Mobile Health Technologies in Cardiopulmonary Disease

Mobile health management among end stage renal disease patients: a scoping review

Aims

The health management of end-stage renal disease patients is a complicated process, and mobile health management technology provides a new choice for the health management of end-stage renal disease patients. The scope of clinical studies on mobile health management for patients with end-stage renal disease was reviewed, and found that about mobile health management problems existing in the literature were identified to provide ideas for subsequent mobile health management research.

Methods

The databases Web of Science, PubMed, The Cochrane Library, Embase, CNKI, Wan Fang Data, BMJ, and VIP were systematically searched for studies on Mobile health management among end-stage renal disease in adult and adolescent patients or children undergoing kidney replacement therapy. The search covered the period from the inception of the databases to June 20, 2023. Two independent reviewers conducted the literature screening process. Following eligibility screening, a total of 38 papers were included for data extraction and descriptive analysis.

Results

A total of 38 studies from 14 countries were finally included. The majority of which were interventional trials. The platforms used in these studies included remote monitoring systems, apps, websites, mobile phones or tablets, and social platforms. These platforms provided patients with a wide range of services, including disease management, behavioral intervention, social support, and follow-up care. Most studies focused on patient clinical indicators, patient experience, quality of life, and healthcare costs.

Conclusion

Our findings that mobile health management has been widely used in disease management of end-stage renal disease patients, with rich management content and many evaluation indicators. Future studies should strengthen the evaluation of patients' mental health, quality of life, and healthcare costs. Additionally, developing a clinical decision support system would enable mobile health management to play a more effective role in end-stage renal disease patients.

Accurate Modeling of Ejection Fraction and Stroke Volume With Mobile Phone Auscultation: Prospective Case-Control Study

BACKGROUND

Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal reimbursement dollars. No current modality or technology allows for accurate measurement of relevant HF parameters in ambulatory, rural, or underserved settings. This limits the use of telehealth to diagnose or monitor HF in ambulatory patients.

OBJECTIVE

This study describes a novel HF diagnostic technology using audio recordings from a standard mobile phone.

METHODS

This prospective study of acoustic microphone recordings enrolled convenience samples of patients from 2 different clinical sites in 2 separate areas of the United States. Recordings were obtained at the aortic (second intercostal) site with the patient sitting upright. The team used recordings to create predictive algorithms using physics-based (not neural networks) models. The analysis matched mobile phone acoustic data to ejection fraction (EF) and stroke volume (SV) as evaluated by echocardiograms. Using the physics-based approach to determine features eliminates the need for neural networks and overfitting strategies entirely, potentially offering advantages in data efficiency, model stability, regulatory visibility, and physical insightfulness.

RESULTS

Recordings were obtained from 113 participants. No recordings were excluded due to background noise or for any other reason. Participants had diverse racial backgrounds and body surface areas. Reliable echocardiogram data were available for EF from 113 patients and for SV from 65 patients. The mean age of the EF cohort was 66.3 (SD 13.3) years, with female patients comprising 38.3% (43/113) of the group. Using an EF cutoff of ≤40% versus >40%, the model (using 4 features) had an area under the receiver operating curve (AUROC) of 0.955, sensitivity of 0.952, specificity of 0.958, and accuracy of 0.956. The mean age of the SV cohort was 65.5 (SD 12.7) years, with female patients comprising 34% (38/65) of the group. Using a clinically relevant SV cutoff of <50 mL versus >50 mL, the model (using 3 features) had an AUROC of 0.922, sensitivity of 1.000, specificity of 0.844, and accuracy of 0.923. Acoustics frequencies associated with SV were observed to be higher than those associated with EF and, therefore, were less likely to pass through the tissue without distortion.

CONCLUSIONS

This work describes the use of mobile phone auscultation recordings obtained with unaltered cellular microphones. The analysis reproduced the estimates of EF and SV with impressive accuracy. This technology will be further developed into a mobile app that could bring screening and monitoring of HF to several clinical settings, such as home or telehealth, rural, remote, and underserved areas across the globe. This would bring high-quality diagnostic methods to patients with HF using equipment they already own and in situations where no other diagnostic and monitoring options exist.

Efficacy of polygenic risk scores and digital technologies for INNOvative personalized cardiovascular disease PREVention in high-risk adults: protocol of a randomized controlled trial

Background

Cardiovascular diseases (CVDs) pose a significant global health challenge, necessitating innovative approaches for primary prevention. Personalized prevention, based on genetic risk scores (PRS) and digital technologies, holds promise in revolutionizing CVD preventive strategies. However, the clinical efficacy of these interventions requires further investigation. This study presents the protocol of the INNOPREV randomized controlled trial, aiming to evaluate the clinical efficacy of PRS and digital technologies in personalized cardiovascular disease prevention.

Methods

The INNOPREV trial is a four-arm RCT conducted in Italy. A total of 1,020 participants, aged 40-69 with high 10-year CVD risk based on SCORE 2 charts, will be randomly assigned to traditional CVD risk assessment, genetic testing (CVD PRS), digital intervention (app and smart band), or a combination of genetic testing and digital intervention. The primary objective is to evaluate the efficacy of providing CVD PRS information, measured at baseline, either alone or in combination with the use of an app and a smart band, on two endpoints: changes in lifestyle patterns, and modification in CVD risk profiles. Participants will undergo a comprehensive assessment and cardiovascular evaluation at baseline, with follow-up visits at one, five, and 12 months. Lifestyle changes and CVD risk profiles will be assessed at different time points beyond the initial assessment, using the Life's Essential 8 and SCORE 2, respectively. Blood samples will be collected at baseline and at study completion to evaluate changes in lipid profiles. The analysis will employ adjusted mixed-effect models for repeated measures to assess significant differences in the data collected over time. Additionally, potential moderators and mediators will be examined to understand the underlying mechanisms of behavior change.

Discussion

As the largest trial in this context, the INNOPREV trial will contribute to the advancement of personalized cardiovascular disease prevention, with the potential to positively impact public health and reduce the burden of CVDs on healthcare systems. By systematically examining the clinical efficacy of PRS and digital interventions, this trial aims to provide valuable evidence to guide future preventive strategies and enhance population health outcomes.

N-of-1 health optimization: Digital monitoring of biomarker dynamics to gamify adherence to metabolic switching

The digital health field is experiencing substantial growth due to its potential for sustained and longitudinal deployment. In turn, this may drive improved monitoring and intervention as catalysts for behavioral change compared to traditional point-of-care practices. In particular, the increase in incidence of population health challenges such as diabetes, heart disease, fatty liver disease, and other disorders coupled with rising healthcare costs have emphasized the importance of exploring technical, economics, and implementation considerations, among others in the decentralization of health and healthcare innovations. Both healthy individuals and patients stand to benefit from continued technical advances and studies in these domains. To address these points, this study reports a N-of-1 study comprised of sustained regimens of intermittent fasting, fitness (strength and cardiovascular training), and high protein, low carbohydrate diet and parallel monitoring. These regimens were paired with serial blood ketone, blood glucose (wearable and finger stick) and blood pressure readings, as well as body weight measurements using a collection of devices. Collectively this suite of platforms and approaches were used to monitor metabolic switching from glucose to ketones as energy sources-a process associated with potential cardio- and neuroprotective functions. In addition to longitudinal biomarker dynamics, this work discusses user perspectives on the potential role of harnessing digital devices to these dynamics as potential gamification factors, as well as considerations for the role of biomarker monitoring in health regimen development, user stratification, and potentially informing downstream population-scale studies to address metabolic disease, healthy aging and longevity, among other indications.

Aluminum Nitride Thin Film Piezoelectric Pressure Sensor for Respiratory Rate Detection

In this study, we propose a low-cost piezoelectric flexible pressure sensor fabricated on Kapton® (Kapton™ Dupont) substrate by using aluminum nitride (AlN) thin film, designed for the monitoring of the respiration rate for a fast detection of respiratory anomalies. The device was characterized in the range of 15-30 breaths per minute (bpm), to simulate moderate difficult breathing, borderline normal breathing, and normal spontaneous breathing. These three breathing typologies were artificially reproduced by setting the expiratory to inspiratory ratios (E:I) at 1:1, 2:1, 3:1. The prototype was able to accurately recognize the breath states with a low response time (~35 ms), excellent linearity (R2 = 0.997) and low hysteresis. The piezoelectric device was also characterized by placing it in an activated carbon filter mask to evaluate the pressure generated by exhaled air through breathing acts. The results indicate suitability also for the monitoring of very weak breath, exhibiting good linearity, accuracy, and reproducibility, in very low breath pressures, ranging from 0.09 to 0.16 kPa. These preliminary results are very promising for the future development of smart wearable devices able to monitor different patients breathing patterns, also related to breathing diseases, providing a suitable real-time diagnosis in a non-invasive and fast way.

Mobile Health Intervention Contents and Their Effects on the Healthcare of Patients with Left Ventricular Assist Devices: An Integrative Review

Self-care in daily life is important for patients with a left ventricular assist device. Mobile health interventions that use an application, the cloud, or telemonitoring enable active health management. This study reviewed the literature on the contents of mobile health interventions for patients with left ventricular assist devices and their effects. We searched four electronic databases (CINAHL, Cochrane Library, EMBASE, and MEDLINE) and reference lists in May 2022. The search terms consisted of "heart-assist devices" and "residence characteristics," combined with "mobile applications," "telemonitoring," "medical informatics applications," "cell*," "app*," "smartphone," and "cloud." In total, seven studies were included in the review. Mobile health interventions included (1) self-management contents and (2) interactions between patient and healthcare providers. The mobile health device and patient's health management were evaluated as a measure of the effect. This review provides a unique understanding for leveraging mobile health interventions as an effective approach to improve healthcare among patients with left ventricular assist devices. Future mobile health intervention strategies targeting these patients should fully consider the patient's perspective. Furthermore, they should be designed and applied to help with long-term health management, accompanied by an evaluation of their effectiveness on self-care improvement.

Early Diagnosis of Cardiovascular Diseases in the Era of Artificial Intelligence: An In-Depth Review

Cardiovascular diseases (CVDs) are significant health issues that result in high death rates globally. Early detection of cardiovascular events may lower the occurrence of acute myocardial infarction and reduce death rates in people with CVDs. Traditional data analysis is inadequate for managing multidimensional data related to the risk prediction of CVDs, heart attacks, medical image interpretations, therapeutic decision-making, and disease prognosis due to the complex pathological mechanisms and multiple factors involved. Artificial intelligence (AI) is a technology that utilizes advanced computer algorithms to extract information from large databases, and it has been integrated into the medical industry. AI methods have shown the ability to speed up the advancement of diagnosing and treating CVDs such as heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease, and more. In clinical settings, AI has shown usefulness in diagnosing cardiovascular illness, improving the efficiency of supporting tools, stratifying and categorizing diseases, and predicting outcomes. Advanced AI algorithms have been intricately designed to analyze intricate relationships within extensive healthcare data, enabling them to tackle more intricate jobs compared to conventional approaches.

Smartphone-based six-lead ECG: A new device for electrocardiographic recording in dogs

Smartphone-based technology for electrocardiographic recording is now part of the new concept of mobile health in both human and veterinary medicine. Although smartphone-based ECG for electrocardiographic screening in dogs is reliable, one-lead ECG devices have mainly been evaluated. This prospective study assessed the feasibility and the diagnostic reliability of a new smartphone-based six-lead electrocardiograph (smECG) in dogs, in comparison to a standard six-lead electrocardiograph (stECG). All ECG tracings were blindly reviewed by an expert operator, who judged whether tracings were acceptable for interpretation, performed the electrocardiographic measurements, and assigned a diagnosis. The agreement in the electrocardiographic interpretation and diagnosis between smECG and stECG was assessed using the Bland-Altman test and Cohen's k test. The study included 108 client-owned dogs. The tracings obtained by the smECG were interpretable in 100 % of cases. No clinically relevant differences between smECG and stECG were found in the assessment of heart rate, interval duration, and QRS mean electrical axis. The smECG tended to underestimate the amplitude of the P and R waves. Perfect agreement was found in the detection of sinus rhythm, atrial fibrillation, ventricular arrhythmias, atrioventricular blocks, and bundle branch blocks. Our study suggests that the tested smartphone-based six-lead ECG is a clinically reliable device for the assessment of heart rate and heart rhythm in dogs, and thus could be used in a clinical setting in dogs and for telemedicine.

Establishment of a digital electrocardiogram telemonitoring system and remote consultation service

BACKGROUND

The use of telemonitoring electrocardiogram (ECG) improves the detection rate of various arrhythmias as it offers an extended recording time and does not impose activity restrictions. However, many community hospitals lack the resources to conduct this test due to a lack of cardiac function specialists and antiquated screening equipment.

OBJECTIVE

To establish a digital ECG telemonitoring system and remote consultation service between tertiary hospitals and community medical service stations to improve diagnosis and treatment effectiveness.

METHODS

We used the PI ECG telemonitoring data acquisition system, with a personal digital assistant (PDA) or computer serving as the platform for ECG acquisition, storage, display, printing, and transmission. We introduced this system to standardize the storage and transmission of ECG telemonitoring data, and ensure accurate transmission, reproducibility, and preservation of data.

RESULTS

The implementation of the PI ECG telemonitoring data acquisition system enabled the sharing of remote ambulatory electrocardiography data between Beijing Shijitan Hospital and its affiliated community hospitals. This has resulted in reduced waiting times for patients to receive reports (from 0.3 to 1 hour, to 0.1 or less), shortened consultation times (from 2 hours to 0.1 hour), and improved patient satisfaction with consultations (> 20% of the patients reported they were highly satisfied). The system successfully combined the goals of intelligence, real-time synchronization, and efficiency, revolutionizing ECG telemonitoring diagnosis in the network era.

CONCLUSION

Sharing digital telematics information between tertiary and community hospitals enables a tiered approach to diagnosis and treatment and allows for more efficient, accurate, and convenient remote diagnostics.

[Development of intelligent monitoring system based on Internet of Things and wearable technology and exploration of its clinical application mode]

Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients' cardiopulmonary function, and management of patients outside hospital.

Promoting physical activity in clinical practice through wearable technology

ABSTRACT

The negative health consequences of physical inactivity continue to be a global problem that must be addressed from the highest levels of government down to local primary care providers. Physical activity has been identified as a useful patient vital sign in health care. Advanced practice nurses should aggressively prescribe physical activity as an evidence-based intervention to help mitigate the increased mortality and morbidity associated with a sedentary lifestyle. A focused literature review was conducted using PubMed, CINAHL, and the Cochrane online databases. Fitness wearables and mobile health trackers are a catalyst for lifestyle behavior change and cultivate a health care partnership between the patient and their provider. The evolution of fitness wearables into mainstream health care hinges on the ability of devices to integrate into electronic health records, uniformity of manufacturer standards, intuitiveness, and the assurance of user privacy and security. It is incumbent on nurse practitioners to educate themselves about the reliability and practicality of fitness trackers for their patient population. Future research should focus on adopting quality standards for all consumer devices, the seamless integration of device data into electronic health records and ensuring personal privacy and security.

Electrocardiogram-based deep learning model to screen peripartum cardiomyopathy

BACKGROUND

Peripartum cardiomyopathy, one of the most fatal conditions during delivery, results in heart failure secondary to left ventricular systolic dysfunction. Left ventricular dysfunction can result in abnormalities in electrocardiography. However, the usefulness of electrocardiography in the identification of peripartum cardiomyopathy in pregnant women remains unclear.

OBJECTIVE

This study aimed to evaluate the effectiveness of a 12-lead electrocardiography-based artificial intelligence/machine learning-based software as a medical device for screening peripartum cardiomyopathy.

STUDY DESIGN

This retrospective cohort study included pregnant women who underwent transthoracic echocardiography between a month before and 5 months after delivery and underwent 12-lead electrocardiography within 30 days of echocardiography between December 2011 and May 2022 at Seoul National University Hospital. The performance of 12-lead electrocardiography-based artificial intelligence/machine learning analysis (AiTiALVSD software; version 1.00.00, which was developed to screen for left ventricular systolic dysfunction in the general population) was evaluated for the identification of peripartum cardiomyopathy. In addition, the performance of another artificial intelligence/machine learning algorithm using only 1-lead electrocardiography to detect left ventricular systolic dysfunction was evaluated in identifying peripartum cardiomyopathy. The results were obtained under a 95% confidence interval and considered significant when P<.05.

RESULTS

Among the 14,557 women who delivered during the study period, 204 (1.4%) underwent transthoracic echocardiography a month before and 5 months after delivery. Among them, 12 (5.8%) were diagnosed with peripartum cardiomyopathy. The results showed that AiTiALVSD for 12-lead electrocardiography was highly effective in detecting peripartum cardiomyopathy, with an area under the receiver operating characteristic of 0.979 (95% confidence interval, 0.953-1.000), an area under the precision-recall curve of 0.715 (95% confidence interval, 0.499-0.951), a sensitivity of 0.917 (95% confidence interval, 0.760-1.000), a specificity of 0.927 (95% confidence interval, 0.890-0.964), a positive predictive value of 0.440 (95% confidence interval, 0.245-0.635), and a negative predictive value of 0.994 (95% confidence interval, 0.983-1.000). In addition, a 1-lead (lead I) artificial intelligence/machine learning algorithm showed excellent performance; the area under the receiver operating characteristic, area under the precision-recall curve, sensitivity, specificity, positive predictive value, and negative predictive value were 0.944 (95% confidence interval, 0.895-0.993), 0.520 (95% confidence interval, 0.319-0.801), 0.833 (95% confidence interval, 0.622-1.000), 0.880 (95% confidence interval, 0.834-0.926), 0.303 (95% confidence interval, 0.146-0.460), and 0.988 (95% confidence interval, 0.972-1.000), respectively.

CONCLUSION

The 12-lead electrocardiography-based artificial intelligence/machine learning-based software as a medical device (AiTiALVSD) and 1-lead algorithm are noninvasive and effective ways of identifying cardiomyopathies occurring during the peripartum period, and they could potentially be used as highly sensitive screening tools for peripartum cardiomyopathy.

Consideration of Sex, Gender, or Age on Outcomes of Digital Technologies for Treatment and Monitoring of Chronic Obstructive Pulmonary Disease: Overview of Systematic Reviews

BACKGROUND

Several systematic reviews have addressed digital technology use for treatment and monitoring of chronic obstructive pulmonary disease (COPD).

OBJECTIVE

This study aimed to assess if systematic reviews considered the effects of sex, gender, or age on the outcomes of digital technologies for treatment and monitoring of COPD through an overview of such systematic reviews. The objectives of this overview were to (1) describe the definitions of sex or gender used in reviews; (2) determine whether the consideration of sex, gender, or age was planned in reviews; (3) determine whether sex, gender, or age was reported in review results; (4) determine whether sex, gender, or age was incorporated in implications for clinical practice in reviews; and (5) create an evidence map for development of individualized clinical recommendations for COPD based on sex, gender, or age diversity.

METHODS

MEDLINE, the Cochrane Library, Epistemonikos, Web of Science, and the bibliographies of the included systematic reviews were searched to June 2022. Inclusion was based on the PICOS framework: (1) population (COPD), (2) intervention (any digital technology), (3) comparison (any), (4) outcome (any), and (5) study type (systematic review). Studies were independently selected by 2 authors based on title and abstract and full-text screening. Data were extracted by 1 author and checked by another author. Data items included systematic review characteristics; PICOS criteria; and variables related to sex, gender, or age. Systematic reviews were appraised using A Measurement Tool to Assess Systematic Reviews, version 2 (AMSTAR 2). Data were synthesized using descriptive statistics.

RESULTS

Of 1439 records, 30 systematic reviews published between 2010 and 2022 were included in this overview. The confidence in the results of 25 of the 30 (83%) reviews was critically low according to AMSTAR 2. The reviews focused on user outcomes that potentially depend on sex, gender, or age, such as efficacy or effectiveness (25/30, 83%) and acceptance, satisfaction, or adherence (3/30, 10%) to digital technologies for COPD. Reviews reported sex or gender (19/30 systematic reviews) or age (25/30 systematic reviews) among primary study characteristics. However, only 1 of 30 reviews included age in a subgroup analysis, and 3 of 30 reviews identified the effects of sex, gender, or age as evidence gaps.

CONCLUSIONS

This overview shows that the effects of sex, gender, or age were rarely considered in 30 systematic reviews of digital technologies for COPD treatment and monitoring. Furthermore, systematic reviews did not incorporate sex, gender, nor age in their implications for clinical practice. We recommend that future systematic reviews should (1) evaluate the effects of sex, gender, or age on the outcomes of digital technologies for treatment and monitoring of COPD and (2) better adhere to reporting guidelines to improve the confidence in review results.

TRIAL REGISTRATION

PROSPERO CRD42022322924; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=322924.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/40538.

Characterizing Real-World Implementation of Consumer Wearables for the Detection of Undiagnosed Atrial Fibrillation in Clinical Practice: Targeted Literature Review

BACKGROUND

Atrial fibrillation (AF), the most common cardiac arrhythmia, is often undiagnosed because of lack of awareness and frequent asymptomatic presentation. As AF is associated with increased risk of stroke, early detection is clinically relevant. Several consumer wearable devices (CWDs) have been cleared by the US Food and Drug Administration for irregular heart rhythm detection suggestive of AF. However, recommendations for the use of CWDs for AF detection in clinical practice, especially with regard to pathways for workflows and clinical decisions, remain lacking.

OBJECTIVE

We conducted a targeted literature review to identify articles on CWDs characterizing the current state of wearable technology for AF detection, identifying approaches to implementing CWDs into the clinical workflow, and characterizing provider and patient perspectives on CWDs for patients at risk of AF.

METHODS

PubMed, ClinicalTrials.gov, UpToDate Clinical Reference, and DynaMed were searched for articles in English published between January 2016 and July 2023. The searches used predefined Medical Subject Headings (MeSH) terms, keywords, and search strings. Articles of interest were specifically on CWDs; articles on ambulatory monitoring tools, tools available by prescription, or handheld devices were excluded. Search results were reviewed for relevancy and discussed among the authors for inclusion. A qualitative analysis was conducted and themes relevant to our study objectives were identified.

RESULTS

A total of 31 articles met inclusion criteria: 7 (23%) medical society reports or guidelines, 4 (13%) general reviews, 5 (16%) systematic reviews, 5 (16%) health care provider surveys, 7 (23%) consumer or patient surveys or interviews, and 3 (10%) analytical reports. Despite recognition of CWDs by medical societies, detailed guidelines regarding CWDs for AF detection were limited, as was the availability of clinical tools. A main theme was the lack of pragmatic studies assessing real-world implementation of CWDs for AF detection. Clinicians expressed concerns about data overload; potential for false positives; reimbursement issues; and the need for clinical tools such as care pathways and guidelines, preferably developed or endorsed by professional organizations. Patient-facing challenges included device costs and variability in digital literacy or technology acceptance.

CONCLUSIONS

This targeted literature review highlights the lack of a comprehensive body of literature guiding real-world implementation of CWDs for AF detection and provides insights for informing additional research and developing appropriate tools and resources for incorporating these devices into clinical practice. The results should also provide an impetus for the active involvement of medical societies and other health care stakeholders in developing appropriate tools and resources for guiding the real-world use of CWDs for AF detection. These resources should target clinicians, patients, and health care systems with the goal of facilitating clinician or patient engagement and using an evidence-based approach for establishing guidelines or frameworks for administrative workflows and patient care pathways.

Patient Outcomes Associated with the First Remote Monitoring Experience of Cardiac Implantable Electronic Devices in South Korea

Purpose

Remote monitoring of cardiac devices reduces unnecessary outpatient visits and increases patient satisfaction. We aimed to evaluate remote monitoring in terms of patient satisfaction, economic efficiency, and safety.

Patients and Methods

This was a single university hospital survey. The time/medical cost efficacy and satisfaction index were evaluated using a questionnaire to investigate patient satisfaction before and after remote monitoring in patients using Biotronik implantable cardiac devices. The questionnaire was adopted and modified from Hwang's 2020 Survey on Telehealth Patient Experience.

Results

Remote monitoring was associated with a decrease in total outpatient visits. Of 1270 remote monitoring-related alerts clinicians received during the study period, more than 95% were from patients with pacemakers. Still, the severity of alerts was higher for implantable cardioverter defibrillators and cardiac resynchronization therapy with defibrillators. The post-RM survey results demonstrated that patients were generally satisfied with RM, perceived it as cost-effective, and found that RM facilitated health management without disrupting their daily routines.

Conclusion

The study participants were satisfied with their first remote monitoring experience and reported having time- and cost-savings by using remote monitoring. Remote monitoring-related alerts from high-voltage devices were more severe and required medical intervention.

Research on digital tool in cognitive assessment: a bibliometric analysis

Objective

The number of research into new cognitive assessment tools has increased rapidly in recent years, sparking great interest among professionals. However, there is still little literature revealing the current status and future trends of digital technology use in cognitive assessment. The aim of this study was to summarize the development of digital cognitive assessment tools through the bibliometric method.

Methods

We carried out a comprehensive search in the Web of Science Core Collection to identify relevant papers published in English between January 1, 2003, and April 3, 2023. We used the subjects such as "digital," "computer," and "cognitive," and finally 13,244 related publications were collected. Then we conducted the bibliometric analysis by Bibliometrix" R-package, VOSviewer and CiteSpace software, revealing the prominent countries, authors, institutions, and journals.

Results

11,045 articles and 2,199 reviews were included in our analyzes. The number of annual publications in this field was rising rapidly. The results showed that the most productive countries, authors and institutions were primarily located in economically developed regions, especially the North American, European, and Australian countries. Research cooperation tended to occur in these areas as well. The application of digital technology in cognitive assessment appealed to growing attention during the outbreak of the COVID-19 epidemic.

Conclusion

Digital technology uses have had a great impact on cognitive assessment and health care. There have been substantial papers published in these areas in recent years. The findings of the study indicate the great potential of digital technology in cognitive assessment.

Morphic Sensors for Respiratory Parameters Estimation: Validation against Overnight Polysomnography

Effective monitoring of respiratory disturbances during sleep requires a sensor capable of accurately capturing chest movements or airflow displacement. Gold-standard monitoring of sleep and breathing through polysomnography achieves this task through dedicated chest/abdomen bands, thermistors, and nasal flow sensors, and more detailed physiology, evaluations via a nasal mask, pneumotachograph, and airway pressure sensors. However, these measurement approaches can be invasive and time-consuming to perform and analyze. This work compares the performance of a non-invasive wearable stretchable morphic sensor, which does not require direct skin contact, embedded in a t-shirt worn by 32 volunteer participants (26 males, 6 females) with sleep-disordered breathing who performed a detailed, overnight in-laboratory sleep study. Direct comparison of computed respiratory parameters from morphic sensors versus traditional polysomnography had approximately 95% (95 ± 0.7) accuracy. These findings confirm that novel wearable morphic sensors provide a viable alternative to non-invasively and simultaneously capture respiratory rate and chest and abdominal motions.

Digital health in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations and hospitalizations. Early identification of individuals at high risk of COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because of a lack of knowledge about the disease, limited access to resources, and insufficient clinical support. The growth of digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, the Internet of Things, mobile health, wearable technology, and digital therapeutics-offers opportunities for improving the early diagnosis and management of COPD. This study reviewed the field of digital health in terms of COPD. The findings showed that despite significant advances in digital health, there are still obstacles impeding its effectiveness. Finally, we highlighted some of the major challenges and possibilities for developing and integrating digital health in COPD management.

Telemedicine in Adult Congenital Heart Disease: Usefulness of Digital Health Technology in the Assistance of Critical Patients

The number of adults with congenital heart disease (ACHD) has progressively increased in recent years to surpass that of children. This population growth has produced a new demand for health care. Moreover, the 2019 coronavirus pandemic has caused significant changes and has underlined the need for an overhaul of healthcare delivery. As a result, telemedicine has emerged as a new strategy to support a patient-based model of specialist care. In this review, we would like to highlight the background knowledge and offer an integrated care strategy for the longitudinal assistance of ACHD patients. In particular, the emphasis is on recognizing these patients as a special population with special requirements in order to deliver effective digital healthcare.

The Italian Society of Cardiology and Working Group on Telecardiology and Informatics 2023 updated position paper on telemedicine and artificial intelligence in cardiovascular disease

In 2015, the Italian Society of Cardiology and its Working Group on Telemedicine and Informatics issued a position paper on Telecardiology, resuming the most eminent evidence supporting the use of information and communication technology in principal areas of cardiovascular care, ranked by level of evidence. More than 5 years later and after the global shock inflicted by the SARS-CoV-2 pandemic, an update on the topic is warranted. Recent evidence and studies on principal areas of cardiovascular disease will be therefore reported and discussed, with particular focus on telemedicine for cardiovascular care in the COVID-19 context. Novel perspectives and opportunities disclosed by artificial intelligence and its applications in cardiovascular disease will also be discussed. Finally, modalities by which machine learning have realized remote patient monitoring and long-term care in recent years, mainly filtering critical clinical data requiring selective hospital admission, will be provided.

From Data to Diagnosis: How Machine Learning Is Changing Heart Health Monitoring

The rapid advances in science and technology in the field of artificial neural networks have led to noticeable interest in the application of this technology in medicine. Given the need to develop medical sensors that monitor vital signs to meet both people's needs in real life and in clinical research, the use of computer-based techniques should be considered. This paper describes the latest progress in heart rate sensors empowered by machine learning methods. The paper is based on a review of the literature and patents from recent years, and is reported according to the PRISMA 2020 statement. The most important challenges and prospects in this field are presented. Key applications of machine learning are discussed in medical sensors used for medical diagnostics in the area of data collection, processing, and interpretation of results. Although current solutions are not yet able to operate independently, especially in the diagnostic context, it is likely that medical sensors will be further developed using advanced artificial intelligence methods.

Wearable Devices in Cardiovascular Medicine

Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.

Access and reimbursement pathways for digital health solutions and in vitro diagnostic devices: Current scenario and challenges

Objectives

Digital therapeutics (DTx) are innovative solutions that use meaningful data to provide evidence-based decisions for the prevention, treatment, and management of diseases. Particular attention is paid to software-based in vitro diagnostics (IVDs). With this point of view, a strong connection between DTx and IVDs is observed.

Methods

We investigated the current regulatory scenarios and reimbursement approaches adopted for DTx and IVDs. The initial assumption was that countries apply different regulations for the access to the market and adopt different reimbursement systems for both DTx and IVDs. The analysis was limited to the US, European countries (Germany, France, and UK), and Australia due to maturity in digital health product adoption and regulatory processes, and recent regulations related to IVDs. The final aim was to provide a general comparative overview and identify those aspects that should be better addressed to support the adoption and commercialization of DTx and IVDs.

Results

Many countries regulate DTx as medical devices or software integrated with a medical device, and some have a more specific pathway than others. Australia has more specific regulations classifying software used in IVD. Some EU countries are adopting similar processes to the Digital Health Applications (DiGA) under Germany's Digitale-Versorgung Gesetz (DVG) law, which deems DTx eligible for reimbursement during the fast access pathway. France is working on a fast-track system to make DTx available to patients and reimbursable by the public system. The US retains some coverage through private insurance, federal and state programs like Medicaid and Veterans Affairs, and out-of-pocket spending. The updated Medical Devices Regulation (MDR) and In Vitro Diagnostic Regulation (IVDR) in the EU includes a classification system specifying how software integrated with medical devices, and IVDs specifically must be regulated.

Conclusion

The outlook for DTx and IVDs is changing as they are becoming more technologically advanced, and some countries are adapting their device classifications depending on specific features. Our analysis showed the complexity of the issue demonstrating how fragmented are regulatory systems for DTx and IVDs. Differences emerged in terms of definitions, terminology, requested evidence, payment approaches and the overall reimbursement landscape. The complexity is expected to have a direct impact on the commercialization of and access to DTx and IVDs. In this scenario, willingness to pay of different stakeholders is a key theme.

Ethical Issues in the Use of Smartphone Apps for HIV Prevention in Malaysia: Focus Group Study With Men Who Have Sex With Men

BACKGROUND

The use of smartphone apps can improve the HIV prevention cascade for key populations such as men who have sex with men (MSM). In Malaysia, where stigma and discrimination toward MSM are high, mobile health app-based strategies have the potential to open new frontiers for HIV prevention. However, little guidance is available to inform researchers about the ethical concerns that are unique to the development and implementation of app-based HIV prevention programs.

OBJECTIVE

This study aimed to fill this gap by characterizing the attitudes and concerns of Malaysian MSM regarding HIV prevention mobile apps, particularly regarding the ethical aspects surrounding their use.

METHODS

We conducted web-based focus group discussions with 23 MSM between August and September 2021. Using in-depth semistructured interviews, participants were asked about the risks and ethical issues they perceived to be associated with using mobile apps for HIV prevention. Each session was digitally recorded and transcribed. Transcripts were inductively coded using the Dedoose software (SocioCultural Research Consultants) and analyzed to identify and interpret emerging themes.

RESULTS

Although participants were highly willing to use app-based strategies for HIV prevention, they raised several ethical concerns related to their use. Prominent concerns raised by participants included privacy and confidentiality concerns, including fear of third-party access to personal health information (eg, friends or family and government agencies), issues around personal health data storage and management, equity and equitable access, informed consent, and regulation.

CONCLUSIONS

The study's findings highlight the role of ethical concerns related to the use of app-based HIV prevention programs. Given the ever-growing nature of such technological platforms that are intermixed with a complex ethical-legal landscape, mobile health platforms must be safe and secure to minimize unintended harm, safeguard user privacy and confidentiality, and obtain public trust and uptake.

Clinical Evaluation of the ButterfLife Device for Simultaneous Multiparameter Telemonitoring in Hospital and Home Settings

We conducted a two-phase study to test the reliability and usability of an all-in-one artificial intelligence-based device (ButterfLife), which allows simultaneous monitoring of five vital signs. The first phase of the study aimed to test the agreement between measurements performed with ButterfLife vs. standard of care (SoC) in 42 hospitalized patients affected by acute respiratory failure. In this setting, the greatest discordance between ButterfLife and SoC was in respiratory rate (mean difference -4.69 bpm). Significantly close correlations were observed for all parameters except diastolic blood pressure and oxygen saturation (Spearman's Rho -0.18 mmHg; p = 0.33 and 0.20%; p = 0.24, respectively). The second phase of the study was conducted on eight poly-comorbid patients using ButterfLife at home, to evaluate the number of clinical conditions detected, as well as the patients' compliance and satisfaction. The average proportion of performed tests compared with the scheduled number was 67.4%, and no patients reported difficulties with use. Seven conditions requiring medical attention were identified, with a sensitivity of 100% and specificity of 88.9%. The median patient satisfaction was 9.5/10. In conclusion, ButterfLife proved to be a reliable and easy-to-use device, capable of simultaneously assessing five vital signs in both hospital and home settings.

Integrating digital inhalers into clinical care of patients with asthma and chronic obstructive pulmonary disease

Modernizing inhaled medications through digital technology can help address persistent problems of non-adherence and poor inhaler technique in patients with obstructive lung diseases. With a growing body of supportive clinical studies, advances in digital inhaler sensors and platforms, greater support from payers and healthcare organizations, significant growth with these technologies is expected. While all digital (smart) inhalers record adherence, these are distinguished by their compatibility with commercial inhalers, capabilities to guide inhaler technique, use of patient-reported outcomes, and user-friendliness for both the healthcare professional (HCP) and patient. Due to the complexity and novelty of employing digital inhalers, collaboration with multiple entities within health systems is necessary and a well-planned integration is needed. For HCPs and patients, cybersecurity and privacy are critical, it will require review by each healthcare organization. In the US, some payers reimburse for remote monitoring using digital inhalers, but reimbursement is currently unavailable in other countries. There are several models for remote patient care, as employing an active, ongoing digital interface between the HCP and patient or they may choose to only review data at clinical encounters. Personalization of therapies and feedback are key to success. While digital inhaler malfunction uncommonly occurs, patient attrition over a year is significant. Some patients will be challenged to use digital platforms or have the necessary technology. Additional research is needed to address cost-effectiveness, in vivo accuracy of inspiratory measurement capable devices, ability to teach inhaler technique, their application for monitoring lung function, and lastly real-world adoption and implementation in routine clinical practice.

The Influence of Sex, Gender, or Age on Outcomes of Digital Technologies for Treatment and Monitoring of Chronic Obstructive Pulmonary Disease: Protocol for an Overview of Systematic Reviews

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common chronic disease that can be treated and monitored with various digital technologies. Digital technologies offer unique opportunities for treating and monitoring people with chronic diseases, but little is known about whether the outcomes of such technologies depend on sex, gender, or age in people with COPD.

OBJECTIVE

The general objective of this study is to assess the possible influence of sex, gender, or age on outcomes of digital technologies for treatment and monitoring of COPD through an overview of systematic reviews.

METHODS

The study is planned as an overview of systematic reviews. Study reporting is based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 guidelines because guidelines for overviews are not available as of this writing. The information sources for the overview will include 4 bibliographic databases (MEDLINE, Cochrane Library, Epistemonikos, and Web of Science) as well as the bibliographies of the included systematic reviews. The electronic search strategy will be developed and conducted in collaboration with an experienced database specialist. The search results will be presented in accordance with the PRISMA 2020 guidelines. The eligibility of studies is based on the population, intervention, comparison, outcomes, and study design (PICOS) criteria: (1) people with COPD (population), (2) digital technology intervention for treatment or monitoring (intervention), (3) any control group or no control group (comparison), (4) any outcome, and (5) systematic review of randomized controlled trials or non-randomized controlled trials with or without a meta-analysis (study design). Critical appraisal of the included systematic reviews will be performed using A Measurement Tool to Assess Systematic Reviews, version 2 (AMSTAR 2). Data will be extracted using a standardized data extraction sheet.

RESULTS

The literature search is scheduled for June 2022. We expect to select the relevant systematic reviews, code the data, and appraise the systematic reviews by December 2022.

CONCLUSIONS

There is a growing recognition that the influence of sex, gender, or age should be considered in research design and outcome reporting in the context of health care interventions. Our overview will identify systematic reviews of various digital technologies for treatment or monitoring of COPD. The most interesting aspect of the overview will be to investigate if any systematic reviews considered the influence of sex, gender, or age on the outcomes of such digital technologies in COPD. Evidence from the overview could be used to guide more individualized (sex, gender, or age-based) recommendations for the use of digital technologies among people with COPD.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022322924; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=322924.

Role of decentralized clinical trials in cancer drug development: Results from a survey of oncologists and patients

As a result of the unprecedented challenges imposed by the COVID-19 pandemic on enrollment to cancer clinical trials, there has been an urgency to identify and incorporate new solutions to mitigate these difficulties. The concept of decentralized or hybrid clinical trials has rapidly gained currency, given that it aims to reduce patient burden, increase patient enrollment and retention, and preserve quality of life, while also increasing the efficiency of trial logistics. Therefore, the clinical trial environment is moving toward remote collection and assessment of data, transitioning from the classic site-centric model to one that is more patient-centric.

Research on Digital Technology Use in Cardiology: Bibliometric Analysis

Background

Digital technology uses in cardiology have become a popular research focus in recent years. However, there has been no published bibliometric report that analyzed the corresponding academic literature in order to derive key publishing trends and characteristics of this scientific area.

Objective

We used a bibliometric approach to identify and analyze the academic literature on digital technology uses in cardiology, and to unveil popular research topics, key authors, institutions, countries, and journals. We further captured the cardiovascular conditions and diagnostic tools most commonly investigated within this field.

Methods

The Web of Science electronic database was queried to identify relevant papers on digital technology uses in cardiology. Publication and citation data were acquired directly from the database. Complete bibliographic data were exported to VOSviewer, a dedicated bibliometric software package, and related to the semantic content of titles, abstracts, and keywords. A term map was constructed for findings visualization.

Results

The analysis was based on data from 12,529 papers. Of the top 5 most productive institutions, 4 were based in the United States. The United States was the most productive country (4224/12,529, 33.7%), followed by United Kingdom (1136/12,529, 9.1%), Germany (1067/12,529, 8.5%), China (682/12,529, 5.4%), and Italy (622/12,529, 5.0%). Cardiovascular diseases that had been frequently investigated included hypertension (152/12,529, 1.2%), atrial fibrillation (122/12,529, 1.0%), atherosclerosis (116/12,529, 0.9%), heart failure (106/12,529, 0.8%), and arterial stiffness (80/12,529, 0.6%). Recurring modalities were electrocardiography (170/12,529, 1.4%), angiography (127/12,529, 1.0%), echocardiography (127/12,529, 1.0%), digital subtraction angiography (111/12,529, 0.9%), and photoplethysmography (80/12,529, 0.6%). For a literature subset on smartphone apps and wearable devices, the Journal of Medical Internet Research (20/632, 3.2%) and other JMIR portfolio journals (51/632, 8.0%) were the major publishing venues.

Conclusions

Digital technology uses in cardiology target physicians, patients, and the general public. Their functions range from assisting diagnosis, recording cardiovascular parameters, and patient education, to teaching laypersons about cardiopulmonary resuscitation. This field already has had a great impact in health care, and we anticipate continued growth.

Sexual Health-related Quality of Life in Women with Pulmonary Arterial Hypertension: Compensating for Loss

Rationale: Health-related quality of life (HRQoL) in patients with pulmonary arterial hypertension (PAH) has become increasingly important in disease management as numerous treatment options have improved prognosis and time to clinical worsening. Sexual-HRQoL is poorly understood in patients with PAH, but previous work has shown that patients may face unrecognized challenges, especially related to parenteral prostanoid analogue therapies. Objective: Using qualitative methods, describe challenges and perspectives of sexual-HRQoL among women with PAH. Methods: We conducted 13 semi-structured in-depth interviews at the Pulmonary Hypertension Association's International Pulmonary Hypertension (PH) Conference and Scientific Sessions among female attendees with self-reported World Symposium on PH Group 1 PAH. A coding structure using both deductive and inductive coding was developed to organize and analyze data using applied thematic analysis. Salient themes were identified and presented here using summary and illustrative quotes. Results: Ninety-two percent (12/13) of participants reported a decline in frequency of sex after diagnosis with PAH. A significant portion (62%; 8/13) experienced fear of having sexual intercourse due to cardiopulmonary symptoms. All participants (100%; 13/13) reported compensatory behaviors/strategies during and around sexual intercourse; some participants on subcutaneous prostanoids also reported timing intercourse to coincide with infusion site changes and, as a result, interrupted treatment during this time. Participants reported changing positions during sex to reduce breathlessness, and some reported removing oxygen to avoid interrupting intimacy. Most participants endorsed negative body image related to their medications, external oxygen supplementation, and/or body weight fluctuations (54%; 7/13). Many participants revealed they had never discussed sexual practices with a healthcare professional and desired increased communication and discussion with their providers. Conclusions: Women with PAH face significant burdens and challenges regarding sexual-HRQoL. PAH therapies directly impact sexual-HRQoL. Further targeted qualitative and quantitative studies are needed to better characterize and improve sexual-HRQoL in patients with PAH.

Medical Data Acquisition and Internet of Things Technology-Based Cerebral Stroke Disease Prevention and Rehabilitation Nursing Mobile Medical Management System

This research was aimed at exploring the application value of a mobile medical management system based on Internet of Things technology and medical data collection in stroke disease prevention and rehabilitation nursing. In this study, on the basis of radio frequency identification (RFID) technology, the signals collected by the sensor were filtered by the optimized median filtering algorithm, and a rehabilitation nursing evaluation model was established based on the backpropagation (BP) neural network. The performance of the medical management system was verified in 32 rehabilitation patients with hemiplegia after stroke and 6 healthy medical staff in the rehabilitation medical center of the hospital. The results showed that the mean square error (MSE) and peak signal-to-noise ratio (PSNR) of the median filtering algorithm after optimization were significantly higher than those before optimization (P < 0.05). When the number of neurons was 23, the prediction accuracy of the test set reached a maximum of 89.83%. Using traingda as the training function, the model had the lowest training time and root mean squared error (RMSE) value of 2.5 s and 0.29, respectively, which were significantly lower than the traingd and traingdm functions (P < 0.01). The error percentage and RMSE of the model reached a minimum of 7.56% and 0.25, respectively, when the transfer functions of both the hidden and input layers were tansig. The prediction accuracy in stages III~VI was 90.63%. It indicated that the mobile medical management system established based on Internet of Things technology and medical data collection has certain application value for the prevention and rehabilitation nursing of stroke patients, which provides a new idea for the diagnosis, treatment, and rehabilitation of stroke patients.

Financial Burden and Shortage of Respiratory Rehabilitation for SARS-CoV-2 Survivors: The Next Step of the Pandemic?

We read with great enthusiasm the recent article by Daynes et al [...]

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies' abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.

Factors affecting patient and physician engagement in remote healthcare for heart failure: a systematic review (Preprint)

Background

Objective

Methods

Results

Conclusions

Multimodal biometric monitoring technologies drive the development of clinical assessments in the home environment

Biometric monitoring technologies (BioMeTs) have attracted the attention of the health care community because of their user-friendly form factor and multi-sensor data-collection capabilities. The potential benefits of remote monitoring for collecting comprehensive, longitudinal, and contextual datasets span therapeutic areas, and both chronic and acute disease settings. Importantly, multimodal BioMeTs unlock the ability to generate rich contextual data to augment digital measures. Currently, the availability of devices is no longer the main factor limiting adoption but rather the ability to integrate fit-for-purpose BioMeTs reliably and safely into clinical care. We provide a critical review of the state of art for multimodal BioMeTs in clinical care and identify three unmet clinical needs: 1) expand the abilities of existing ambulatory unimodal BioMeTs; 2) adapt standardized clinical test protocols ("spot checks'') for use under free living conditions; and 3) develop novel applications to manage rehabilitation and chronic diseases. As the field is still in an early and quickly evolving state, we make practical recommendations: 1) to select appropriate BioMeTs; 2) to develop composite digital measures; and 3) to design interoperable software to ingest, process, delegate, and visualize the data when deploying novel clinical applications. Multimodal BioMeTs will drive the evolution from in-clinic assessments to at-home data collection with a focus on prevention, personalization, and long-term outcomes by empowering health care providers with knowledge, delivering convenience, and an improved standard of care to patients.

Digital Inhalers for Asthma or Chronic Obstructive Pulmonary Disease: A Scientific Perspective

Impressive advances in inhalation therapy for patients with asthma and chronic obstructive pulmonary disease (COPD) have occurred in recent years. However, important gaps in care remain, particularly relating to poor adherence to inhaled therapies. Digital inhaler health platforms which incorporate digital inhalers to monitor time and date of dosing are an effective disease and medication management tool, promoting collaborative care between clinicians and patients, and providing more in-depth understanding of actual inhaler use. With advances in technology, nearly all inhalers can be digitalized with add-on or embedded sensors to record and transmit data quantitating inhaler actuations, and some have additional capabilities to evaluate inhaler technique. In addition to providing an objective and readily available measure of adherence, they allow patients to interact with the device directly or through their self-management smartphone application such as via alerts and recording of health status. Clinicians can access these data remotely and during patient encounters, to better inform them about disease status and medication adherence and inhaler technique. The ability for remote patient monitoring is accelerating interest in and the use of these devices in clinical practice and research settings. More than 20 clinical studies of digital inhalers in asthma or COPD collectively show improvement in medication adherence, exacerbation risk, and patient outcomes with digital inhalers. These studies support previous findings about patient inhaler use and behaviors, but with greater granularity, and reveal some new findings about patient medication-taking behaviors. Digital devices that record inspiratory flows with inhaler use can guide proper inhaler technique and may prove to be a clinically useful lung function measure. Adoption of digital inhalers into practice is still early, and additional research is needed to determine patient and clinician acceptability, the appropriate place of these devices in the therapeutic regimen, and their cost effectiveness.

Smartphone application alerts for early trauma team activation: Millennial technology in healthcare

BACKGROUND

Data access through smartphone applications (apps) has reframed procedure and policy in healthcare, but its impact in trauma remains unclear. Citizen is a free app that provides real-time alerts curated from 911 dispatch data. Our primary objective was to determine whether app alerts occurred earlier than recorded times for trauma team activation and emergency department arrival.

METHODS

Trauma registry entries were extracted from a level one urban trauma center from January 1, 2018 to June 30, 2019 and compared with app metadata from the center catchment area. We matched entries to metadata according to description, date, time, and location then compared metadata timestamps to trauma team activation and emergency department arrival times. We computed percentage of time the app reported traumatic events earlier than trauma team activation or emergency department arrival along with exact binomial 95% confidence interval; median differences between times were presented along with interquartile ranges.

RESULTS

Of 3,684 trauma registry entries, 209 (5.7%) matched app metadata. App alerts were earlier for 96.1% and 96.2% of trauma team activation and emergency department arrival times, respectively, with events reported median 36 (24-53, IQR) minutes earlier than trauma team activation and 32 (25-42, IQR) minutes earlier than emergency department arrival. Registry entries for younger males, motor vehicle-related injuries and penetrating traumas were more likely to match alerts (P < .0001).

CONCLUSION

Apps like Citizen may provide earlier notification of traumatic events and therefore earlier mobilization of trauma service resources. Earlier notification may translate into improved patient outcomes. Additional studies into the benefit of apps for trauma care are warranted.

Critical Success Factors in Adoption of Wearable Technology Devices for Seniors in Thailand

The adoption of wearable devices has been proposed as a promising approach to improve the well-being of senior in Thai care services. This study aims to find the critical success factors (CSFs) in adopting wearable technology from the stakeholder perspective. We collected data from total 27 participants from three groups of stakeholders: formal caregivers, informal caregivers, and seniors. Using the grounded theory approach, we found four types of CSFs and its variety in according to devices and stakeholders’ viewpoints. Based on the findings, this paper also discusses how to develop wearable devices to satisfy stakeholder requirements and improve their wellbeing.

Cardiac Rehabilitation: A Bibliometric Review From 2001 to 2020

Cardiovascular disease (CVD) is a serious threat to global public health due to its high prevalence and disability rate. Meanwhile, cardiac rehabilitation (CR) has attracted increasing attention for its positive effects on the cardiovascular system. There is overwhelming evidence that CR for patients with CVD is effective in reducing cardiovascular morbidity and mortality. To learn more about the development of CR, 5,567 papers about CR and related research were retrieved in the Web of Science Core Collection from 2001 to 2020. Then, these publications were scientometrically analyzed based on CiteSpace in terms of spatiotemporal distribution, author distribution, subject categories, topic distribution, and references. The results can be elaborated from three aspects. Firstly, the number of annual publications related to CR has increased year by year in general over the past two decades. Secondly, a co-occurrence analysis of the output countries and authors shows that a few developed countries such as the United States, Canada, and the UK are the most active in carrying out CR and where regional academic communities represented by Sherry Grace and Ross Arena were formed. Thirdly, an analysis of the subject categories and topic distribution of the papers reveals that CR is a typical interdiscipline with a wide range of disciplines involved, including clinical medicine, basic medicine, public health management, and sports science. The research topics cover the participants and implementers, components, and the objectives and requirements of CR. The current research hotspots are the three core modalities of CR, namely patient education, exercise training and mental support, as well as mobile health (mHealth) dependent on computer science. In conclusion, this work has provided some useful information for acquiring knowledge about CR, including identifying potential collaborators for researchers interested in CR, and discovering research trends and hot topics in CR, which can offer some guidance for more extensive and in-depth CR-related studies in the future.

A Narrative Review of Factors Historically Influencing Telehealth Use across Six Medical Specialties in the United States

Prior to the COVID-19 pandemic, studies in the US have identified wide variations in telehealth use across medical specialties. This is an intriguing problem, because the US has historically lacked a standardized set of telehealth coverage and reimbursement policies, which has posed a barrier to telehealth use across all specialties. Although all medical specialties in the US have been affected by these macro (policy-level) barriers, some specialties have been able to integrate telehealth use into mainstream practice, while others are just gaining momentum with telehealth during COVID-19. Although the temporary removal of policy (coverage) restrictions during the pandemic has accelerated telehealth use, uncertainties remain regarding future telehealth sustainability. Since macro (policy-level) factors by themselves do not serve to explain the variation in telehealth use across specialties, it would be important to examine meso (organizational-level) and micro (individual-level) factors historically influencing telehealth use across specialties, to understand underlying reasons for variation and identify implications for widespread sustainability. This paper draws upon the existing literature to develop a conceptual framework on macro-meso-micro factors influencing telehealth use within a medical specialty. The framework is then used to guide a narrative review of the telehealth literature across six medical specialties, including three specialties with lower telehealth use (allergy-immunology, family medicine, gastroenterology) and three with higher telehealth use (psychiatry, cardiology, radiology) in the US, in order to synthesize themes and gain insights into barriers and facilitators to telehealth use. In doing so, this review addresses a gap in the literature and provides a foundation for future research. Importantly, it helps to identify implications for ensuring widespread sustainability of telehealth use in the post-pandemic future.

A Blockchain-Enabled Framework for mHealth Systems

Presently modern technology makes a significant contribution to the transition from traditional healthcare to smart healthcare systems. Mobile health (mHealth) uses advances in wearable sensors, telecommunications and the Internet of Things (IoT) to propose a new healthcare concept centered on the patient. Patients' real-time remote continuous health monitoring, remote diagnosis, treatment, and therapy is possible in an mHealth system. However, major limitations include the transparency, security, and privacy of health data. One possible solution to this is the use of blockchain technologies, which have found numerous applications in the healthcare domain mainly due to theirs features such as decentralization (no central authority is needed), immutability, traceability, and transparency. We propose an mHealth system that uses a private blockchain based on the Ethereum platform, where wearable sensors can communicate with a smart device (a smartphone or smart tablet) that uses a peer-to-peer hypermedia protocol, the InterPlanetary File System (IPFS), for the distributed storage of health-related data. Smart contracts are used to create data queries, to access patient data by healthcare providers, to record diagnostic, treatment, and therapy, and to send alerts to patients and medical professionals.

The Vagal Autonomic Pathway of COVID-19 at the Crossroad of Alzheimer's Disease and Aging: A Review of Knowledge

Coronavirus Disease 2019 (COVID-19) pandemic-triggered mortality is significantly higher in older than in younger populations worldwide. Alzheimer's disease (AD) is related to aging and was recently reported to be among the major risk factors for COVID-19 mortality in older people. The symptomatology of COVID-19 indicates that lethal outcomes of infection rely on neurogenic mechanisms. The present review compiles the available knowledge pointing to the convergence of COVID-19 complications with the mechanisms of autonomic dysfunctions in AD and aging. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is prone to neuroinvasion from the lung along the vagus nerve up to the brainstem autonomic nervous centers involved in the coupling of cardiovascular and respiratory rhythms. The brainstem autonomic network allows SARS-CoV-2 to trigger a neurogenic switch to hypertension and hypoventilation, which may act in synergy with aging- and AD-induced dysautonomias, along with an inflammatory "storm". The lethal outcomes of COVID-19, like in AD and unhealthy aging, likely rely on a critical hypoactivity of the efferent vagus nerve cholinergic pathway, which is involved in lowering cardiovascular pressure and systemic inflammation tone. We further discuss the emerging evidence supporting the use of 1) the non-invasive stimulation of vagus nerve as an additional therapeutic approach for severe COVID-19, and 2) the demonstrated vagal tone index, i.e., heart rate variability, via smartphone-based applications as a non-serological low-cost diagnostic of COVID-19. These two well-known medical approaches are already available and now deserve large-scale testing on human cohorts in the context of both AD and COVID-19.

Intelligent Rehabilitation Assistance Tools for Distal Radius Fracture: A Systematic Review Based on Literatures and Mobile Application Stores

Objective

To systematically analyze the existing intelligent rehabilitation mobile applications (APPs) related to distal radius fracture (DRF) and evaluate their features and characteristics, so as to help doctors and patients to make evidence-based choice for appropriate intelligent-assisted rehabilitation.

Methods

Literatures which in regard to the intelligent rehabilitation tools of DRF were systematic retrieved from the PubMed, the Cochrane library, Wan Fang, and VIP Data. The effective APPs were systematically screened out through the APP markets of iOS and Android mobile platform, and the functional characteristics of different APPs were evaluated and analyzed.

Results

A total of 8 literatures and 31 APPs were included, which were divided into four categories: intelligent intervention, angle measurement, intelligent monitoring, and auxiliary rehabilitation games. These APPs provide support for the patients' home rehabilitation guidance and training and make up for the high cost and space limitations of traditional rehabilitation methods. The intelligent intervention category has the largest download ratio in the APP market. Angle measurement tools help DRF patients to measure the joint angle autonomously to judge the degree of rehabilitation, which is the most concentrated type of literature research. Some of the APPs and tools have obtained good clinical verification. However, due to the restrictions of cost, geographic authority, and applicable population, a large number of APPs still lack effective evidence to support popularization.

Conclusion

Patients with DRF could draw support from different kinds of APPs in order to fulfill personal need and promote self-management. Intelligent rehabilitation APPs play a positive role in the rehabilitation of patients, but the acceptance of the utilization for intelligent rehabilitation APPs is relatively low, which might need follow-up research to address the conundrum.