Stepping Forward: A Scoping Systematic Literature Review on the Health Outcomes of Smart Sensor Technologies for Diabetic Foot Ulcers.

Diabetic foot ulcers (DFUs) pose a significant challenge in diabetes care, demanding advanced approaches for effective prevention and management. Smart insoles using sensor technology have emerged as promising tools to address the challenges associated with DFU and neuropathy. By recognizing the pivotal role of smart insoles in successful prevention and healthcare management, this scoping review aims to present a comprehensive overview of the existing evidence regarding DFU studies related to smart insoles, offloading sensors, and actuator technologies. This systematic review identified and critically evaluated 11 key studies exploring both sensor technologies and offloading devices in the context of DFU care through searches in CINAHL, MEDLINE, and ScienceDirect databases. Predominantly, smart insoles, mobile applications, and wearable technologies were frequently utilized for interventions and patient monitoring in diabetic foot care. Patients emphasized the importance of these technologies in facilitating care management. The pivotal role of offloading devices is underscored by the majority of the studies exhibiting increased efficient monitoring, prevention, prognosis, healing rate, and patient adherence. The findings indicate that, overall, smart insoles and digital technologies are perceived as acceptable, feasible, and beneficial in meeting the specific needs of DFU patients. By acknowledging the promising outcomes, the present scoping review suggests smart technologies can potentially redefine DFU management by emphasizing accessibility, efficacy, and patient centricity.

Real-world data analysis for the association of glucose control and mortality in critically ill patients.

Existing results regarding the usage of glycemic control in critically ill patients for reduced morbidity and mortality have been based on clinical studies but could not be reproduced in large prospective studies. Current guidelines for glycemic control suggest a target blood glucose of 140-180 mg/dL, with lower targets being appropriate for some patients. The current study aims to provide additional evidence to this area, through the usage of real-world retrospective data of everyday clinical practice. We have used the large, credentialed access database MIMIC-IV to assess the effect of glycemic control to patient mortality. Glycemic control has been characterized by the percentage of time that the glucose measurements fall within pre-specified glucose bands. Results from logistic regression and survival analysis are reported, along with visualizations based on methods from the machine learning literature, which all suggest that increased time in low and high glucose values is related to increased ICU mortality and decreased survival.

GATEKEEPER's Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases.

BACKGROUND: The World Health Organization's strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. OBJECTIVE: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. METHODS: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. RESULTS: Seven European countries were selected, covering Europe's geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence-based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. CONCLUSIONS: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.

IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions. The main objective of the current article is to present the successful completion of a collaborative multiscale research work, which addressed the complicated exercise of ethical decision making in IoT smart ecosystems for older adults. Our results reveal that among the strong enablers of the proposed ethical decision support model were the participatory and deliberative procedures complemented by a set of regulatory and non-regulatory tools to operationalize core ethical values such as transparency, trust, and fairness in real care settings for older adults and their caregivers.

Two-stage, school and community-based population screening successfully identifies individuals and families at high-risk for type 2 diabetes: the Feel4Diabetes-study.

BACKGROUND: The implementation of population screening and early prevention strategies targeting individuals at high-risk for type 2 diabetes (T2D) seems to be a public health priority. The current work aimed to describe the screening procedure applied in the Feel4Diabetes-study and examine its effectiveness in identifying individuals and families at high risk, primarily for T2D and secondarily for hypertension, among vulnerable populations in low to middle-income countries (LMICs) and high-income countries (HICs) across Europe. METHODS: A two-stage screening procedure, using primary schools as the entry-point to the community, was applied in low socioeconomic status (SES) regions in LMICs (Bulgaria-Hungary), HICs (Belgium-Finland) and HICs under austerity measures (Greece-Spain). During the first-stage screening via the school-setting, a total of 20,501 parents (mothers and/or fathers) of schoolchildren from 11,396 families completed the Finnish Diabetes Risk Score (FINDRISC) questionnaire, while their children underwent anthropometric measurements in the school setting. Parents from the identified "high-risk families" (n = 4484) were invited to participate in the second-stage screening, including the measurement of fasting plasma glucose (FPG) and blood pressure (BP). In total, 3153 parents participated in the second-stage screening (mean age 41.1 ± 5.6 years, 65.8% females). RESULTS: Among parents who attended the second-stage screening, the prevalence of prediabetes (as defined by impaired fasting glucose; FPG 100-125 mg/dl) and T2D (FPG > 126 mg/dl) was 23.2 and 3.0% respectively, and it was found to be higher in the higher FINDRISC categories. The percentage of undiagnosed T2D among the participants identified with T2D was 53.5%. The prevalence of high normal BP (systolic BP 130-139 mmHg and/ or diastolic BP 85-89 mmHg) and hypertension (systolic BP ≥ 140 mmHg and/ or diastolic BP ≥ 90 mmHg) was 14 and 18.6% respectively, which was also higher in the higher FINDRISC categories. The percentage of cases not receiving antihypertensive treatment among the participants identified with hypertension was 80.3%. CONCLUSION: The findings of the current study indicate that the two-stage school and community-based screening procedure followed, effectively identified high-risk individuals and families in vulnerable populations across Europe. This approach could be potentially scalable and sustainable and support initiatives for the early prevention of T2D and hypertension. TRIAL REGISTRATION: The Feel4Diabetes-intervention is registered at https://clinicaltrials.gov/ (NCT02393872; date of trial registration: March 20, 2015).

Sociodemographic and lifestyle-related risk factors for identifying vulnerable groups for type 2 diabetes: a narrative review with emphasis on data from Europe.

BACKGROUND: Type 2 diabetes mellitus (T2DM) comprises the vast majority of all diabetes cases in adults, with alarmingly increasing prevalence over the past few decades worldwide. A particularly heavy healthcare burden of diabetes is noted in Europe, where 8.8% of the population aged 20-79 years is estimated to have diabetes according to the International Diabetes Federation. Multiple risk factors are implicated in the pathogenesis of T2DM with complex underlying interplay and intricate gene-environment interactions. Thus, intense research has been focused on studying the role of T2DM risk factors and on identifying vulnerable groups for T2DM in the general population which can then be targeted for prevention interventions. METHODS: For this narrative review, we conducted a comprehensive search of the existing literature on T2DM risk factors, focusing on studies in adult cohorts from European countries which were published in English after January 2000. RESULTS: Multiple lifestyle-related and sociodemographic factors were identified as related to high T2DM risk, including age, ethnicity, family history, low socioeconomic status, obesity, metabolic syndrome and each of its components, as well as certain unhealthy lifestyle behaviors. As Europe has an increasingly aging population, multiple migrant and ethnic minority groups and significant socioeconomic diversity both within and across different countries, this review focuses not only on modifiable T2DM risk factors, but also on the impact of pertinent demographic and socioeconomic factors. CONCLUSION: In addition to other T2DM risk factors, low socioeconomic status can significantly increase the risk for prediabetes and T2DM, but is often overlooked. In multinational and multicultural regions such as Europe, a holistic approach, which will take into account both traditional and socioeconomic/socioecological factors, is becoming increasingly crucial in order to implement multidimensional public health programs and integrated community-based interventions for effective T2DM prevention.

Methodology of the health economic evaluation of the Feel4Diabetes-study.

BACKGROUND: The clinical and economic burden of type 2 diabetes mellitus on society is rising. Effective and efficient preventive measures may stop the increasing prevalence, given that type 2 diabetes mellitus is mainly a lifestyle-driven disease. The Feel4Diabetes-study aimed to tackle unhealthy lifestyle (unhealthy diet, lack of physical activity, sedentary behaviour, and excess weight) of families with a child in the first grades of elementary school. These schools were located in regions with a relatively low socio-economic status in Belgium, Bulgaria, Finland, Greece, Hungary and Spain. Special attention was paid to families with a high risk of developing type 2 diabetes mellitus. METHODS: The aim of this paper is to describe the detailed methodology of the intervention's cost-effectiveness analysis. Based on the health economic evaluation of the Toybox-study, both a decision analytic part and a Markov model have been designed to assess the long-term (time horizon of 70 year with one-year cycles) intervention's value for money. Data sources used for the calculation of health state incidences, transition probabilities between health states, health state costs, and health state utilities are listed. Intervention-related costs were collected by questionnaires and diaries, and attributed to either all families or high risk families only. CONCLUSIONS: The optimal use of limited resources is pivotal. The future results of the health economic evaluation of the Feel4Diabetes-study will contribute to the efficient use of those resources.

Type 1 diabetes mellitus and risk of incident epilepsy: a population-based, open-cohort study.

AIMS/HYPOTHESIS: The aim of this research was to explore the relationship between incident epilepsy and type 1 diabetes in British participants. METHODS: Using The Health Improvement Network database, we conducted a retrospective, open-cohort study. Patients who were newly diagnosed with type 1 diabetes mellitus at the age of ≤40 years were identified and followed-up from 1 January 1990 to 15 September 2015. These patients, identified as not suffering from epilepsy at the time of diagnosis, were randomly matched with up to four individuals without type 1 diabetes mellitus, based on age, sex and participating general practice. A Cox regression analysis was subsequently performed using Townsend deprivation index, cerebral palsy, head injury and learning disabilities as model covariates. RESULTS: The study population consisted of a total of 24,610 individuals (4922 with type 1 diabetes and 19,688 controls). These individuals were followed up for a mean of 5.4 years (approximately 132,000 person-years of follow up). Patients with type 1 diabetes were significantly more likely to be diagnosed with epilepsy during the observation period compared with controls (crude HR [95% CI]: 3.02 [1.95, 4.69]). The incidence rate was estimated to be 132 and 44 per 100,000 person-years in patients and controls, respectively. This finding persisted after adjusting for model covariates (adjusted HR [95% CI]: 3.01 [1.93, 4.68]) and was also robust to sensitivity analysis, excluding adult-onset type 1 diabetes mellitus. CONCLUSIONS/INTERPRETATION: Patients with type 1 diabetes are at approximately three-times greater risk of developing epilepsy compared with matched controls without type 1 diabetes. This should be considered when investigating seizure-related disorders in patients with type 1 diabetes mellitus.

The hackathon model to spur innovation around global mHealth.

The challenge of providing quality healthcare to underserved populations in low- and middle-income countries (LMICs) has attracted increasing attention from information and communication technology (ICT) professionals interested in providing societal impact through their work. Sana is an organisation hosted at the Institute for Medical Engineering and Science at the Massachusetts Institute of Technology that was established out of this interest. Over the past several years, Sana has developed a model of organising mobile health bootcamp and hackathon events in LMICs with the goal of encouraging increased collaboration between ICT and medical professionals and leveraging the growing prevalence of cellphones to provide health solutions in resource limited settings. Most recently, these events have been based in Colombia, Uganda, Greece and Mexico. The lessons learned from these events can provide a framework for others working to create sustainable health solutions in the developing world.

The prevalence and treatment patterns of diabetes in the Greek population based on real-world data from the nation-wide prescription database.

AIMS: Epidemiological data regarding diabetes in Greece are based on regional, small-scale studies. We aimed to identify all citizens with prescribed pharmacological treatment for diabetes, to further explore type 1 diabetes prevalence and describe pharmacological treatment patterns in type 2 diabetes. METHODS: The electronic prescription database of the National Organization for Health Care Services Provision was used to identify individuals who received at least two prescriptions with an ICD-10 code relevant to diabetes, dispensed between June 1st, 2014 and May 31st, 2015. Type-1 diabetes was defined in those receiving at least two fully-reimbursable insulin prescriptions with an ICD-10 code of E10 (insulin-dependent diabetes). RESULTS: The study population consisted of 10,222,779 individuals, accounting for 95% of the Greek population. Prevalence of medication-prescribed diabetes was 7.0% (720,764 individuals), ranging from 0.08% in children and adolescents, to 8.2% in adults, and 30.3% in those ⩾75years old. Prevalence of type 1 diabetes was 0.24%, with a clear male predominance and more than half of cases developing after 14years of age. Metformin was the most frequently prescribed medication (77.4%) in type-2 diabetes followed by DPP-4 inhibitors (44.8%) and sulphonylureas (34.5%), while insulin was used by 19.4% of patients. CONCLUSIONS: This nation-wide real-world data analysis on medication-prescribed diabetes demonstrates that the current prevalence in Greece is 7.0%, with wide age variation and high figures in older adults. Identification of pharmacological patterns among patients with type 2 diabetes is a valuable guide in policy-makers' efforts to balance a cost-effective, quality-acceptable disease management.

Telemonitoring in chronic heart failure: a systematic review.

Heart failure (HF) is a growing epidemic with the annual number of hospitalizations constantly increasing over the last decades for HF as a primary or secondary diagnosis. Despite the emergence of novel therapeutic approached that can prolong life and shorten hospital stay, HF patients will be needing rehospitalization and will often have a poor prognosis. Telemonitoring is a novel diagnostic modality that has been suggested to be beneficial for HF patients. Telemonitoring is viewed as a means of recording physiological data, such as body weight, heart rate, arterial blood pressure, and electrocardiogram recordings, by portable devices and transmitting these data remotely (via a telephone line, a mobile phone or a computer) to a server where they can be stored, reviewed and analyzed by the research team. In this systematic review of all randomized clinical trials evaluating telemonitoring in chronic HF, we aim to assess whether telemonitoring provides any substantial benefit in this patient population.

Gerontechnology: providing a helping hand when caring for cognitively impaired older adults-intermediate results from a controlled study on the satisfaction and acceptance of informal caregivers.

The incidence of cognitive impairment in older age is increasing, as is the number of cognitively impaired older adults living in their own homes. Due to lack of social care resources for these adults and their desires to remain in their own homes and live as independently as possible, research shows that the current standard care provisions are inadequate. Promising opportunities exist in using home assistive technology services to foster healthy aging and to realize the unmet needs of these groups of citizens in a user-centered manner. ISISEMD project has designed, implemented, verified, and assessed an assistive technology platform of personalized home care (telecare) for the elderly with cognitive impairments and their caregivers by offering intelligent home support services. Regions from four European countries have carried out long-term pilot-controlled study in real-life conditions. This paper presents the outcomes from intermediate evaluations pertaining to user satisfaction with the system, acceptance of the technology and the services, and quality of life outcomes as a result of utilizing the services.