Changes in Intrapersonal Factors of Participants in the Pregnancy Remote Monitoring Study Who Are at Risk for Pregnancy-Induced Hypertension: Descriptive Quantitative Study.

BACKGROUND: The peripartum period, defined as the period from the beginning of the gestation until 1 year after the delivery, has long been shown to be potentially associated with increased levels of stress and anxiety with regard to one's transition to the status of parent and the accompanying parental tasks. Yet, no research to date has investigated changes in intrapersonal factors during the peripartum period in women at risk for pregnancy-induced hypertension (PIH). OBJECTIVE: The aim of this study is to explore and describe changes in intrapersonal factors in participants at risk for PIH. METHODS: We used an explorative design in which 3 questionnaires were sent by email to 110 participants the day following enrollment in the Pregnancy Remote Monitoring program for pregnant women at risk for PIH. Women were invited to complete the questionnaires at the beginning of their participation in the Pregnancy Remote Monitoring project (mostly at 14 weeks of gestation) and after approaching 32 weeks of gestational age (GA). The Generalized Anxiety Disorder-7 Scale (GAD-7) and the Patient Health Questionnaire-9 were used to assess anxiety and depression, and adaptation of the Pain Catastrophizing Scale was used to measure trait pain catastrophizing. RESULTS: Scores were significantly higher at 32 weeks of GA than at the moment of enrollment (GAD-7 score=7, range 4-11 vs 5, range 3-8; P=.01; and Patient Health Questionnaire-9 score=6, range 4-10 vs 4, range 2-7; P<.001). The subscale scores of the Pain Catastrophizing Scale were all lower at 32 weeks of GA compared with 14 weeks of GA (rumination: 4, range 1-6 vs 5, range 2-9.5; P=.11; magnification: 3, range 1-5.5 vs 4, range 3-7; P=.04; and helplessness: 5, range 2-9 vs 6, range 3.5-12; P=.06). The proportion of women with a risk for depression (GAD-7 score >10) was 13.3% (10/75) at enrollment and had increased to 35.6% (26/75) at 32 weeks of GA. CONCLUSIONS: This study shows that pregnant women at risk for PIH have higher levels of stress and anxiety at 32 weeks of GA than at the moment of enrollment. Further research is recommended to investigate potential strategies to help pregnant women at risk for PIH manage feelings of stress and anxiety. TRIAL REGISTRATION: ClinicalTrials.gov NCT03246737; https://clinicaltrials.gov/study/NCT03246737.

A Home Hospitalisation Strategy for Patients with an Acute Episode of Heart Failure Using a Digital Health-Supported Platform: A Multicentre Feasibility Study - A Rationale and Study Design.

BACKGROUND: Heart failure (HF) is a common cause of hospitalisation and mortality in elderly. The frequent rehospitalisations put a serious burden on patients, health-care budgets, and health-care capacity. Frequent hospital admissions are also associated with a substantial additional hazard for serious complications and reduced quality of life. The NWE-Chance project will explore the feasibility and scalability of providing home hospitalisation supported by a newly developed digital health-supported platform and daily visits of specialised nurses. METHODS/DESIGN: Hundred patients with chronic HF will be recruited over a 1-year period. The digital health-supported home hospitalisation strategy will be tested in 3 hospitals with different experience in delivering home hospitalisation: Isala Zwolle, Maastricht UMC+, both in The Netherlands, and Jessa Hospital, Hasselt in Belgium. The home hospitalisation intervention will have a maximal duration of 14 days. Feasibility will be measured with acceptability, satisfaction, and usability questionnaires for patients, nurses, and physicians. Furthermore, safety and costs will be assessed for 30 days after the start of the home hospitalisation intervention. DISCUSSION: The NWE-Chance project will be one of the first studies to examine the feasibility of a digital health-supported home hospitalisation platform for HF patients. It has the potential to augment current standard HF care and quality of life of HF patients and to innovate the standard HF care to potentially lower the hospitalisation-related complications, the burden of HF on health-care systems, and to potentially implement more patient-centred care strategies.

Towards the Monitoring of Functional Status in a Free-Living Environment for People with Hip or Knee Osteoarthritis: Design and Evaluation of the JOLO Blended Care App.

(1) Background: Joint loading is an important parameter in patients with osteoarthritis (OA). However, calculating joint loading relies on the performance of an extensive biomechanical analysis, which is not possible to do in a free-living situation. We propose the concept and design of a novel blended-care app called JOLO (Joint Load) that combines free-living information on activity with lab-based measures of joint loading in order to estimate a subject's functional status. (2) Method: We used an iterative design process to evaluate the usability of the JOLO app through questionnaires. The user interfaces that resulted from the iterations are described and provide a concept for feedback on functional status. (3) Results: In total, 44 people (20 people with OA and 24 health-care providers) participated in the testing of the JOLO app. OA patients rated the latest version of the JOLO app as moderately useful. Therapists were predominantly positive; however, their intention to use JOLO was low due to technological issues. (4) Conclusion: We can conclude that JOLO is promising, but further technological improvements concerning activity recognition, the development of personalized joint loading predictions and a more comfortable means to carry the device are needed to facilitate its integration as a blended-care program.

Midwives', Obstetricians', and Recently Delivered Mothers' Perceptions of Remote Monitoring for Prenatal Care: Retrospective Survey.

BACKGROUND: The Pregnancy Remote Monitoring (PREMOM) study enrolled pregnant women at increased risk of developing hypertensive disorders of pregnancy and investigated the effect of remote monitoring in addition to their prenatal follow-up. OBJECTIVE: The objective of this study was to investigate the perceptions and experiences of remote monitoring among mothers, midwives, and obstetricians who participated in the PREMOM study. METHODS: We developed specific questionnaires for the mothers, midwives, and obstetricians addressing 5 domains: (1) prior knowledge and experience of remote monitoring, (2) reactions to abnormal values, (3) privacy, (4) quality and patient safety, and (5) financial aspects. We also questioned the health care providers about which issues they considered important when implementing remote monitoring. We used a 5-point Likert scale to provide objective scores. It was possible to add free-text feedback at every question. RESULTS: A total of 91 participants completed the questionnaires. The mothers, midwives, and obstetricians reported positive experiences and perceptions of remote monitoring, although most of them had no or little prior experience with this technology. They supported a further rollout of remote monitoring in Belgium. Nearly three-quarters of the mothers (34/47, 72%) did not report any problems with taking the measurements at the required times. Almost half of the mothers (19/47, 40%) wanted to be contacted within 3 to 12 hours after abnormal measurement values, preferably by telephone. CONCLUSIONS: Although most of midwives and obstetricians had no or very little experience with remote monitoring before enrolling in the PREMOM study, they reported, based on their one-year experience, that remote monitoring was an important component in the follow-up of high-risk pregnancies and would recommend it to their colleagues and pregnant patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT03246737; https://clinicaltrials.gov/ct2/show/NCT03246737 (Archived by WebCite at http://www.webcitation.org/76KVnHSYY).

A Prenatal Remote Monitoring Program in Pregnancies Complicated with Gestational Hypertensive Disorders: What Are the Contributors to the Cost Savings?

Background: In 2015, we performed a cost analysis of a prenatal remote monitoring (RM) program compared with conventional care (CC) for women diagnosed with gestational hypertensive disorders (GHD). Introduction: We investigated where the cost savings were distributed by dividing our patient population into three subgroups, according to the gestational age (GA) at the time of delivery: (1) <34 weeks; (2) 34-37 weeks; and (3) >37 weeks of GA. Materials and Methods: Health care costs were calculated from patient-specific hospital bills at Ziekenhuis Oost Limburg (Genk, Belgium) in 2015-2016. Cost comparisons were made from the perspectives of the Belgium national health care system (HCS), the National Institution for Insurance of Disease and Disability (RIZIV), and the costs to individual patients. Results: A total of 256 pregnant women were included, 80 (31.25%) of whom received RM and 176 (68.75%) of whom received CC. The greatest difference in costs between RM and CC was in the group that delivered before 34 weeks of GA, followed by the group who delivered after 37 weeks of GA, and then the group of women who delivered at 34-37 weeks of GA. Most of the cost savings were in neonatal care, for both the three separate study subgroups and the total study group. Discussion and Conclusion: Our data showed that RM is more cost-effective than CC for pregnant women with GHD. Further investigation of the effects of RM on the long-term economic and social costs is recommended, together with an analysis of the price that should be asked for RM services.

Prenatal Remote Monitoring of Women With Gestational Hypertensive Diseases: Cost Analysis.

BACKGROUND: Remote monitoring in obstetrics is relatively new; some studies have shown its effectiveness for both mother and child. However, few studies have evaluated the economic impact compared to conventional care, and no cost analysis of a remote monitoring prenatal follow-up program for women diagnosed with gestational hypertensive diseases (GHD) has been published. OBJECTIVE: The aim of this study was to assess the costs of remote monitoring versus conventional care relative to reported benefits. METHODS: Patient data from the Pregnancy Remote Monitoring (PREMOM) study were used. Health care costs were calculated from patient-specific hospital bills of Ziekenhuis Oost-Limburg (Genk, Belgium) in 2015. Cost comparison was made from three perspectives: the Belgian national health care system (HCS), the National Institution for Insurance of Disease and Disability (RIZIV), and costs for individual patients. The calculations were made for four major domains: prenatal follow-up, prenatal admission to the hospital, maternal and neonatal care at and after delivery, and total amount of costs. A simulation exercise was made in which it was calculated how much could be demanded of RIZIV for funding the remote monitoring service. RESULTS: A total of 140 pregnancies were included, of which 43 received remote monitoring (30.7%) and 97 received conventional care (69.2%). From the three perspectives, there were no differences in costs for prenatal follow-up. Compared to conventional care, remote monitoring patients had 34.51% less HCS and 41.72% less RIZIV costs for laboratory test results (HCS: mean €0.00 [SD €55.34] vs mean €38.28 [SD € 44.08], P<.001; RIZIV: mean €21.09 [SD €27.94] vs mean €36.19 [SD €41.36], P<.001) and a reduction of 47.16% in HCS and 48.19% in RIZIV costs for neonatal care (HCS: mean €989.66 [SD €3020.22] vs mean €1872.92 [SD €5058.31], P<.001; RIZIV: mean €872.97 [SD €2761.64] vs mean €1684.86 [SD €4702.20], P<.001). HCS costs for medication were 1.92% lower in remote monitoring than conventional care (mean €209.22 [SD €213.32] vs mean €231.32 [SD 67.09], P=.02), but were 0.69% higher for RIZIV (mean €122.60 [SD €92.02] vs mean €121.78 [SD €20.77], P<.001). Overall HCS costs for remote monitoring were mean €4233.31 (SD €3463.31) per person and mean €4973.69 (SD €5219.00) per person for conventional care (P=.82), a reduction of €740.38 (14.89%) per person, with savings mainly for RIZIV of €848.97 per person (23.18%; mean €2797.42 [SD €2905.18] vs mean €3646.39 [SD €4878.47], P=.19). When an additional fee of €525.07 per month per pregnant woman for funding remote monitoring costs is demanded, remote monitoring is acceptable in their costs for HCS, RIZIV, and individual patients. CONCLUSIONS: In the current organization of Belgian health care, a remote monitoring prenatal follow-up of women with GHD is cost saving for the global health care system, mainly via savings for the insurance institution RIZIV.

Protocol-driven remote monitoring of cardiac resynchronization therapy as part of a heart failure disease management strategy.

BACKGROUND: Cardiac resynchronisation therapy (CRT) is an established treatment for heart failure (HF) with reduced ejection fraction. CRT devices are equipped with remote monitoring functions, which are pivotal in the detection of device problems, but may also facilitate disease management. The aim of this study was to provide a comprehensive overview of the clinical interventions taken based on remote monitoring. METHODS: This is a single centre observational study of consecutive CRT patients (n = 192) participating in protocol-driven remote follow-up. Incoming technical- and disease-related alerts were analysed together with subsequently triggered interventions. RESULTS: During 34 ± 13 months of follow-up, 1372 alert-containing notifications were received (2.53 per patient-year of follow-up), comprising 1696 unique alerts (3.12 per patient-year of follow-up). In 60%, notifications resulted in a phone contact. Technical alerts constituted 8% of incoming alerts (0.23 per patient-year of follow-up). Rhythm (1.43 per patient-year of follow-up) and bioimpedance alerts (0.98 per patient-year of follow-up) were the most frequent disease-related alerts. Notifications included a rhythm alert in 39%, which triggered referral to the emergency room (4%), outpatient cardiology clinic (36%) or general practitioner (7%), or resulted in medication changes (13%). Sole bioimpedance notifications resulted in a telephone contact in 91%, which triggered outpatient evaluation in 8% versus medication changes in 10%. Clinical outcome was excellent with 97% 1-year survival. CONCLUSIONS: Remote CRT follow-up resulted in 0.23 technical- versus 2.64 disease-related alerts annually. Rhythm and bioimpedance notifications constituted the majority of incoming notifications which triggered an actual intervention in 22% and 15% of cases, respectively.

Bioimpedance Alerts from Cardiovascular Implantable Electronic Devices: Observational Study of Diagnostic Relevance and Clinical Outcomes.

BACKGROUND: The use of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) devices is expanding in the treatment of heart failure. Most of the current devices are equipped with remote monitoring functions, including bioimpedance for fluid status monitoring. The question remains whether bioimpedance measurements positively impact clinical outcome. OBJECTIVE: The aim of this study was to provide a comprehensive overview of the clinical interventions taken based on remote bioimpedance monitoring alerts and their impact on clinical outcome. METHODS: This is a single-center observational study of consecutive ICD and CRT patients (n=282) participating in protocol-driven remote follow-up. Bioimpedance alerts were analyzed with subsequently triggered interventions. RESULTS: A total of 55.0% (155/282) of patients had an ICD or CRT device equipped with a remote bioimpedance algorithm. During 34 (SD 12) months of follow-up, 1751 remote monitoring alarm notifications were received (2.2 per patient-year of follow-up), comprising 2096 unique alerts (2.6 per patient-year of follow-up). Since 591 (28.2%) of all incoming alerts were bioimpedance-related, patients with an ICD or CRT including a bioimpedance algorithm had significantly more alerts (3.4 versus 1.8 alerts per patient-year of follow-up, P<.001). Bioimpedance-only alerts resulted in a phone contact in 91.0% (498/547) of cases, which triggered an actual intervention in 15.9% (87/547) of cases, since in 75.1% (411/547) of cases reenforcing heart failure education sufficed. Overall survival was lower in patients with a cardiovascular implantable electronic device with a bioimpedance algorithm; however, this difference was driven by differences in baseline characteristics (adjusted hazard ratio of 2.118, 95% CI 0.845-5.791). No significant differences between both groups were observed in terms of the number of follow-up visits in the outpatient heart failure clinic, the number of hospital admissions with a primary diagnosis of heart failure, or mean length of hospital stay. CONCLUSIONS: Bioimpedance-only alerts constituted a substantial amount of incoming alerts when turned on during remote follow-up and triggered an additional intervention in only 16% of cases since in 75% of cases, providing general heart failure education sufficed. The high frequency of heart failure education that was provided could have contributed to fewer heart failure-related hospitalizations despite significant differences in baseline characteristics.

MotifSuite: workflow for probabilistic motif detection and assessment.

MOTIVATION: Probabilistic motif detection requires a multi-step approach going from the actual de novo regulatory motif finding up to a tedious assessment of the predicted motifs. MotifSuite, a user-friendly web interface streamlines this analysis flow. Its core consists of two post-processing procedures that allow prioritizing the motif detection output. The tools offered by MotifSuite are built around the well-established motif detection tool MotifSampler and can also be used in combination with any other probabilistic motif detection tool. Elaborate guidelines on each of its applications have been provided. AVAILABILITY: http://homes.esat.kuleuven.be/bioi_marchal/MotifSuite/Index.htm

Adherence to inhaled antibiotics in people with cystic fibrosis: insights from a virtual patient advisory board.

BACKGROUND: Chronic airway infection by Pseudomonas aeruginosa significantly impacts the health of people with cystic fibrosis (PwCF), presenting complex treatment challenges. RESEARCH DESIGN AND METHODS: To gain insights into PwCF's experiences, a virtual European Patient Advisory Board was convened. Board explored inhaled antibiotic usage, treatment adherence, and associated challenges. Additionally, an online survey was conducted among PwCF to further understand real-life experiences and unmet needs, particularly related to CFTR modulators. RESULTS: The Advisory Board proved instrumental in collecting valuable real-world perspectives, offering potential avenues for reshaping the care model for complex diseases like cystic fibrosis. CONCLUSIONS: PwCF on CFTR modulators are questioning the necessity of continuing chronic medications and therapies. Physicians are urged to carefully consider the balance between simplifying antibiotic treatment and the risk of clinical deterioration due to bacterial infections when making treatment decisions. Furthermore, the development and global harmonization of diagnostic tools for chronic lung damage and treatment guidelines are crucial to justify the demanding routines that PwCF must endure to manage their condition.The heterogeneity in patient journeys, diagnostic challenges, treatment complexity, and issues related to adherence highlight the need for patient-centric, personalized care that emphasizes improving and maintaining treatment adherence to optimize cystic fibrosis management.

Query-based biclustering of gene expression data using Probabilistic Relational Models.

BACKGROUND: With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set. RESULTS: We applied ProBic on a large scale Escherichia coli compendium to extend partially described regulons with potentially novel members. We compared ProBic's performance with previously published query-based biclustering algorithms, namely ISA and QDB, from the perspective of bicluster expression quality, robustness of the outcome against noisy seed sets and biological relevance.This comparison learns that ProBic is able to retrieve biologically relevant, high quality biclusters that retain their seed genes and that it is particularly strong in handling noisy seeds. CONCLUSIONS: ProBic is a query-based biclustering algorithm developed in a flexible framework, designed to detect biologically relevant, high quality biclusters that retain relevant seed genes even in the presence of noise or when dealing with low quality seed sets.

Factors for severe outcomes following SARS-CoV-2 infection in people with cystic fibrosis in Europe.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in people with cystic fibrosis (pwCF) can lead to severe outcomes. METHODS: In this observational study, the European Cystic Fibrosis Society Patient Registry collected data on pwCF and SARS-CoV-2 infection to estimate incidence, describe clinical presentation and investigate factors associated with severe outcomes using multivariable analysis. RESULTS: Up to December 31, 2020, 26 countries reported information on 828 pwCF and SARS-CoV-2 infection. Incidence was 17.2 per 1000 pwCF (95% CI: 16.0-18.4). Median age was 24 years, 48.4% were male and 9.4% had lung transplants. SARS-CoV-2 incidence was higher in lung-transplanted (28.6; 95% CI: 22.7-35.5) versus non-lung-transplanted pwCF (16.6; 95% CI: 15.4-17.8) (p≤0.001).SARS-CoV-2 infection caused symptomatic illness in 75.7%. Factors associated with symptomatic SARS-CoV-2 infection were age >40 years, at least one F508del mutation and pancreatic insufficiency.Overall, 23.7% of pwCF were admitted to hospital, 2.5% of those to intensive care, and regretfully 11 (1.4%) died. Hospitalisation, oxygen therapy, intensive care, respiratory support and death were 2- to 6-fold more frequent in lung-transplanted versus non-lung-transplanted pwCF.Factors associated with hospitalisation and oxygen therapy were lung transplantation, cystic fibrosis-related diabetes (CFRD), moderate or severe lung disease and azithromycin use (often considered a surrogate marker for Pseudomonas aeruginosa infection and poorer lung function). CONCLUSION: SARS-CoV-2 infection yielded high morbidity and hospitalisation in pwCF. PwCF with forced expiratory volume in 1 s <70% predicted, CFRD and those with lung transplants are at particular risk of more severe outcomes.

ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules.

BACKGROUND: The detection of cis-regulatory modules (CRMs) that mediate transcriptional responses in eukaryotes remains a key challenge in the postgenomic era. A CRM is characterized by a set of co-occurring transcription factor binding sites (TFBS). In silico methods have been developed to search for CRMs by determining the combination of TFBS that are statistically overrepresented in a certain geneset. Most of these methods solve this combinatorial problem by relying on computational intensive optimization methods. As a result their usage is limited to finding CRMs in small datasets (containing a few genes only) and using binding sites for a restricted number of transcription factors (TFs) out of which the optimal module will be selected. RESULTS: We present an itemset mining based strategy for computationally detecting cis-regulatory modules (CRMs) in a set of genes. We tested our method by applying it on a large benchmark data set, derived from a ChIP-Chip analysis and compared its performance with other well known cis-regulatory module detection tools. CONCLUSION: We show that by exploiting the computational efficiency of an itemset mining approach and combining it with a well-designed statistical scoring scheme, we were able to prioritize the biologically valid CRMs in a large set of coregulated genes using binding sites for a large number of potential TFs as input.

Relationship Between Adherence to Remote Monitoring and Patient Characteristics: Observational Study in Women With Pregnancy-Induced Hypertension.

BACKGROUND: Pregnancy-induced hypertension (PIH) is associated with high levels of morbidity and mortality in mothers, fetuses, and newborns. New technologies, such as remote monitoring (RM), were introduced in 2015 into the care of patients at risk of PIH in Ziekenhuis Oost-Limburg (Genk, Belgium) to improve both maternal and neonatal outcomes. In developing new strategies for obstetric care in pregnant women, including RM, it is important to understand the psychosocial characteristics associated with adherence to RM to optimize care. OBJECTIVE: The aim of this study was to explore the role of patients' psychosocial characteristics (severity of depression or anxiety, cognitive factors, attachment styles, and personality traits) in their adherence to RM. METHODS: Questionnaires were sent by email to 108 mothers the day after they entered an RM program for pregnant women at risk of PIH. The Generalized Anxiety Disorder Assessment-7 and Patient Health Questionnaire-9 (PHQ-9) were used to assess anxiety and the severity of depression, respectively; an adaptation of the Pain Catastrophizing Scale was used to assess cognitive factors; and attachment and personality were measured with the Experiences in Close Relationships-Revised Scale (ECR-R), the Depressive Experiences Questionnaire, and the Multidimensional Perfectionism Scale, respectively. RESULTS: The moderate adherence group showed significantly higher levels of anxiety and depression, negative cognitions, and insecure attachment styles, especially compared with the over adherence group. The low adherence group scored significantly higher than the other groups on other-oriented perfectionism. There were no significant differences between the good and over adherence groups. Single linear regression showed that the answers on the PHQ-9 and ECR-R questionnaires were significantly related to the adherence rate. CONCLUSIONS: This study demonstrates the relationships between adherence to RM and patient characteristics in women at risk of PIH. Alertness toward the group of women who show less than optimal adherence is essential. These findings call for further research on the management of PIH and the importance of individual tailoring of RM in this patient group. TRIAL REGISTRATION: ClinicalTrials.gov NCT03509272; https://clinicaltrials.gov/ct2/show/NCT03509272.

A Vendor-Independent Mobile Health Monitoring Platform for Digital Health Studies: Development and Usability Study.

BACKGROUND: Medical smartphone apps and mobile health devices are rapidly entering mainstream use because of the rising number of smartphone users. Consequently, a large amount of consumer-generated data is being collected. Technological advances in innovative sensory systems have enabled data connectivity and aggregation to become cornerstones in developing workable solutions for remote monitoring systems in clinical practice. However, few systems are currently available to handle such data, especially for clinical use. OBJECTIVE: The aim of this study was to develop and implement the digital health research platform for mobile health (DHARMA) that combines data saved in different formats from a variety of sources into a single integrated digital platform suitable for mobile remote monitoring studies. METHODS: DHARMA comprises a smartphone app, a Web-based platform, and custom middleware and has been developed to collect, store, process, and visualize data from different vendor-specific sensors. The middleware is a component-based system with independent building blocks for user authentication, study and patient administration, data handling, questionnaire management, patient files, and reporting. RESULTS: A prototype version of the research platform has been tested and deployed in multiple clinical studies. In this study, we used the platform for the follow-up of pregnant women at risk of developing pre-eclampsia. The patients' blood pressure, weight, and activity were semi-automatically captured at home using different devices. DHARMA automatically collected and stored data from each source and enabled data processing for the end users in terms of study-specific parameters, thresholds, and visualization. CONCLUSIONS: The increasing use of mobile health apps and connected medical devices is leading to a large amount of data for collection. There has been limited investment in handling and aggregating data from different sources for use in academic and clinical research focusing on remote monitoring studies. In this study, we created a modular mobile health research platform to collect and integrate data from a variety of third-party devices in several patient populations. The functionality of the platform was demonstrated in a real-life setting among women with high-risk pregnancies.

The impact of a remote monitoring program on the prenatal follow-up of women with gestational hypertensive disorders.

OBJECTIVES: In 2015, we showed the value of a remote monitoring (RM) follow-up program for women diagnosed with gestational hypertensive disorders (GHDs) compared with women who received conventional care (CC). We want to confirm or refute the conclusions drawn in 2015, by including data from 2016. STUDY DESIGN: A two year retrospective study in which all women diagnosed with GHD, who underwent prenatal follow-up at the outpatients prenatal clinic of Ziekenhuis Oost-Limburg (Genk, Belgium) during 2015 and 2016, were included. Of the 320 women diagnosed with GHD, ninety (28.13%) were monitored with RM. The other 230 (71.88%) GHD pregnancies were monitored with CC. Differences in continuous and categorical variables in maternal demographics and characteristics were tested using Unpaired Student's two sampled t-test or Mann Whitney U test and the c2 test. Both a univariate and multivariate analysis were performed for analyzing prenatal follow up and gestational outcomes. All statistical analyses are done at nominal level a = 0.05. RESULTS: The RM group had more women diagnosed with gestational hypertension but less with pre-eclampsia when compared to the CC group (69.77% versus 42.79% and 19.77% versus 44.19% respectively). In both uni- and multivariate analyses, the RM group had, when compared to the CC group, less prenatal admission (51.62% versus 71.63%), less prenatal admissions until the moment of the delivery (31.40% versus 57.67%), less induced starts of the birth process (43.00% versus 32.09%), more spontaneous starts of the birth process (32.86% versus 46.51%), more births after 37 weeks of gestational age in pregnancies complicated with gestational hypertension (91.67% versus 53.33%) and pregnancies complicated with pre-eclampsia (58.82% versus 53.33%). In multivariate analysis, a reduction in total number of prenatal visits was visible in the RM group when compared to the CC group (b = -1.76; CI = -2.74-0.77). Only in the univariate analysis was the mean gestational age at delivery between 34 and 37 weeks of gestation in pregnancies complicated with gestational hypertension higher in the CC group versus the RM group (35 w 4/7 (±0.49) versus 34 w 6/7 (±0.00).These conclusions were almost the same as in the analyses of 2015, except (1) there wasn't a difference anymore in NICU admissions between the RM and CC group in the analyses of 2015-2016 and (2) a significant decrease in total number of visits is reported in the RM group in the dataset of 2015-2016, which wasn't visible in the dataset of 2015. CONCLUSIONS: This study demonstrates that RM provides opportunities to offer timely interventions to pregnant women who require them.

A Novel Intelligent Two-Way Communication System for Remote Heart Failure Medication Uptitration (the CardioCoach Study): Randomized Controlled Feasibility Trial.

BACKGROUND: European Society of Cardiology guidelines for the treatment of heart failure (HF) prescribe uptitration of angiotensin-converting enzyme inhibitors (ACE-I) and ß-blockers to the maximum-tolerated, evidence-based dose. Although HF prognosis can drastically improve when correctly implementing these guidelines, studies have shown that they are insufficiently implemented in clinical practice. OBJECTIVE: The aim of this study was to verify whether supplementing the usual care with the CardioCoach follow-up tool is feasible and safe, and whether the tool is more efficient in implementing the guideline recommendations for ß-blocker and ACE-I. METHODS: A total of 25 HF patients were randomly assigned to either the usual care control group (n=10) or CardioCoach intervention group (n=15), and observed for 6 months. The CardioCoach follow-up tool is a two-way communication platform with decision support algorithms for semiautomatic remote medication uptitration. Remote monitoring sensors automatically transmit patient's blood pressure, heart rate, and weight on a daily basis. RESULTS: Patients' satisfaction and adherence for medication intake (10,018/10,825, 92.55%) and vital sign measurements (4504/4758, 94.66%) were excellent. However, the number of technical issues that arose was large, with 831 phone contacts (median 41, IQR 32-65) in total. The semiautomatic remote uptitration was safe, as there were no adverse events and no false positive uptitration proposals. Although no significant differences were found between both groups, a higher number of patients were on guideline-recommended medication dose in both groups compared with previous reports. CONCLUSIONS: The CardioCoach follow-up tool for remote uptitration is feasible and safe and was found to be efficient in facilitating information exchange between care providers, with high patient satisfaction and adherence. TRIAL REGISTRATION: ClinicalTrials.gov NCT03294811; https://clinicaltrials.gov/ct2/show/NCT03294811 (Archived by WebCite at http://www.webcitation.org/6xLiWVsgM).

Metadata Correction: Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study.

[This corrects the article DOI: 10.2196/mhealth.7254.].

Clinical Validation of Heart Rate Apps: Mixed-Methods Evaluation Study.

BACKGROUND: Photoplethysmography (PPG) is a proven way to measure heart rate (HR). This technology is already available in smartphones, which allows measuring HR only by using the smartphone. Given the widespread availability of smartphones, this creates a scalable way to enable mobile HR monitoring. An essential precondition is that these technologies are as reliable and accurate as the current clinical (gold) standards. At this moment, there is no consensus on a gold standard method for the validation of HR apps. This results in different validation processes that do not always reflect the veracious outcome of comparison. OBJECTIVE: The aim of this paper was to investigate and describe the necessary elements in validating and comparing HR apps versus standard technology. METHODS: The FibriCheck (Qompium) app was used in two separate prospective nonrandomized studies. In the first study, the HR of the FibriCheck app was consecutively compared with 2 different Food and Drug Administration (FDA)-cleared HR devices: the Nonin oximeter and the AliveCor Mobile ECG. In the second study, a next step in validation was performed by comparing the beat-to-beat intervals of the FibriCheck app to a synchronized ECG recording. RESULTS: In the first study, the HR (BPM, beats per minute) of 88 random subjects consecutively measured with the 3 devices showed a correlation coefficient of .834 between FibriCheck and Nonin, .88 between FibriCheck and AliveCor, and .897 between Nonin and AliveCor. A single way analysis of variance (ANOVA; P=.61 was executed to test the hypothesis that there were no significant differences between the HRs as measured by the 3 devices. In the second study, 20,298 (ms) R-R intervals (RRI)-peak-to-peak intervals (PPI) from 229 subjects were analyzed. This resulted in a positive correlation (rs=.993, root mean square deviation [RMSE]=23.04 ms, and normalized root mean square error [NRMSE]=0.012) between the PPI from FibriCheck and the RRI from the wearable ECG. There was no significant difference (P=.92) between these intervals. CONCLUSIONS: Our findings suggest that the most suitable method for the validation of an HR app is a simultaneous measurement of the HR by the smartphone app and an ECG system, compared on the basis of beat-to-beat analysis. This approach could lead to more correct assessments of the accuracy of HR apps.

Remote Monitoring of Hypertension Diseases in Pregnancy: A Pilot Study.

BACKGROUND: Although remote monitoring (RM) has proven its added value in various health care domains, little is known about the remote follow-up of pregnant women diagnosed with a gestational hypertensive disorders (GHD). OBJECTIVE: The aim of this study was to evaluate the added value of a remote follow-up program for pregnant women diagnosed with GHD. METHODS: A 1-year retrospective study was performed in the outpatient clinic of a 2nd level prenatal center where pregnant women with GHD received RM or conventional care (CC). Primary study endpoints include number of prenatal visits and admissions to the prenatal observation ward. Secondary outcomes include gestational outcome, mode of delivery, neonatal outcome, and admission to neonatal intensive care (NIC). Differences in continuous and categorical variables in maternal demographics and characteristics were tested using Unpaired Student's two sampled t test or Mann-Whitney U test and the chi-square test. Both a univariate and multivariate analysis were performed for analyzing prenatal follow-up and gestational outcomes. All statistical analyses were done at nominal level, Cronbach alpha=.05. RESULTS: Of the 166 patients diagnosed with GHD, 53 received RM and 113 CC. After excluding 5 patients in the RM group and 15 in the CC group because of the missing data, 48 patients in RM group and 98 in CC group were taken into final analysis. The RM group had more women diagnosed with gestational hypertension, but less with preeclampsia when compared with CC (81.25% vs 42.86% and 14.58% vs 43.87%). Compared with CC, univariate analysis in RM showed less induction, more spontaneous labors, and less maternal and neonatal hospitalizations (48.98% vs 25.00%; 31.63% vs 60.42%; 74.49% vs 56.25%; and 27.55% vs 10.42%). This was also true in multivariate analysis, except for hospitalizations. CONCLUSIONS: An RM follow-up of women with GHD is a promising tool in the prenatal care. It opens the perspectives to reverse the current evolution of antenatal interventions leading to more interventions and as such to ever increasing medicalized antenatal care.