included studies; 3. Risk of bias assessments; 4. Evidence synthesis/meta-analyses; 5. Certainty of evidence consideration; 6. Documentation of excluded studies, conflicts of interest, and an a priori published SR protocol. SNABBSTAR evaluates how useful an SR is by assessing the methodology used in the SR. In the current project, SRs reaching at least SNABBSTAR level 4 were considered to provide relevant data synthesis. As reaching SNABBSTAR level 5 or 6 is considered necessary for reliable conclusions, we cited key conclusions only from SRs reaching these levels. We did not extract any data from the included SRs.ResultsThe literature search resulted in 3,332 hits. Of these, 279 were read in full text to assess their relevance for the PICO. Seventy-five SRs were considered relevant and were included; these were assessed by SNABBSTAR.  [More about the abstract in fulltext