Validation and Acceptability of a Cuffless Wrist-Worn Wearable Blood Pressure Monitoring Device Among Users and Health Care Professionals: Mixed Methods Study

Feasibility and Effectiveness of a Ring-Type Blood Pressure Measurement Device Compared With 24-Hour Ambulatory Blood Pressure Monitoring Device

BACKGROUNDS AND OBJECTIVES

This study aimed to evaluate the applicability and precision of a ring-type cuffless blood pressure (BP) measurement device, CART-I Plus, compared to conventional 24-hour ambulatory BP monitoring (ABPM).

METHODS

Forty patients were recruited, and 33 participants were included in the final analysis. Each participant wore both CART-I Plus and ABPM devices on the same arm for approximately 24 hours. BP estimation from CART-I Plus, derived from photoplethysmography (PPG) signals, were compared with the corresponding ABPM measurements.

RESULTS

The CART-I Plus recorded systolic blood pressure (SBP)/diastolic blood pressure (DBP) values of 131.4±14.1/81.1±12.0, 132.7±13.9/81.9±11.9, and 128.7±14.6/79.3±12.2 mmHg for 24-hour, daytime, and nighttime periods respectively, compared to ABPM values of 129.7±11.7/84.4±11.2, 131.9±11.6/86.3±11.1, and 124.5±13.6/80.0±12.2 mmHg. Mean differences in SBP/DBP between the two devices were 1.74±6.69/-3.24±6.51 mmHg, 0.75±7.44/-4.41±7.42 mmHg, and 4.15±6.15/-0.67±5.23 mmHg for 24-hour, daytime, and nighttime periods respectively. Strong correlations were also observed between the devices, with r=0.725 and r=0.750 for transitions in SBP and DBP from daytime to nighttime, respectively (both p<0.001).

CONCLUSIONS

The CART-I Plus device, with its unique ring-type design, shows promising accuracy in BP estimation and offers a potential avenue for continuous BP monitoring in clinical practice.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT06084065.

Wearable Devices: Implications for Precision Medicine and the Future of Health Care

Wearable devices are integrated analytical units equipped with sensitive physical, chemical, and biological sensors capable of noninvasive and continuous monitoring of vital physiological parameters. Recent advances in disciplines including electronics, computation, and material science have resulted in affordable and highly sensitive wearable devices that are routinely used for tracking and managing health and well-being. Combined with longitudinal monitoring of physiological parameters, wearables are poised to transform the early detection, diagnosis, and treatment/management of a range of clinical conditions. Smartwatches are the most commonly used wearable devices and have already demonstrated valuable biomedical potential in detecting clinical conditions such as arrhythmias, Lyme disease, inflammation, and, more recently, COVID-19 infection. Despite significant clinical promise shown in research settings, there remain major hurdles in translating the medical uses of wearables to the clinic. There is a clear need for more effective collaboration among stakeholders, including users, data scientists, clinicians, payers, and governments, to improve device security, user privacy, data standardization, regulatory approval, and clinical validity. This review examines the potential of wearables to offer affordable and reliable measures of physiological status that are on par with FDA-approved specialized medical devices. We briefly examine studies where wearables proved critical for the early detection of acute and chronic clinical conditions with a particular focus on cardiovascular disease, viral infections, and mental health. Finally, we discuss current obstacles to the clinical implementation of wearables and provide perspectives on their potential to deliver increasingly personalized proactive health care across a wide variety of conditions.

European Society of Hypertension recommendations for the validation of cuffless blood pressure measuring devices: European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability

BACKGROUND

There is intense effort to develop cuffless blood pressure (BP) measuring devices, and several are already on the market claiming that they provide accurate measurements. These devices are heterogeneous in measurement principle, intended use, functions, and calibration, and have special accuracy issues requiring different validation than classic cuff BP monitors. To date, there are no generally accepted protocols for their validation to ensure adequate accuracy for clinical use.

OBJECTIVE

This statement by the European Society of Hypertension (ESH) Working Group on BP Monitoring and Cardiovascular Variability recommends procedures for validating intermittent cuffless BP devices (providing measurements every >30 sec and usually 30-60 min, or upon user initiation), which are most common.

VALIDATION PROCEDURES

Six validation tests are defined for evaluating different aspects of intermittent cuffless devices: static test (absolute BP accuracy); device position test (hydrostatic pressure effect robustness); treatment test (BP decrease accuracy); awake/asleep test (BP change accuracy); exercise test (BP increase accuracy); and recalibration test (cuff calibration stability over time). Not all these tests are required for a given device. The necessary tests depend on whether the device requires individual user calibration, measures automatically or manually, and takes measurements in more than one position.

CONCLUSION

The validation of cuffless BP devices is complex and needs to be tailored according to their functions and calibration. These ESH recommendations present specific, clinically meaningful, and pragmatic validation procedures for different types of intermittent cuffless devices to ensure that only accurate devices will be used in the evaluation and management of hypertension.

Burden of Hypertensive Heart Disease and High Systolic Blood Pressure in Australia from 1990 to 2019: Results From the Global Burden of Diseases Study

BACKGROUND

There is a dearth of comprehensive studies examining the burden and trends of hypertensive heart disease (HHD) and high systolic blood pressure (SBP) among the Australian population. We aimed to explore the burden of HHD and high SBP, and how they changed over time from 1990 to 2019 in Australia.

METHODS

We analysed data from the Global Burden of Disease study in Australia. We assessed the prevalence, mortality, disability-adjusted life-years (DALY), years lived with disability (YLD) and years of life lost (YLL) attributable to HHD and high SBP. Data were presented as point estimates with 95% uncertainty intervals (UI). We compared the burden of HHD and high SBP in Australia with World Bank defined high-income countries and six other comparator countries with similar sociodemographic characteristics and economies.

RESULTS

From 1990 to 2019, the burden of HHD and high SBP in Australia reduced. Age standardised prevalence rate of HHD was 119.3 cases per 100,000 people (95% UI 86.6-161.0) in 1990, compared to 80.1 cases (95% UI 57.4-108.1) in 2019. Deaths due to HDD were 3.4 cases per 100,000 population (95% UI 2.6-3.8) in 1990, compared to 2.5 (95% UI 1.9-3.0) in 2019. HHD contributed to 57.2 (95% UI 46.6-64.7) DALYs per 100,000 population in 1990 compared to 38.4 (95% UI 32.0-45.2) in 2019. Death rates per 100,000 population attributable to high SBP declined significantly over time for both sexes from 1990 (155.6 cases; 95% UI 131.2-177.0) to approximately one third in 2019 (53.8 cases; 95% UI 43.4-64.4). Compared to six other countries in 2019, the prevalence of HHD was highest in the USA (274.3%) and lowest in the UK (52.6%), with Australia displaying the third highest prevalence. Australia ranked second in term of lowest rates of deaths and third for lowest DALYs respectively due to high SBP. From 1990-2019, Australia ranked third best for reductions in deaths and DALYs due to HHD and first for reductions in deaths and DALYs due to high SBP.

CONCLUSION

Over the past three decades, the burden of HHD in Australia has reduced, but its prevalence remains relatively high. The contribution of high SBP to deaths, DALYs and YLLs also reduced over the three decades.

The burden of type 2 diabetes in Australia during the period 1990-2019: Findings from the global burden of disease study

AIMS

To describe morbidity and mortality trends of type 2 diabetes in Australia, from 1990 to 2019, compared with similar sociodemographic index (SDI) countries.

METHODS

Australia-specific Global Burden of Diseases data were used to estimate age-standardised, age-specific, and sex-specific rates for prevalence, years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life years (DALYs), and deaths due to type 2 diabetes between 1990 and 2019. Australian data were compared with 14 similar SDI countries.

RESULTS

Type 2 diabetes increased in Australia between 1990 and 2019. The age-standardised prevalence increased from 1,985 [95% Confidence Interval (CI): 1,786.7-2195.3] per 100,000 population, to 3,429 [95% CI 3,053.3-3,853.7]. Cases tripled, from 379,532 [342,465-419,475] to 1,307,261 [1,165,522-1,461,180]. The age-standardised death rates doubled, from 2,098 [1,953-2,203] per 100,000, to 4,122 [3,617-4,512]. DALYs doubled, from 70,348 [59,187-83,500] to 169,763 [129,792-216,150], with increases seen in YLDs and YLLs. Men displayed higher rates. Compared to similar SDI countries, Australia ranked 4th in terms of burden for type 2 diabetes.

CONCLUSIONS

The burden of type 2 diabetes in Australia has increased considerably over three decades. There is an urgent need to prioritise resource allocation for prevention programs, screening initiatives to facilitate early detection, and effective and accessible management strategies for the large proportion of the population impacted by type 2 diabetes.

Design and development of a smartphone app for hypertension management: An intervention mapping approach

Background

Several research studies have demonstrated the potential of mobile health apps in supporting health management. However, the design and development process of these apps are rarely presented.

Objective

We present the design and development of a smartphone-based lifestyle app integrating a wearable device for hypertension management.

Methods

We used an intervention mapping approach for the development of theory- and evidence-based intervention in hypertension management. This consisted of six fundamental steps: needs assessment, matrices, theoretical methods and practical strategies, program design, adoption and implementation plan, and evaluation plan. To design the contents of the intervention, we performed a literature review to determine the preferences of people with hypertension (Step 1) and necessary objectives toward the promotion of self-management behaviors (Step 2). Based on these findings, we implemented theoretical and practical strategies in consultation with stakeholders and researchers (Steps 3), which was used to identify the functionality and develop an mHealth app (Step 4). The adoption (Step 5) and evaluation (Step 6) of the mHealth app will be conducted in a future study.

Results

Through the needs analysis, we identified that people with hypertension preferred having education, medication or treatment adherence, lifestyle modification, alcohol and smoking cessation and blood pressure monitoring support. We utilized MoSCoW analysis to consider four key elements, i.e., education, medication or treatment adherence, lifestyle modification and blood pressure support based on past experiences, and its potential benefits in hypertension management. Theoretical models such as (i) the information, motivation, and behavior skills model, and (ii) the patient health engagement model was implemented in the intervention development to ensure positive engagement and health behavior. Our app provides health education to people with hypertension related to their condition, while utilizing wearable devices to promote lifestyle modification and blood pressure management. The app also contains a clinician portal with rules and medication lists titrated by the clinician to ensure treatment adherence, with regular push notifications to prompt behavioral change. In addition, the app data can be reviewed by patients and clinicians as needed.

Conclusions

This is the first study describing the design and development of an app that integrates a wearable blood pressure device and provides lifestyle support and hypertension management. Our theory-driven intervention for hypertension management is founded on the critical needs of people with hypertension to ensure treatment adherence and supports medication review and titration by clinicians. The intervention will be clinically evaluated in future studies to determine its effectiveness and usability.

Trends of the burden of hypertension in Saudi Arabia between 1990 and 2019: an analysis from the Global Burden of Diseases study.. [DOI: 10.21203/rs.3.rs-2609599/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background: Hypertension is a widely prevalent condition associated with significant morbidity and premature mortality, primarily because it is a risk factor for CVDs. The aim of this study was to estimate the trend of the burden of hypertension in Saudi Arabia in the last three decades. Methods: We conducted a systematic analysis of secondary data obtained from the Global Burden of Disease Study (GBD). We estimated sex-stratified, age-standardised and age-specific rates (per 100,000) of prevalence, deaths, and disability-adjusted years (DALYs) associated with hypertension in adults aged 20-94 years in Saudi Arabia between 1990 and 2019. Results: In Saudi Arabia, the age-standardised prevalence of hypertension increased from 87.7 cases per 100,000 in 1990 to 94.9 per 100,000 in 2019. More women than men had hypertension throughout the past three decades. The death and DALYs rate, however, decreased during this time. In 1990, 9.2 deaths per 100,000 in women and 3.0 deaths per 100,000 in men were due to hypertension; the respective rates declined to 6.5 and 2.8 in 2019. While the rates of DALYs in women declined steadily from 211.7 to 151.8 per 100,000 DALYs between 1990 and 2019, the rate in males did not decline considerably. The burden of hypertension–prevalence, deaths, and DALYs–were greater in older people. Conclusion: The prevalence of hypertension has increased in Saudi Arabia during the last 30 years; however, death rates and DALY related to hypertension has decreased during this time. Age- and sex-specific strategies are needed to decrease the prevalence of hypertension in Saudi Arabia.

Tests for the identification of reflex syncope mechanism

INTRODUCTION

Treatment efficacy of reflex syncope is mainly related to the mechanism underlying syncope rather than its etiology or clinical presentation. The predominant mechanism underlying reflex syncope can be assigned to hypotensive or to bradycardic phenotypes.

AREAS COVERED

Methodology and diagnostic criteria of the most useful tests for the identification of hypotensive and bradycardic phenotypes are discussed. Diagnostic tests for the hypotensive phenotype include office blood pressure measurement with active standing test, home, and wearable blood pressure monitoring, 24-h ambulatory blood pressure monitoring and tilt table test. Diagnostic tests for the bradycardic phenotype include carotid sinus massage, tilt table test and prolonged ECG monitoring.

EXPERT OPINION

In reflex syncope, the documentation of bradycardia/asystole during a syncopal episode does not rule out the possibility that a preceding or parallel hypotensive reflex plays an important role. Similarly, even when a hypotensive mechanism is established, the possibility of an associated cardioinhibitory reflex should be investigated. Investigating the mechanism of reflex syncope is mandatory in patients with severe recurrent episodes, with the final aim to develop a personalized treatment strategy. Recent trials have demonstrated the benefits of personalized mechanism-based therapy, thus highlighting the importance of a comprehensive assessment of the mechanisms underlying syncope.

Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges

Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges.

Consensus on Recommended Functions of a Smart Home System to Improve Self-Management Behaviors in People With Heart Failure: A Modified Delphi Approach

Background

Smart home systems could enhance clinical and self-management of chronic heart failure by supporting health monitoring and remote support, but evidence to guide the design of smart home system functionalities is lacking.

Objective

To identify consensus-based recommendations for functions of a smart home system that could augment clinical and self-management for people living with chronic heart failure in the community.

Methods

Healthcare professionals caring for people living with chronic heart failure participated in a two-round modified Delphi survey and a consensus workshop. Thirty survey items spanning eight chronic health failure categories were derived from international guidelines for the management of heart failure. In survey Round 1, participants rated the importance of all items using a 9-point Liket scale and suggested new functions to support people with chronic heart failure in their homes using a smart home system. The Likert scale scores ranged from 0 (not important) to 9 (very important) and scores were categorized into three groups: 1–3 = not important, 4–6 = important, and 7–9 = very important. Consensus agreement was defined a priori as ≥70% of respondents rating a score of ≥7 and ≤ 15% rating a score ≤ 3. In survey Round 2, panel members re-rated items where consensus was not reached, and rated the new items proposed in earlier round. Panel members were invited to an online consensus workshop to discuss items that had not reached consensus after Round 2 and agree on a set of recommendations for a smart home system.

Results

In Round 1, 15 experts agreed 24/30 items were “very important”, and suggested six new items. In Round 2, experts agreed 2/6 original items and 6/6 new items were “very important”. During the consensus workshop, experts endorsed 2/4 remaining items. Finally, the expert panel recommended 34 items as “very important” for a smart home system including, healthy eating, body weight and fluid intake, physical activity and sedentary behavior, heart failure symptoms, tobacco cessation and alcohol reduction, medication adherence, physiological monitoring, interaction with healthcare professionals, and mental health among others.

Conclusion

A panel of healthcare professional experts recommended 34-item core functions in smart home systems designed to support people with chronic heart failure for self-management and clinical support. Results of this study will help researchers to co-design and protyping solutions with consumers and healthcare providers to achieve these core functions to improve self-management and clinical outcomes in people with chronic heart failure.

Chinese adult segmentation according to health skills and analysis of their use for smart home: a cross-sectional national survey

Background

Digital health has become a heated topic today and smart homes have received much attention as an important area of digital health. Smart home is a device that enables automation and remote control in a home environment via the internet. However, most of the existing studies have focused on discussing the impact of smart home on people. Only few studies have focused on relationship between health skills and use of smart home.

Aims

To analyze the health skills of Chinese adults and segment them to compare and analyze the use of smart home for each group.

Methods

We used data from 11,031 participants aged 18 and above. The population was clustered based on five health skills factors: perceived social support, family health, health literacy, media use, and chronic diseases self-behavioral management. A total of 23 smart homes were categorized into three sub-categories based on their functions: entertainment smart home, functional smart home, and health smart home. We analyzed demographic characteristics and utilization rate of smart home across different cluster. Each groups’ features and the differences in their needs for smart home functions were compared and analyzed.

Results

As a result of the survey on health skills, three groups with different characteristics were clustered: good health skills, middle health skills, and poor health skills. The utilization rate of smart home was the highest was good health skills group (total smart home: 92.7%; entertainment smart home: 61.1%, functional smart home: 77.4%, and health smart home: 75.3%; P < 0.001). For entertainment smart home, smart TV had the highest utilization rate (good health skills: 45.7%; middle health skills: 43.5%, poor health skills: 33.4%, P < 0.001). For functional smart home, smart washing machine (good health skills: 37.7%, middle health skills: 35.11%, poor health skills: 26.5%; P < 0.001) and smart air conditioner (good health skills: 36.0%, middle health skills: 29.1%, poor health skills: 24.6%) were higher than other of this category. For health smart home, sports bracelet has the highest utilization rate (good health skills: 37.3%, middle health skills: 24.5%, poor health skills: 22.8%).

Conclusion

People can be divided into different categories based on health skill profiles, those with good health skills had a better utilization rate of smart home. The government and smart home companies need to focus on people with poor smart home use in various ways to promote their use of smart homes for personal health management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08126-8.

Wearable cuffless blood pressure monitoring devices: a systematic review and meta-analysis

Aims

High blood pressure (BP) is the commonest modifiable cardiovascular risk factor, yet its monitoring remains problematic. Wearable cuffless BP devices offer potential solutions; however, little is known about their validity and utility. We aimed to systematically review the validity, features and clinical use of wearable cuffless BP devices.

Methods and results

We searched MEDLINE, Embase, IEEE Xplore and the Cochrane Database till December 2019 for studies that reported validating cuffless BP devices. We extracted information about study characteristics, device features, validation processes, and clinical applications. Devices were classified according to their functions and features. We defined devices with a mean systolic BP (SBP) and diastolic BP (DBP) biases of <5 mmHg as valid as a consensus. Our definition of validity did not include assessment of device measurement precision, which is assessed by standard deviation of the mean difference-a critical component of ISO protocol validation criteria. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 tool. A random-effects model meta-analysis was performed to summarise the mean biases for SBP and DBP across studies. Of the 430 studies identified, 16 studies (15 devices, 974 participants) were selected. The majority of devices (81.3%) used photoplethysmography to estimate BP against a reference device; other technologies included tonometry, auscultation and electrocardiogram. In addition to BP and heart rate, some devices also measured night-time BP (n = 5), sleep monitoring (n = 3), oxygen saturation (n = 3), temperature (n = 2) and electrocardiogram (n = 3). Eight devices showed mean biases of <5 mmHg for SBP and DBP compared with a reference device and three devices were commercially available. The meta-analysis showed no statistically significant differences between the wearable and reference devices for SBP (pooled mean difference = 3.42 mmHg, 95% CI: -2.17, 9.01, I² 95.4%) and DBP (pooled mean = 1.16 mmHg, 95% CI: -1.26, 3.58, I² 87.1%).

Conclusion

Several cuffless BP devices are currently available using different technologies, offering the potential for continuous BP monitoring. The variation in standards and validation protocols limited the comparability of findings across studies and the identification of the most accurate device. Challenges such as validation using standard protocols and in real-life settings must be overcome before they can be recommended for uptake into clinical practice.

Prediction of cardiac autonomic neuropathy using a machine learning model in patients with diabetes

BACKGROUND

Cardiac autonomic neuropathy (CAN) is a diabetes-related complication with increasing prevalence and remains challenging to detect in clinical settings. Machine learning (ML) approaches have the potential to predict CAN using clinical data. In this study, we aimed to develop and evaluate the performance of an ML model to predict early CAN occurrence in patients with diabetes.

METHODS

We used the diabetes complications screening research initiative data set containing 200 CAN-related tests on more than 2000 participants with type 2 diabetes in Australia. Data were collected on peripheral nerve functions, Ewing's tests, blood biochemistry, demographics, and medical history. The ML model was validated using 10-fold cross-validation, of which 90% were used in training the model and the remaining 10% was used in evaluating the performance of the model. Predictive accuracy was assessed by area under the receiver operating curve, and sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

Of the 237 patients included, 105 were diagnosed with an early stage of CAN while the remaining 132 were healthy. The ML model showed outstanding performance for CAN prediction with receiver operating characteristic curve of 0.962 [95% confidence interval (CI) = 0.939-0.984], 87.34% accuracy, and 87.12% sensitivity. There was a significant and positive association between the ML model and CAN occurrence (p < 0.001).

CONCLUSION

Our ML model has the potential to detect CAN at an early stage using Ewing's tests. This model might be useful for healthcare providers for predicting the occurrence of CAN in patients with diabetes, monitoring the progression, and providing timely intervention.

Smart wearable devices in cardiovascular care: where we are and how to move forward

Technological innovations reach deeply into our daily lives and an emerging trend supports the use of commercial smart wearable devices to manage health. In the era of remote, decentralized and increasingly personalized patient care, catalysed by the COVID-19 pandemic, the cardiovascular community must familiarize itself with the wearable technologies on the market and their wide range of clinical applications. In this Review, we highlight the basic engineering principles of common wearable sensors and where they can be error-prone. We also examine the role of these devices in the remote screening and diagnosis of common cardiovascular diseases, such as arrhythmias, and in the management of patients with established cardiovascular conditions, for example, heart failure. To date, challenges such as device accuracy, clinical validity, a lack of standardized regulatory policies and concerns for patient privacy are still hindering the widespread adoption of smart wearable technologies in clinical practice. We present several recommendations to navigate these challenges and propose a simple and practical 'ABCD' guide for clinicians, personalized to their specific practice needs, to accelerate the integration of these devices into the clinical workflow for optimal patient care.

Visualising the knowledge structure and evolution of wearable device research

In recent years, the literature associated with wearable devices has grown rapidly, but few studies have used bibliometrics and a visualisation approach to conduct deep mining and reveal a panorama of the wearable devices field. To explore the foundational knowledge and research hotspots of the wearable devices field, this study conducted a series of bibliometric analyses on the related literature, including papers' production trends in the field and the distribution of countries, a keyword co-occurrence analysis, theme evolution analysis and research hotspots and trends for the future. By conducting a literature content analysis and structure analysis, we found the following: (a) The subject evolution path includes sensor research, sensitivity research and multi-functional device research. (b) Wearable device research focuses on information collection, sensor materials, manufacturing technology and application, artificial intelligence technology application, energy supply and medical applications. The future development trend will be further studied in combination with big data analysis, telemedicine and personalised precision medical application.

Cardiovascular diseases risk prediction in patients with diabetes: Posthoc analysis from a matched case-control study in Bangladesh

Purpose

This study aimed to investigate the estimated 10-year predicted risk of developing cardiovascular diseases (CVD) among participants with and without diabetes in Bangladesh.

Methods

We performed posthoc analysis from a matched case-control study conducted among 1262 participants. A total of 631 participants with diabetes (case) were recruited from a tertiary hospital, and 631 age, sex and residence matched participants (control) were recruited from the community in Dhaka, Bangladesh. Socioeconomic anthropometric, clinical and CVD risk factor data were collected from the participants. The 10-year estimated CVD risk was calculated using the Framingham Risk Score, which has reasonable validity in South Asians.

Results

The mean (SD) age of the participants were 51 (10) years. Total 52.3% of cases and 17.2% of controls were at high risk for CVD. The 10-year risk of CVD increased by age and was higher among males in both groups. Among the control group, high CVD risk was more prevalent among higher education and income groups. More than 85% of the tobacco smokers and 70% of chewing tobacco users in the case group were at high risk of CVD. Prevalence of high CVD risk among non-smokers cases was 8.6%. About 35% of hypertensive participants in the control group were at high risk of CVD.

Conclusion

Bangladeshi patients with diabetes showed a significant burden of CVD risk at a relatively younger age. Strategies for reducing tobacco use and improving BP control in people with diabetes is needed for lowering future CVD risks.

Wearable Health Devices in Health Care: Narrative Systematic Review

BACKGROUND

With the rise of mobile medicine, the development of new technologies such as smart sensing, and the popularization of personalized health concepts, the field of smart wearable devices has developed rapidly in recent years. Among them, medical wearable devices have become one of the most promising fields. These intelligent devices not only assist people in pursuing a healthier lifestyle but also provide a constant stream of health care data for disease diagnosis and treatment by actively recording physiological parameters and tracking metabolic status. Therefore, wearable medical devices have the potential to become a mainstay of the future mobile medical market.

OBJECTIVE

Although previous reviews have discussed consumer trends in wearable electronics and the application of wearable technology in recreational and sporting activities, data on broad clinical usefulness are lacking. We aimed to review the current application of wearable devices in health care while highlighting shortcomings for further research. In addition to daily health and safety monitoring, the focus of our work was mainly on the use of wearable devices in clinical practice.

METHODS

We conducted a narrative review of the use of wearable devices in health care settings by searching papers in PubMed, EMBASE, Scopus, and the Cochrane Library published since October 2015. Potentially relevant papers were then compared to determine their relevance and reviewed independently for inclusion.

RESULTS

A total of 82 relevant papers drawn from 960 papers on the subject of wearable devices in health care settings were qualitatively analyzed, and the information was synthesized. Our review shows that the wearable medical devices developed so far have been designed for use on all parts of the human body, including the head, limbs, and torso. These devices can be classified into 4 application areas: (1) health and safety monitoring, (2) chronic disease management, (3) disease diagnosis and treatment, and (4) rehabilitation. However, the wearable medical device industry currently faces several important limitations that prevent further use of wearable technology in medical practice, such as difficulties in achieving user-friendly solutions, security and privacy concerns, the lack of industry standards, and various technical bottlenecks.

CONCLUSIONS

We predict that with the development of science and technology and the popularization of personalized health concepts, wearable devices will play a greater role in the field of health care and become better integrated into people's daily lives. However, more research is needed to explore further applications of wearable devices in the medical field. We hope that this review can provide a useful reference for the development of wearable medical devices.

Validation of a wearable cuff-less wristwatch-type blood pressure monitoring device

Ambulatory blood pressure (BP) monitoring is recommended to improve the management of hypertension. Here, we investigated the accuracy of BP estimated using a wearable cuff-less device, InBodyWATCH, compared with BP measured using a manual sphygmomanometer. Thirty-five adults were enrolled (age 57.1 ± 17.9 years). The BP was estimated using InBodyWATCH with an individualized estimation based on a neural network model. Three paired sets of BPs from the two devices were compared using correlation analysis and Bland–Altman plots (n = 105 paired BP readings). The correlations for both systolic and diastolic BP (SBP and DBP) between the two devices were high (r = 0.964 and 0.939, both P < 0.001). The mean difference was 2.2 ± 6.1 mmHg for SBP and −0.2 ± 4.2 mmHg for DBP; these were not significant (P = 0.472 for SBP and P = 0.880 for DBP). The proportions of estimated SBP/DBP obtained from the InBodyWATCH within ± 5 mmHg of manual SBP/DBP were 71.4%/83.8%; within ± 10 mmHg they were 86.7%/98.1%; and within ± 15 mmHg they were 97.1%/99.0%. The estimated BP from this wearable cuff-less device correlated highly with the manual BP and showed good accuracy, suggesting its potential to be used in ambulatory BP monitoring.

Armstrong D. The Potential Role of Sensors, Wearables and Telehealth in the Remote Management of Diabetes-Related Foot Disease

Diabetes-related foot disease (DFD), which includes foot ulcers, infection and gangrene, is a leading cause of the global disability burden. About half of people who develop DFD experience a recurrence within one year. Long-term medical management to reduce the risk of recurrence is therefore important to reduce the global DFD burden. This review describes research assessing the value of sensors, wearables and telehealth in preventing DFD. Sensors and wearables have been developed to monitor foot temperature, plantar pressures, glucose, blood pressure and lipids. The monitoring of these risk factors along with telehealth consultations has promise as a method for remotely managing people who are at risk of DFD. This approach can potentially avoid or reduce the need for face-to-face consultations. Home foot temperature monitoring, continuous glucose monitoring and telehealth consultations are the approaches for which the most highly developed and user-friendly technology has been developed. A number of clinical studies in people at risk of DFD have demonstrated benefits when using one of these remote monitoring methods. Further development and evidence are needed for some of the other approaches, such as home plantar pressure and footwear adherence monitoring. As yet, no composite remote management program incorporating remote monitoring and the management of all the key risk factors for DFD has been developed and implemented. Further research assessing the feasibility and value of combining these remote monitoring approaches as a holistic way of preventing DFD is needed.

Management of Hypertension in the Digital Era: Small Wearable Monitoring Devices for Remote Blood Pressure Monitoring

Out-of-office blood pressure measurement is an essential part of diagnosing and managing hypertension. In the era of advanced digital health information technology, the approach to achieving this is shifting from traditional methods (ambulatory and home blood pressure monitoring) to wearable devices and technology. Wearable blood pressure monitors allow frequent blood pressure measurements (ideally continuous beat-by-beat monitoring of blood pressure) with minimal stress on the patient. It is expected that wearable devices will dramatically change the quality of detection and management of hypertension by increasing the number of measurements in different situations, allowing accurate detection of phenotypes that have a negative impact on cardiovascular prognosis, such as masked hypertension and abnormal blood pressure variability. Frequent blood pressure measurements and the addition of new features such as monitoring of environmental conditions allows interpretation of blood pressure data in the context of daily stressors and different situations. This new digital approach to hypertension contributes to anticipation medicine, which refers to strategies designed to identify increasing risk and predict the onset of cardiovascular events based on a series of data collected over time, allowing proactive interventions to reduce risk. To achieve this, further research and validation is required to develop wearable blood pressure monitoring devices that provide the same accuracy as current approaches and can effectively contribute to personalized medicine.

Usability of Wearable Devices With a Novel Cardiac Force Index for Estimating the Dynamic Cardiac Function: Observational Study

Background

Long-distance running can be a form of stress to the heart. Technological improvements combined with the public’s gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied.

Objective

We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running.

Methods

This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs.

Results

The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = –2.702 – 0.096 × [waist circumference] – 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner’s CFR varies with changes in activity. Since the runner’s acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner’s explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter.

Conclusions

In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.