Personal Glucose Meter for α-Glucosidase Inhibitor Screening Based on the Hydrolysis of Maltose.

As a key enzyme regulating postprandial blood glucose, α-Glucosidase is considered to be an effective target for the treatment of diabetes mellitus. In this study, a simple, rapid, and effective method for enzyme inhibitors screening assay was established based on α-glucosidase catalyzes reactions in a personal glucose meter (PGM). α-glucosidase catalyzes the hydrolysis of maltose to produce glucose, which triggers the reduction of ferricyanide (K3[Fe(CN)6]) to ferrocyanide (K4[Fe(CN)6]) and generates the PGM detectable signals. When the α-glucosidase inhibitor (such as acarbose) is added, the yield of glucose and the readout of PGM decreased accordingly. This method can achieve the direct determination of α-glucosidase activity by the PGM as simple as the blood glucose tests. Under the optimal experimental conditions, the developed method was applied to evaluate the inhibitory activity of thirty-four small-molecule compounds and eighteen medicinal plants extracts on α-glucosidase. The results exhibit that lithospermic acid (52.5 ± 3.0%) and protocatechualdehyde (36.8 ± 2.8%) have higher inhibitory activity than that of positive control acarbose (31.5 ± 2.5%) at the same final concentration of 5.0 mM. Besides, the lemon extract has a good inhibitory effect on α-glucosidase with a percentage of inhibition of 43.3 ± 3.5%. Finally, the binding sites and modes of four active small-molecule compounds to α-glucosidase were investigated by molecular docking analysis. These results indicate that the PGM method is feasible to screening inhibitors from natural products with simple and rapid operations.

Responsive Neurostimulation as a Novel Palliative Option in Epilepsy Surgery.

Patients with drug-resistant focal onset epilepsy are not always suitable candidates for resective surgery, a definitive intervention to control their seizures. The alternative surgical treatment for these patients in Japan has been vagus nerve stimulation (VNS). Besides VNS, epileptologists in the United States can choose a novel palliative option called responsive neurostimulation (RNS), a closed-loop neuromodulation system approved by the US Food and Drug Administration in 2013. The RNS System continuously monitors neural electroencephalography (EEG) activity at the possible seizure onset zone (SOZ) where electrodes are placed and responds with electrical stimulation when a pre-defined epileptic activity is detected. The controlled clinical trials in the United States have demonstrated long-term utility and safety of the RNS System. Seizure reduction rates have continued to improve over time, reaching 75% over 9 years of treatment. The incidence of implant-site infection, the most frequent device-related adverse event, is similar to those of other neuromodulation devices. The RNS System has shown favorable efficacy for both mesial temporal lobe epilepsy (TLE) and neocortical epilepsy of the eloquent cortex. Another unique advantage of the RNS System is its ability to provide chronic monitoring of ambulatory electrocorticography (ECoG). Valuable information obtained from ECoG monitoring provides a better understanding of the state of epilepsy in each patient and improves clinical management. This article reviews the developmental history, structure, and clinical utility of the RNS System, and discusses its indications as a novel palliative option for drug-resistant epilepsy.

A new implantable tool for repeated assessment of supraventricular electrophysiology and atrial fibrillation susceptibility in freely moving rats.

The complex pathophysiology of atrial fibrillation (AF) is governed by multiple risk factors in ways that are still elusive. Basic electrophysiological properties, including atrial effective refractory period (AERP) and conduction velocity, are major factors determining the susceptibility of the atrial myocardium to AF. Although there is a great need for affordable animal models in this field of research, in vivo rodent studies are limited by technical challenges. Recently, we introduced an implantable system for long-term assessment of AF susceptibility in ambulatory rats. However, technical considerations did not allow us to perform concomitant supraventricular electrophysiology measurements. Here, we designed a novel quadripolar electrode specifically adapted for comprehensive atrial studies in ambulatory rats. Electrodes were fabricated from medical-grade silicone, four platinum-iridium poles, and stainless-steel fixating pins. Initial quality validation was performed ex vivo, followed by implantation in adult rats and repeated electrophysiological studies 1, 4, and 8 wk postimplantation. Capture threshold was stable. Baseline AERP values (38.1 ± 2.3 and 39.5 ± 2.0 using 70-ms and 120-ms S1-S1 cycle lengths, respectively) confirmed the expected absence of rate adaptation in the unanesthetized state and validated our prediction that markedly higher values reported under anesthesia are nonphysiological. Evaluation of AF substrate in parallel with electrophysiological parameters validated our recent finding of a gradual increase in AF susceptibility over time and demonstrated that this phenomenon is associated with an electrical remodeling process characterized by AERP shortening. Our findings indicate that the miniature quadripolar electrode is a potent new tool, which opens a window of opportunities for better utilization of rats in AF research.NEW & NOTEWORTHY Rodents are increasingly used in AF research. However, technical challenges restrict long-term supraventricular electrophysiology studies in these species. Here, we developed an implantable electrode adapted for such studies in the rat. Our findings indicate that this new tool is effective for long-term follow-up of critical parameters such as atrial refractoriness. Obtained data shed light on the normal electrophysiology and on the increased AF susceptibility that develops in rats with implanted atrial electrodes over time.

Enabling Remote Patient Monitoring Through the Use of Smart Thermostat Data in Canada: Exploratory Study.

BACKGROUND: Advances in technology have made the development of remote patient monitoring possible in recent years. However, there is still room for innovation in the types of technologies that are developed, used, and implemented. The smart thermostat solutions provided in this study can expand beyond typically defined features and be used for improved holistic health monitoring purposes. OBJECTIVE: The aim of this study is to validate the hypothesis that remote motion sensors could be used to quantify and track an individual's movements around the house. On the basis of our results, the next step would be to determine if using remote motion sensors could be a novel data collection method compared with the national census-level surveys administered by governmental bodies. The results will be used to inform a more extensive implementation study of similar smart home technologies to gather data for machine learning algorithms and to build upon pattern recognition and comprehensive health monitoring. METHODS: We conducted a pilot study with a sample size of 8 to validate the use of remote motion sensors to quantify movement in the house. A large database containing data from smart home thermostats was analyzed to compare the following indicators; sleep, physical activity, and sedentary behavior. These indicators were developed by the Public Health Agency of Canada and are collected through traditional survey methods. RESULTS: The results showed a significant Spearman rank correlation coefficient of 0.8 (P<.001), which indicates a positive linear association between the total number of sensors activated and the total number of indoor steps traveled by study participants. In addition, the indicators of sleep, physical activity, and sedentary behavior were all found to be highly comparable with those attained by the Public Health Agency of Canada. CONCLUSIONS: The findings demonstrate that remote motion sensors data from a smart thermostat solution are a viable option when compared with traditional survey data collection methods for health data collection and are also a form of zero-effort technology that can be used to monitor the activity levels and nature of activity of occupants within the home.

Expertise, experience, and excellence. Twenty years of patient involvement in health technology assessment at NICE: an evolving story.

From its inception in 1999, the National Institute for Health and Care Excellence (NICE) committed to including the expertise, experiences, and perspectives of lay people, patients and carers, and patient organizations in its health technology assessments (HTAs). This is our story of patient involvement in HTA: from early methods designed for use when assessing medicines, widening to address the different requirements of HTAs for interventional procedures, medical technologies, and diagnostic technologies. We also chart the evolution and development of all our patient involvement methods over the past 20 years through regular evaluation and by responding to external challenge. However, we know that processes and methods alone are not enough. Through case studies we demonstrate the value of patient involvement in HTA and highlight the unique perspectives and experiences that patients bring to HTA committees. Finally, we discuss the underpinning principles and commitments that have made NICE a world leader in delivering meaningful and legitimate patient involvement.

Design of the Pregnancy REmote MOnitoring II study (PREMOM II): a multicenter, randomized controlled trial of remote monitoring for gestational hypertensive disorders.

BACKGROUND: Observational data from the retrospective, non-randomized Pregnancy REmote MOnitoring I (PREMOM I) study showed that remote monitoring (RM) may be beneficial for prenatal observation of women at risk for gestational hypertensive disorders (GHD) in terms of clinical outcomes, health economics, and stakeholder perceptions. PREMOM II is a prospective, randomized, multicenter follow-up study that was performed to explore these promising results. METHODS: After providing written consent, 3922 pregnant women aged ≥18 years who are at increased risk of developing GHD will be randomized (1:1:1 ratio) to (a) conventional care (control group), (b) a patient self-monitoring group, and (c) a midwife-assisted RM group. The women in each group will be further divided (1:1 ratio) to evaluate the outcomes of targeted or non-targeted (conventional) antihypertensive medication. Women will be recruited in five hospitals in Flanders, Belgium: Ziekenhuis Oost-Limburg, Universitaire Ziekenhuis Antwerpen, Universitaire Ziekenhuis Leuven, AZ Sint Jan Brugge-Oostende, and AZ Sint Lucas Brugge. The primary outcomes are: (1) numbers and types of prenatal visits; (2) maternal outcomes; (3) neonatal outcomes; (4) the applicability and performance of RM; and (5) compliance with RM and self-monitoring. The secondary outcomes are: (1) cost-effectiveness and willingness to pay; (2) patient-reported outcome measures (PROMS) questionnaires on the experiences of the participants; and (3) the maternal and perinatal outcomes according to the type of antihypertensive medication. Demographic, and maternal and neonatal outcomes are collected from the patients' electronic records. Blood pressure and compliance rate will be obtained from an online digital coordination platform for remote data handling. Information about the healthcare-related costs will be obtained from the National Coordination Committee of Belgian Health Insurance Companies (Intermutualistisch Agentschap). PROMS will be assessed using validated questionnaires. DISCUSSION: To our knowledge, this is the first randomized trial comparing midwife-assisted RM and self-monitoring of prenatal blood pressure versus conventional management among women at increased risk of GHD. Positive results of this study may lead to a practical framework for caregivers, hospital management, and payers to introduce RM into the prenatal care programs of high-risk pregnancies. TRIAL REGISTRATION: This study was registered on clinicaltrials.gov , identification number NCT04031430. Registered 24 July 2019, https://clinicaltrials.gov/ct2/show/NCT04031430?cond=premom+ii&draw=2&rank=1 .

Effect of novel technology-enabled multidimensional physical activity feedback in primary care patients at risk of chronic disease - the MIPACT study: a randomised controlled trial.

BACKGROUND: Technological progress has enabled the provision of personalised feedback across multiple dimensions of physical activity that are important for health. Whether this multidimensional approach supports physical activity behaviour change has not yet been examined. Our objective was to examine the effectiveness of a novel digital system and app that provided multidimensional physical activity feedback combined with health trainer support in primary care patients identified as at risk of chronic disease. METHODS: MIPACT was a parallel-group, randomised controlled trial that recruited patients at medium (≥10 and < 20%) or high (≥20%) risk of cardiovascular disease and/or type II diabetes from six primary care practices in the United Kingdom. Intervention group participants (n = 120) received personal multidimensional physical activity feedback using a customised digital system and web-app for 3 months plus five health trainer-led sessions. All participants received standardised information regarding physical activity. Control group participants (n = 84) received no further intervention. The primary outcome was device-based assessment of physical activity at 12 months. RESULTS: Mean intervention effects were: moderate-vigorous physical activity: -1.1 (95% CI, - 17.9 to 15.7) min/day; moderate-vigorous physical activity in ≥10-min bouts: 0.2 (- 14.2 to 14.6) min/day; Physical Activity Level (PAL): 0.00 (- 0.036 to 0.054); vigorous physical activity: 1.8 (- 0.8 to 4.2) min/day; and sedentary time: 10 (- 19.3 to 39.3) min/day. For all of these outcomes, the results showed that the groups were practically equivalent and statistically ruled out meaningful positive or negative effects (>minimum clinically important difference, MCID). However, there was profound physical activity multidimensionality, and only a small proportion (5%) of patients had consistently low physical activity across all dimensions. CONCLUSION: In patients at risk of cardiovascular disease and/or type II diabetes, MIPACT did not increase mean physical activity. Using a sophisticated multidimensional digital approach revealed enormous heterogeneity in baseline physical activity in primary care patients, and practitioners may need to screen for low physical activity across dimensions rather than rely on disease-risk algorithms that are heavily influenced by age. TRIAL REGISTRATION: This trial is registered with the ISRCTN registry ( ISRCTN18008011 ; registration date 31 July 2013).

A new era in electroencephalographic monitoring? Subscalp devices for ultra-long-term recordings.

Inaccurate subjective seizure counting poses treatment and diagnostic challenges and thus suboptimal quality in epilepsy management. The limitations of existing hospital- and home-based monitoring solutions are motivating the development of minimally invasive, subscalp, implantable electroencephalography (EEG) systems with accompanying cloud-based software. This new generation of ultra-long-term brain monitoring systems is setting expectations for a sea change in the field of clinical epilepsy. From definitive diagnoses and reliable seizure logs to treatment optimization and presurgical seizure foci localization, the clinical need for continuous monitoring of brain electrophysiological activity in epilepsy patients is evident. This paper presents the converging solutions developed independently by researchers and organizations working at the forefront of next generation EEG monitoring. The immediate value of these devices is discussed as well as the potential drivers and hurdles to adoption. Additionally, this paper discusses what the expected value of ultra-long-term EEG data might be in the future with respect to alarms for especially focal seizures, seizure forecasting, and treatment personalization.

Autonomic nervous system changes detected with peripheral sensors in the setting of epileptic seizures.

A better understanding of the early detection of seizures is highly desirable as identification of an impending seizure may afford improved treatments, such as antiepileptic drug chronotherapy, or timely warning to patients. While epileptic seizures are known to often manifest also with autonomic nervous system (ANS) changes, it is not clear whether ANS markers, if recorded from a wearable device, are also informative about an impending seizure with statistically significant sensitivity and specificity. Using statistical testing with seizure surrogate data and a unique dataset of continuously recorded multi-day wristband data including electrodermal activity (EDA), temperature (TEMP) and heart rate (HR) from 66 people with epilepsy (9.9 ± 5.8 years; 27 females; 161 seizures) we investigated differences between inter- and preictal periods in terms of mean, variance, and entropy of these signals. We found that signal mean and variance do not differentiate between inter- and preictal periods in a statistically meaningful way. EDA signal entropy was found to be increased prior to seizures in a small subset of patients. Findings may provide novel insights into the pathophysiology of epileptic seizures with respect to ANS function, and, while further validation and investigation of potential causes of the observed changes are needed, indicate that epilepsy-related state changes may be detectable using peripheral wearable devices. Detection of such changes with wearable devices may be more feasible for everyday monitoring than utilizing an electroencephalogram.

Young-onset diabetes, nutritional therapy and novel insulin delivery systems: a report from the 21st Hong Kong Diabetes and Cardiovascular Risk Factors - East Meets West Symposium.

The prevalence and incidence of young-onset diabetes are increasing in many parts of the world, with the most rapid increase occurring in Asia, where one in five people with diabetes are diagnosed below the age of 40 years. Accumulation of glycaemic burden from an early age significantly increases the lifetime risks of developing complications from diabetes. Despite impending health threats, young people fare worse in the control of blood glucose and other metabolic risk factors. Challenges in the management of young-onset diabetes are compounded by heterogeneity of the underlying causes, pathophysiology and clinical phenotypes in this group. Effective characterization of people with diabetes has implications in steering the choice of glucose-lowering drugs, which, in turn, determines the clinical outcome. Medical nutritional therapy is key to effective management of people with diabetes but dietary adherence is often suboptimal among younger individuals. A recently published consensus report on nutritional therapy addresses dietary management in people with prediabetes as well as diabetes, and summarizes clinical evidence regarding macronutrient and micronutrient composition as well as eating patterns in people with diabetes. For people with type 1 diabetes, automated insulin delivery systems have rapidly evolved since the concept was first introduced at the National Institute of Health and the Juvenile Diabetes Research Foundation in 2005. The subsequent development of a type 1 diabetes simulator, developed using detailed human physiology data on carbohydrate metabolism replaced the need for pre-clinical animal studies and facilitated the seamless progression to artificial pancreas human clinical trials.

Evaluating the Impact of Freespira on Panic Disorder Patients' Health Outcomes and Healthcare Costs within the Allegheny Health Network.

Panic disorder (PD) is a debilitating condition that drives medical spending at least twice as high as medically matched controls. Excessive utilization of healthcare resources comes from emergency department (ED), medications, diagnostic testing, and physician visits. Freespira is an FDA-cleared digital therapeutic that treats PD and panic attacks (PA) by correcting underlying abnormal respiratory physiology. Efficacy of Freespira has been established in prior studies. This paper reports on a quality improvement program that investigated whether treating PD patients with Freespira would reduce medical costs and improve outcomes over 12-months. Panic symptoms were assessed using the Panic Disorder Severity Scale (PDSS). Pre-and post-treatment insurance claims determined costs. At baseline, mean Clinician Global Impression (CGI-S) was 4.4 (moderately/markedly ill), mean PDSS was 14.4 and mean PA frequency/week was 2 (range 0-5). Immediately post-treatment (week 5) mean CGI-S, PDSS and weekly PA frequency declined to 2.8 (borderline/mildly ill, 4.9 (remission) and 0.2 (range 0-2) respectively, p < 0.001. 82% reported PDSS decrease of ≥ 40% (clinically significant), 86% were PA-free. One-year post treatment mean CGI-S, PDSS and PA remained low at 2.1, 4.4, and 0.3 (range 0-1) respectively. 91% had PDSS decrease of ≥ 40%, 73% were PA-free. The majority of patients were panic attack free and/or reduced their symptoms and avoidance behaviors 1-year post Freespira treatment. Mean overall medical costs were reduced by 35% from $548 to $358 PMPM (per member per month) or an annual reduction of $2280. at 12 months post-treatment. There was a 65% reduction in ED costs from $87 to $30 PMPM. Median pharmacy costs were reduced by 68% from $73 to $23 PMPM.

Mesial temporal resection following long-term ambulatory intracranial EEG monitoring with a direct brain-responsive neurostimulation system.

OBJECTIVE: To describe seizure outcomes in patients with medically refractory epilepsy who had evidence of bilateral mesial temporal lobe (MTL) seizure onsets and underwent MTL resection based on chronic ambulatory intracranial EEG (ICEEG) data from a direct brain-responsive neurostimulator (RNS) system. METHODS: We retrospectively identified all patients at 17 epilepsy centers with MTL epilepsy who were treated with the RNS System using bilateral MTL leads, and in whom an MTL resection was subsequently performed. Presumed lateralization based on routine presurgical approaches was compared to lateralization determined by RNS System chronic ambulatory ICEEG recordings. The primary outcome was frequency of disabling seizures at last 3-month follow-up after MTL resection compared to seizure frequency 3 months before MTL resection. RESULTS: We identified 157 patients treated with the RNS System with bilateral MTL leads due to presumed bitemporal epilepsy. Twenty-five patients (16%) subsequently had an MTL resection informed by chronic ambulatory ICEEG (mean = 42 months ICEEG); follow-up was available for 24 patients. After MTL resection, the median reduction in disabling seizures at last follow-up was 100% (mean: 94%; range: 50%-100%). Nine patients (38%) had exclusively unilateral electrographic seizures recorded by chronic ambulatory ICEEG and all were seizure-free at last follow-up after MTL resection; eight of nine continued RNS System treatment. Fifteen patients (62%) had bilateral MTL electrographic seizures, had an MTL resection on the more active side, continued RNS System treatment, and achieved a median clinical seizure reduction of 100% (mean: 90%; range: 50%-100%) at last follow-up, with eight of fifteen seizure-free. For those with more than 1 year of follow-up (N = 21), 15 patients (71%) were seizure-free during the most recent year, including all eight patients with unilateral onsets and 7 of 13 patients (54%) with bilateral onsets. SIGNIFICANCE: Chronic ambulatory ICEEG data provide information about lateralization of MTL seizures and can identify additional patients who may benefit from MTL resection.

Biofeedback Treatment App for Pediatric Migraine: Development and Usability Study.

OBJECTIVE: The objective of this study was to develop and investigate the usability of a biofeedback treatment smartphone app for adolescent migraine sufferers. BACKGROUND: Biofeedback is effective in treating pediatric migraine. However, biofeedback is not widely used due to the necessity of a trained therapist and specialized equipment. Emerging digital technology, including smartphones and wearables, enables new ways of administering biofeedback. METHODS: In a prospective open-label development and usability study, 10 adolescent migraine sufferers used a newly developed biofeedback app with wearable sensors that measured their muscle tension, finger temperature, and heart rate. Three iterative rounds of usability testing, including a 2-week home testing period, were completed. A biofeedback algorithm, combining and optimizing the 3 physiological modalities, and several algorithms for sham-treatment were created. Usability was evaluated statistically and summarized thematically. RESULTS: Five of ten participants completed all 3 rounds of usability testing. A total of 72 biofeedback sessions were completed. Usability scoring was consistently high, with median scores ranging from 3.5 to 4.5 on a 5-point scale. The biofeedback optimization algorithm correlated excellently to the raw physiological measurements (r = 0.85, P < .001). The intervention was safe and tolerable. CONCLUSION: We developed an app for young migraine sufferers to receive therapist-independent biofeedback. The app underwent a rigorous development process as well as usability and feasibility testing. It is now ready for clinical trials.

Asymptomatic Idiopathic Belhassen Ventricular Tachycardia in a Neonate Detected Using 'Smart Sock' Wearable Smartphone-Enabled Cardiac Monitoring.

BACKGROUND Wearable smartphone-enabled cardiac monitoring devices can aid the diagnosis of asymptomatic tachycardia in neonates and infants. This report is of a rare case of left posterior fascicular ventricular tachycardia of Belhassen type detected in a neonate by 'smart sock' cardiac monitoring. CASE REPORT A premature baby boy at 37 weeks gestational age was discharged home after three days without complication, and was given 'smart socks' to wear. He was followed up daily for the management of hyperbilirubinemia, which was treated in the outpatient clinic with a phototherapy blanket. He was admitted to the emergency room (ER) at 6 days of age because his 'smart socks' identified a tachycardia of between 180-200 bpm. His parents reported no fever, cough, nasal congestion, or emesis. On examination in the ER, he was alert with no distress. An electrocardiogram (ECG) showed a sustained monomorphic and wide QRS tachycardia with a heart rate of 200 bpm, right bundle branch block (RBBB), and a superior axis that was compatible with a diagnosis of left posterior fascicular ventricular tachycardia of Belhassen type. The echocardiogram showed a structurally normal heart with normal cardiac function. His tachycardia spontaneously converted to normal sinus rhythm after four hours. He was discharged home three days later without further episodes of tachycardia. Cardiac monitoring using 'smart socks' continued at home, and no further arrhythmias were detected at one year of age. CONCLUSIONS The home use of smartphone-enabled technology to monitor the neonatal and infant cardiac heart rate can identify asymptomatic arrhythmias.

Yoga Posture Recognition and Quantitative Evaluation with Wearable Sensors Based on Two-Stage Classifier and Prior Bayesian Network.

Currently, with the satisfaction of people's material life, sports, like yoga and tai chi, have become essential activities in people's daily life. For most yoga amateurs, they could only learn yoga by self-study, like mechanically imitating from yoga video. They could not know whether they performed standardly without feedback and guidance. In this paper, we proposed a full-body posture modeling and quantitative evaluation method to recognize and evaluate yoga postures to provide guidance to the learner. Back propagation artificial neural network (BP-ANN) was adopted as the first classifier to divide yoga postures into different categories, and fuzzy C-means (FCM) was utilized as the second classifier to classify the postures in a category. The posture data on each body part was regarded as a multidimensional Gaussian variable to build a Bayesian network. The conditional probability of the Gaussian variable corresponding to each body part relative to the Gaussian variable corresponding to the connected body part was used as criterion to quantitatively evaluate the standard degree of body parts. The angular differences between nonstandard parts and the standard model could be calculated to provide guidance with an easily-accepted language, such as "lift up your left arm", "straighten your right forearm". To evaluate our method, a wearable device with 11 inertial measurement units (IMUs) fixed onto the body was designed to measure yoga posture data with quaternion format, and the posture database with a total of 211,643 data frames and 1831 posture instances was collected from 11 subjects. Both the posture recognition test and evaluation test were conducted. In the recognition test, 30% data was randomly picked from the database to train BP-ANN and FCM classifiers, and the recognition accuracy of the remaining 70% data was 95.39%, which is highly competitive with previous posture recognition approaches. In the evaluation test, 30% data were picked randomly from subject three, subject four, and subject six, to train the Bayesian network. The probabilities of nonstandard parts were almost all smaller than 0.3, while the probabilities of standard parts were almost all greater than 0.5, and thus the nonstandard parts of body posture could be effectively separated and picked for guidance. We also tested separately the trainers' yoga posture performance in the condition of without and with guidance provided by our proposed method. The results showed that with guidance, the joint angle errors significantly decreased.

Prediction using a randomized evaluation of data collection integrated through connected technologies (PREDICT): Design and rationale of a randomized trial of patients discharged from the hospital to home.

BACKGROUND: Hospital readmission prediction models often perform poorly. A critical limitation is that they use data collected up until the time of discharge but do not leverage information on patient behaviors at home after discharge. METHODS: PREDICT is a two-arm, randomized trial comparing ways to use remotely-monitored patient activity levels after hospital discharge to improve hospital readmission prediction models. Patients are randomly assigned to use a wearable device or smartphone application to track physical activity data. The study collects also validated assessments on patient characteristics as well as disparate data on credit scores and medication adherence. Patients are followed for 6 months. We evaluate whether these data sources can improve prediction compared to standard modelling approaches. CONCLUSION: The PREDICT Trial tests a novel method of remotely-monitoring patient behaviors after hospital discharge. Findings from the trial could inform new ways to improve the identification of patients at high-risk for hospital readmission. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT02983812.

Factors influencing behavioural intention to use a smart shoe insole in regionally based adults with diabetes: a mixed methods study.

BACKGROUND: Smart insole technologies that provide biofeedback on foot health can support foot-care in adults with diabetes. However, the factors that influence patient uptake and acceptance of this technology are unclear. Therefore, the aim of this mixed-methods study was to use an established theoretical framework to determine a model of psychosocial factors that best predicts participant intention to use smart insoles. METHODS: Fifty-three adults with diabetes from regional Australia completed the validated Unified Theory of Acceptance and Use of Technology (UTAUT) questionnaire. Multiple regression analysis was used to determine the psychosocial factors that best predict behavioural intention to adopt a smart insole. Additionally, a focus group was conducted and thematic analysis was performed to explore barriers and enablers to adopting this technology. RESULTS: The multiple regression model that best predicted intention to adopt the smart insole (adjusted R2 = 0.51, p < 0.001) identified that self-efficacy (ß = 0.67, p = 0.001) and attitude (ß = 0.72, p < 0.001) were significant predictors of behavioural intention, while effort expectancy (ß = - 0.52, p = 0.003) and performance expectancy (ß = - 0.40, p = 0.040) were moderating factors. Thematic analysis illustrates the importance of attitude and self-efficacy on participants' behavioural intentions, influenced by participant's belief in the device's clinical efficacy and anticipated effort expectancy. CONCLUSIONS: This mixed-methods study demonstrates that attitude, self-efficacy, performance expectancy and effort expectancy combine to predict intention to adopt smart insole technology. Clinicians should consider these psychosocial factors when they prescribe and implement smart soles with patients at high risk of foot ulceration.

Corrie Health Digital Platform for Self-Management in Secondary Prevention After Acute Myocardial Infarction.

BACKGROUND: Unplanned readmissions after hospitalization for acute myocardial infarction are among the leading causes of preventable morbidity, mortality, and healthcare costs. Digital health interventions could be an effective tool in promoting self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction. A digital health intervention developed at Johns Hopkins-the Corrie Health Digital Platform (Corrie)-includes the first cardiology Apple CareKit smartphone application, which is paired with an Apple Watch and iHealth Bluetooth-enabled blood pressure cuff. Corrie targets: (1) self-management of cardiac medications, (2) self-tracking of vital signs, (3) education about cardiovascular disease through articles and animated videos, and (4) care coordination that includes outpatient follow-up appointments. METHODS AND RESULTS: The 3 phases of the MiCORE study (Myocardial infarction, Combined-device, Recovery Enhancement) include (1) the development of Corrie, (2) a pilot study to assess the usability and feasibility of Corrie, and (3) a prospective research study to primarily compare time to first readmission within 30 days postdischarge among patients with Corrie to patients in the historical standard of care comparison group. In Phase 2, the feasibility of deploying Corrie in an acute care setting was established among a sample of 60 patients with acute myocardial infarction. Phase 3 is ongoing and patients from 4 hospitals are being enrolled as early as possible during their hospital stay if they are 18 years or older, admitted with acute myocardial infarction (ST-segment-elevation myocardial infarction or type I non-ST-segment-elevation myocardial infarction), and own a smartphone. Patients are either being enrolled with their own personal devices or they are provided an iPhone and/or Apple Watch for the duration of the study. Phase 3 started in October 2017 and we aim to recruit 140 participants. CONCLUSIONS: This article will provide an in-depth understanding of the feasibility associated with implementing a digital health intervention in an acute care setting and the potential of Corrie as a self-management tool for acute myocardial infarction recovery.