Patient-Driven Diabetes Care of the Future in the Technology Era

Efficacy of Self-Review of Lifestyle Behaviors with Once-Weekly Glycated Albumin Measurement in People with Type 2 Diabetes: A Randomized Pilot Study

INTRODUCTION

Lifestyle management, including appropriate modifications of nutrition, exercise, and medication behaviors, is essential for optimal glycemic control. The absence of appropriate monitoring methods to validate the lifestyle change may hinder the modification and continuation of behaviors. In this study, we evaluated whether once-weekly glycated albumin (GA) measurement received via a smartphone application could improve glycemia management in patients with type 2 diabetes mellitus by supporting self-review and modification of lifestyle behaviors.

METHODS

This open-label, randomized controlled, single-center study in Japan with an 8-week intervention period was conducted in individuals with type 2 diabetes mellitus and HbA1c levels between 7.0 and 9.0% (53‒75 mmol/mol). The intervention was once-weekly home monitoring of GA with a daily self-review of lifestyle behaviors using a smartphone application, in addition to conventional treatment.

RESULTS

A total of 98 participants (72.0% males; age 63.2 ± 11.4 years; HbA1c 7.39 ± 0.39% [57.3 ± 4.3 mmol/mol]) were randomly assigned to the intervention or control group. Significant decreases of the GA and HbA1c levels from the baseline to the last observation day were observed in the intervention group (- 1.71 ± 1.37% [- 39.1 ± 31.3 mmol/mol] and - 0.32 ± 0.32% [- 3.5 ± 3.5 mmol/mol], respectively). Significant decreases of the body weight, waist circumference, and caloric expenditure (p < 0.0001 and p = 0.0003, p = 0.0346, respectively), but not of the caloric intake (p = 0.678), were also observed in the intervention group as compared with the control group.

CONCLUSIONS

Self-review of lifestyle behaviors in combination with once-weekly GA home testing received via a smartphone application might potentially benefit glycemic management in people with type 2 diabetes mellitus.

TRIAL REGISTRATION

jRCTs042220048.

Integrated patient-centred care for type 2 diabetes in Singapore Primary Care Networks: a mixed-methods study

OBJECTIVE

Patients with type 2 diabetes require patient-centred care as guided by the Chronic Care Model (CCM). Many diabetes patients in Singapore are managed by the Primary Care Networks (PCNs) which organised healthcare professionals (HCPs) comprising general practitioners, nurses and care coordinators into teams to provide diabetes care. Little is known about how the PCNs deliver care to people with type 2 diabetes. This study evaluated the consistency of diabetes care delivery in the PCNs with the CCM.

DESIGN

This was a mixed-method study. The Assessment of Chronic Illness Care (ACIC version 3.5) survey was self-administered by the HCPs in the quantitative study (ACIC scores range 0-11, the latter indicating care delivery most consistent with CCM). Descriptive statistics were obtained, and linear mixed-effects regression model was used to test for association between independent variables and ACIC total scores. The qualitative study comprised semi-structured focus group discussions and used thematic analysis.

SETTING

The study was conducted on virtual platforms involving the PCNs.

PARTICIPANTS

179 HCPs for quantitative study and 65 HCPs for qualitative study.

RESULTS

Integrated analysis of quantitative and qualitative results found that there was support for diabetes care consistent with the CCM in the PCNs. The mean ACIC total score was 5.62 (SD 1.93). The mean element scores ranged from 6.69 (SD 2.18) (Health System Organisation) to 4.91 (SD 2.37) (Community Linkages). The qualitative themes described how the PCNs provided much needed diabetes services, their characteristics such as continuity of care, patient-centred care; collaborating with community partners, financial aspects of care, enablers for and challenges in performing care, and areas for enhancement.

CONCLUSION

This mixed-methods study informs that diabetes care delivery in the Singapore PCNs is consistent with the CCM. Future research should consider using independent observers in the quantitative study and collecting objective data such as patient outcomes.

App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data

BACKGROUND

Early weight loss is an established predictor for treatment outcomes in weight management interventions for people with obesity. However, there is a paucity of additional, reliable, and clinically actionable early predictors in weight management interventions. Novel blended-care weight management interventions combine coach and app support and afford new means of structured, continuous data collection, informing research on treatment adherence and outcome prediction.

OBJECTIVE

Against this backdrop, this study analyzes app engagement as a predictor for weight loss in large-scale, real-world, blended-care interventions. We hypothesize that patients who engage more frequently in app usage in blended-care treatment (eg, higher logging activity) lose more weight than patients who engage comparably less frequently at 3 and 6 months of intervention.

METHODS

Real-world data from 19,211 patients in obesity treatment were analyzed retrospectively. Patients were treated with 3 different blended-care weight management interventions, offered in Switzerland, the United Kingdom, and Germany by a digital behavior change provider. The principal component analysis identified an overarching metric for app engagement based on app usage. A median split informed a distinction in higher and lower engagers among the patients. Both groups were matched through optimal propensity score matching for relevant characteristics (eg, gender, age, and start weight). A linear regression model, combining patient characteristics and app-derived data, was applied to identify predictors for weight loss outcomes.

RESULTS

For the entire sample (N=19,211), mean weight loss was -3.24% (SD 4.58%) at 3 months and -5.22% (SD 6.29%) at 6 months. Across countries, higher app engagement yielded more weight loss than lower engagement after 3 but not after 6 months of intervention (P3 months<.001 and P6 months=.59). Early app engagement within the first 3 months predicted percentage weight loss in Switzerland and Germany, but not in the United Kingdom (PSwitzerland<.001, PUnited Kingdom=.12, and PGermany=.005). Higher age was associated with stronger weight loss in the 3-month period (PSwitzerland=.001, PUnited Kingdom=.002, and PGermany<.001) and, for Germany, also in the 6-month period (PSwitzerland=.09, PUnited Kingdom=.46, and PGermany=.03). In Switzerland, higher numbers of patients' messages to coaches were associated with higher weight loss (P3 months<.001 and P6 months<.001). Messages from coaches were not significantly associated with weight loss (all P>.05).

CONCLUSIONS

Early app engagement is a predictor of weight loss, with higher engagement yielding more weight loss than lower engagement in this analysis. This new predictor lends itself to automated monitoring and as a digital indicator for needed or adapted clinical action. Further research needs to establish the reliability of early app engagement as a predictor for treatment adherence and outcomes. In general, the obtained results testify to the potential of app-derived data to inform clinical monitoring practices and intervention design.

Measuring the effectiveness of hybrid diabetes care over 90 days through continuous data monitoring in type 2 diabetic patients

Background

Diabetes Mellitus, a global health challenge, affects 537 million individuals. Traditional management relies on periodic clinic visits, but technological advancements, including remote monitoring, offer transformative changes. Telemedicine enhances access, convenience, adherence, and glycemic control. Challenges include trust-building and limitations in face-to-face interactions. Integrating remote monitoring with in-person healthcare creates a hybrid approach. This study evaluates the impact on Type 2 Diabetes patients over 3 months.

Methods

A retrospective case-control observational study. Inclusion criteria involved previous Type 2 Diabetes diagnosis and a minimum 3-month GluCare model period with two physical visits. Patients in the case group had in-clinic visits, bi-weekly app engagement, and monthly body weight readings. Control group had in-clinic visits only. Outcomes measured included HbA1c, lipid profile, CV risk, eGFR, urine Albumin/Creatinine Ratio, Uric Acid, and CRP.

Results

Case group showed significant HbA1c improvements (-2.19%), especially in higher baseline levels. Weight, BMI, LDL, total cholesterol, and CVD risk also improved. Controls showed smaller improvements. Higher digital interactions correlated with better outcomes. Patients with ≥11 interactions showed significant reductions in HbA1c (-2.38%) and weight (-6.00 kg).

Conclusion

The GluCare.Health hybrid model demonstrates promising outcomes in Type 2 diabetes management. The integration of in-clinic consultations with continuous remote monitoring leads to substantial improvements in glycemic control and clinical parameters. The study highlights the importance of patient engagement in achieving positive outcomes, with higher digital interactions associated with greater reductions in HbA1c and weight. The hybrid approach proves more effective than digital-only interventions, emphasizing the need for comprehensive, end-to-end solutions in diabetes care.

Treatment approaches and costs associated with diabetes clinical metrics as measured by Healthcare Effectiveness Data and Information Set (HEDIS)

BACKGROUND

The clinical outcomes of diabetes can be influenced by primary care providers' (PCP) treatment approaches. This study explores the association between PCP approaches to management and performance measured by established diabetes metrics and related costs.

METHODS

In phase one, Electronic Medical Records were used to extract diabetes related metrics using Healthcare Effectiveness Data and Information Set (HEDIS), for patients with diabetes who had office visits to 44 PCP practices from April 2019 to March 2020. Using those metrics and scoring system, PCP practices were ranked and then categorized into high- and low-performing groups (top and bottom 25%, n = 11 each), with a total of 19,059 clinic visits by patients with a diagnosis of diabetes. Then extensive analysis was performed to evaluate a correlation between treatment approaches and diabetes outcomes across the top and bottom performing practices. In phase 2, patients with diabetes who were attributed to the aforementioned PCP practices were identified in a local health plan claims data base (a total of 3,221 patients), and the allowed amounts from their claims were used to evaluate differences in total and diabetes-related healthcare costs by providers' performance.

RESULTS

Comparing 10,834 visits in high-performing practices to 8,235 visits in low-performing practices, referrals to certified diabetes care and education specialists and provider-to-provider electronic consults (e-consults) were higher in high-performing practices (Z = 6.06, p < .0001), while traditional referrals were higher in low-performing practices (Z = -6.94, p < .0001). The patient-to-provider ratio was higher in the low-performing group (M = 235.23) than in the high-performing group (M = 153.26) (Z = -2.82, p = .0048). Claims data analysis included 1,825 and 1,396 patients from high- and low-performing providers, respectively. The patient-to-provider ratio was again higher in the low-performing group (p = .009, V = 0.62). Patients receiving care from lower-performing practices were more likely to have had a diabetes-related hospital observation (5.7% vs. 3.9%, p = .02; V = 0.04) and higher diabetes-related care costs (p = .002; d = - 0.07); these differences by performance status persisted when controlling for differences in patient and physician characteristics. Patients seeing low-performing providers had higher Charlson Comorbidity Index scores (Mdn = 3) than those seeing high-performing providers (Mdn = 2).

CONCLUSIONS

Referrals to the CDCES and e-Consult were associated with better measured diabetes outcomes, as were certain aspects of cost and types of hospital utilization. Higher patients to providers ratio and patients with more comorbidities were observed in low performing group.

Effectiveness of remote monitoring for glycemic control on maternal-fetal outcomes in women with gestational diabetes mellitus: A meta-analysis

BACKGROUND

The current pandemic and future public health emergencies highlight the importance of evaluating a telehealth care model. Previous studies have reached mixed conclusions about the effectiveness of remote monitoring on glycemic control and maternal and infant outcomes in women with gestational diabetes mellitus (GDM).

OBJECTIVES

This meta-analysis aimed to evaluate the effectiveness of remote blood glucose monitoring for women with gestational diabetes mellitus and to provide evidence-based guidance on the management of women with gestational diabetes mellitus for policymakers and healthcare providers during situations such as pandemics or natural disasters.

METHODS

The Cochrane Library, PubMed, Web of Science, EBSCO, Embase, Medline, CINAHL databases, and ClinicalTrials.gov were systematically searched from their inception to July 10, 2021. Randomized controlled trials (RCTs) published in English with respect to remote blood glucose monitoring in women with GDM were included in the meta-analysis. Two independent reviewers performed data extraction and assessed the quality of the studies. Risk ratios, mean differences, 95% confidence intervals, and heterogeneity were calculated.

RESULTS

A total of 1265 participants were included in the 11 RCTs. There were no significant differences in glycemic control and maternal-fetal outcomes between the remote monitoring group and a standard care group, which included glycosylated hemoglobin (HbA1c), fasting blood glucose, mean 2-h postprandial blood glucose, caesarean birth, gestational weight gain, shoulder dystocia, neonatal hypoglycemia, and other outcomes.

CONCLUSION

This meta-analysis reveals that it is unclear if remote glucose monitoring is preferable to standard of care glucose monitoring. To improve glycemic control and maternal-fetal outcomes during the current epidemic or other natural disasters, the implementation of double-blind RCTs in the context of simulating similar disasters remains to be studied in the future.

The Influence of Nurse-Led Interventions on Diseases Management in Patients with Diabetes Mellitus: A Narrative Review

The global prevalence of people with diabetes mellitus (PWD) is rapidly increasing. Nurses can provide diabetes care for PWD in several areas. Interventions led by nurses can support PWD for effective management of diabetes, which can positively improve clinical outcomes. Nurse-led diabetes self-management education (DSME) is an effective strategy to manage diabetes mellitus (DM) since it improves self-care practice and knowledge regarding diabetes. PWD often need to stay in hospitals longer, which involves poorer patient satisfaction and clinical outcomes. Nurse-led clinics for DM management are a new strategy to possibly ameliorate the disease management. Diabetes specialist nurses can play an important role in improving diabetes care in inpatient settings. Various studies have revealed that nurses can independently provide care to PWD in collaboration with various other healthcare providers. Studies also demonstrated that the nurse-led education-receiving group showed a significantly reduced level of average glycosylated haemoglobin A1c level. Moreover, nurse-led interventions often result in significant improvements in diabetes knowledge, psychological outcomes, self-management behaviours, and physiological outcomes. The purpose of this literature review was to identify the impact of nurse-led interventions on diabetes management. Moreover, in this review, a number of nursing interventions and the nurses' roles as educators, motivators as well as caregivers in DM management have been extensively discussed. This article also summarises the outcomes that are measured to evaluate the impact of nursing interventions and the strategies to overcome the existing and emerging challenges for nurses in diabetes care.

Novel Therapies in Diabetes: A Comprehensive Narrative Review of GLP-1 Receptor Agonists, SGLT2 Inhibitors, and Beyond

Diabetes mellitus, a widespread metabolic illness with increasing global occurrence, continues to have a significant impact on public health. Diabetes is a condition marked by long-term high blood sugar levels. It is caused by a combination of genetic, environmental, and lifestyle factors, which lead to problems with insulin production and insulin resistance. This dysfunctional state disturbs the delicate balance of glucose regulation, promoting the emergence of problems in both large and small blood vessels that have a substantial impact on illness and death rates. Traditional therapy methods have traditionally given more importance to managing blood sugar levels by using insulin sensitizers, secretagogues, and other medications that lower glucose levels. Advancements in our understanding of the underlying mechanisms of diabetes have led to a significant change in approach, focusing on comprehensive therapies that target not only high blood sugar levels but also the accompanying dangers to the heart and kidneys. This study examines the evolving field of diabetes therapies, explicitly highlighting the significance of GLP-1 receptor agonists and SGLT2 inhibitors. These two types of drugs have become essential components in modern diabetes management. GLP-1 receptor agonists replicate the effects of natural glucagon-like peptide-1, leading to insulin production that is reliant on glucose levels, reducing the release of glucagon, and providing cardiovascular advantages that go beyond controlling blood sugar levels. SGLT2 inhibitors, however, act on the process of renal glucose reabsorption, leading to increased excretion of glucose in the urine and showing significant benefits for cardiovascular and renal protection. This extensive investigation seeks to contribute to the ongoing discourse on diabetes therapies by synthesizing existing research. This review aims to provide clinicians, researchers, and policymakers with a comprehensive understanding of the disease background and the specific pharmacological details of GLP-1 receptor agonists, SGLT2 inhibitors, and other related treatments. The goal is to assist them in developing more effective and personalized strategies to tackle the complex challenges presented by diabetes.

Effectiveness of a hybrid technology enabled care model as measured by ICHOM standard set on established and managed type 2 diabetes already using medications: A RWE retrospective study

Aims

Diabetes is a pressing global health issue, demanding innovative strategies for improved treatment. However, traditional care often falls short of patient goals. To address this, digital health solutions, including smartphone apps and remote monitoring, have emerged as crucial in diabetes management. This study aims to assess a comprehensive intervention, combining remote continuous data monitoring (RCDM) with in-clinic care, for enhancing diabetes-related outcomes. Additionally, it seeks to evaluate the effectiveness of the digital RCDM component by comparing adherent and non-adherent patients.

Methods

Conducted in the United Arab Emirates, a retrospective study involved 89 patients primarily on anti-diabetic medications. They were split into two groups based on adherence to RCDM. Over time, significant improvements were observed across various parameters.

Results

Notably, patients exhibited weight loss (-4.0 ± 5.3, p < 0.001), reduced waist circumference (-4.74 ± 7.8, p < 0.001), lowered HbA1c levels (-1.00 ± 1.3, p < 0.001), decreased systolic BP (-3.1 ± 13.1, p = 0.035), and diminished diastolic BP (-3.4 ± 9.9, p = 0.002) annually. Furthermore, patients adhering to the GluCare model demonstrated substantial HbA1c reductions (-1.53 ± 1.5, p < 0.001), improved lipid profiles, notably decreased total Cholesterol (-16.6 ± 50.3, p = 0.034), and lowered LDL levels (-18.65 ± 42.6, p = 0.006).

Conclusions

The intervention model effectively managed T2D patients through a comprehensive approach, yielding notable improvements in HbA1c levels and other outcomes within a year. The study underscores the limitations of traditional care and reliance simply on pharmacotherapy, and emphasizes the need for a hyper-personalized, and continuous approach for T2D management.

The Future of Patient Education: AI-Driven Guide for Type 2 Diabetes

Introduction and aim The surging incidence of type 2 diabetes has become a growing concern for the healthcare sector. This chronic ailment, characterized by its complex blend of genetic and lifestyle determinants, has witnessed a notable increase in recent times, exerting substantial pressure on healthcare resources. As more individuals turn to online platforms for health guidance and embrace the utilization of Chat Generative Pre-trained Transformer (ChatGPT; San Francisco, CA: OpenAI), a text-generating AI (TGAI), to get insights into their well-being, evaluating its effectiveness and reliability becomes crucial. This research primarily aimed to evaluate the correctness of TGAI responses to type 2 diabetes (T2DM) inquiries via ChatGPT. Furthermore, this study aimed to examine the consistency of TGAI in addressing common queries on T2DM complications for patient education. Material and methods Questions on T2DM were formulated by experienced physicians and screened by research personnel before querying ChatGPT. Each question was posed thrice, and the collected answers were summarized. Responses were then sorted into three distinct categories as follows: (a) appropriate, (b) inappropriate, and (c) unreliable by two seasoned physicians. In instances of differing opinions, a third physician was consulted to achieve consensus. Results From the initial set of 110 T2DM questions, 40 were dismissed by experts for relevance, resulting in a final count of 70. An overwhelming 98.5% of the AI's answers were judged as appropriate, thus underscoring its reliability over traditional online search engines. Nonetheless, a 1.5% rate of inappropriate responses underlines the importance of ongoing AI improvements and strict adherence to medical protocols. Conclusion TGAI provides medical information of high quality and reliability. This study underscores TGAI's impressive effectiveness in delivering reliable information about T2DM, with 98.5% of responses aligning with the standard of care. These results hold promise for integrating AI platforms as supplementary tools to enhance patient education and outcomes.

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialists, uneven distribution of medical resources, low adherence to medications, and improper self-management contribute to poor glycemic control in patients with diabetes. Recent advancements in digital health technologies, especially artificial intelligence (AI), provide a significant opportunity to achieve better efficiency in diabetes care, which may diminish the increase in diabetes-related health-care expenditures. Here, we review the recent progress in the application of AI in the management of diabetes and then discuss the opportunities and challenges of AI application in clinical practice. Furthermore, we explore the possibility of combining and expanding upon existing digital health technologies to develop an AI-assisted digital health-care ecosystem that includes the prevention and management of diabetes.

Segmenting Patients With Diabetes With the Navigator Service in Primary Care and a Description of the Self-Acting Patient Group: Cross-Sectional Study

BACKGROUND

The aim of patient segmentation is to recognize patients with similar health care needs. The Finnish patient segmentation service Navigator segregates patients into 4 groups, including a self-acting group, who presumably manages their everyday life and coordinates their health care. Digital services could support their self-care. Knowledge on self-acting patients' characteristics is lacking.

OBJECTIVE

The study aims are to describe how Navigator assigns patients with diabetes to the 4 groups at nurses' appointments at a health center, the self-acting patient group's characteristics compared with other patient groups, and the concordance between the nurse's evaluation of the patient's group and the actual group assigned by Navigator (criterion validity).

METHODS

Patients with diabetes ≥18 years old visiting primary care were invited to participate in this cross-sectional study. Patients with disability preventing informed consent for participation were excluded. Nurses estimated the patients' upcoming group results before the appointment. We describe the concordance (%) between the evaluation and actual groups. Nurses used Navigator patients with diabetes (n=304) at their annual follow-up visits. The self-acting patients' diabetes care values (glycated hemoglobin [HbA1c], urine albumin to creatinine ratio, low-density lipoprotein cholesterol, blood pressure, BMI), chronic conditions, medication, smoking status, self-rated health, disability (World Health Organization Disability Assessment Schedule [WHODAS] 2.0), health-related quality of life (EQ-5D-5L), and well-being (Well-being Questionnaire [WBQ-12]) and the patients' responses to Navigator's question concerning their digital skills as outcome variables were compared with those of the other patients. We used descriptive statistics for the patients' distribution into the 4 groups and demographic data. We used the Mann-Whitney U test with nonnormally distributed variables, independent samples t test with normally distributed variables, and Pearson chi-square tests with categorized variables to compare the groups.

RESULTS

Most patients (259/304, 85.2%) were in the self-acting group. Hypertension, hyperlipidemia, and joint ailments were the most prevalent comorbidities among all patients. Self-acting patients had less ischemic cardiac disease (P=.001), depression or anxiety (P=.03), asthma or chronic obstructive pulmonary disease (P<.001), long-term pain (P<.001), and related medication. Self-acting patients had better self-rated health (P<.001), functional ability (P<.001), health-related quality of life (P<.001), and general well-being (P<.001). All patients considered their skills at using electronic services to be good.

CONCLUSIONS

The patients in the self-acting group had several comorbidities. However, their functional ability was not yet diminished compared with patients in the other groups. Therefore, to prevent diabetic complications and disabilities, support for patients' self-management should be emphasized in their integrated care services. Digital services could be involved in the care of patients willing to use them. The study was performed in 1 health center, the participants were volunteers, and most patients were assigned to self-acting patient group. These facts limit the generalizability of our results.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/20570.

The Direction of Neurosurgery to Overcome the Living with COVID-19 Era : The Possibility of Telemedicine in Neurosurgery

OBJECTIVE

Due to the implementation of vaccinations and the development of therapeutic agents, the coronavirus disease 2019 (COVID-19) pandemic that started at the end of 2019 has entered a new phase. As a result, neurosurgeons should reconsider the way they treat their patients. As the COVID-19 situation prolongs, the change in neurosurgical emergency patients according to the number of confirmed cases is no longer clear. Outpatient treatment by telephone was permitted according to government policy. In addition, visits to caregivers in the intensive care unit were limited.

METHODS

The electronic medical records of patients who had been treated over the phone for a month (during April 2020, while the hospital was closing) were reviewed. Meanwhile, according to the limited visits to the intensive care unit, a video meeting was held with the caregivers. After the video meeting, satisfaction was evaluated using a questionnaire.

RESULTS

During April 2020, 1021 patients received non-face-to-face care over the telephone. Among the patients, no critical medical problem occurred due to non-face-to-face care. From July 2021 to December 2021, 321 patients were admitted to the neurosurgical intensive care unit and 107 patients (33.3%) including their caregivers agreed to video visits. Twice a week, advance notice was given that access would be made through a mobile device and the nurse explained to caregivers how to use the mobile device. The time for the video meeting was approximately 20 minutes per patient. Based on the questionnaire, 81 respondents (75.7%) answered that they agreed, and 26 respondents (24.3%) answered that they strongly agreed that was easy to communicate through video meetings. Fifty-two (48.6%) agreed and 55 (51.4%) strongly agreed that they were easy to understand the doctor's explanation. For overall satisfaction with this video meeting, three respondents (2.8%) gave 4/5 points and 95 respondents (88.8%) gave 5/5 points, and nine (8.4%) gave 3/5 points. Their reason was that there was not enough time.

CONCLUSION

In situations where patient visits are limited, video meetings through a mobile device can provide sufficient satisfaction to caregivers. Telemedicine will likely become common in the near future. Health care professionals should prepare and respond to these needs and changes. Therefore, establishing a system with institutional support is necessary.

eHealth profile of patients with diabetes

Background

Digital health technology can be useful to improve the health of patients with diabetes and to support patient-centered care and self-management. In this cross-sectional study, we described the eHealth profile of patients with diabetes, based on their use of digital health technology, and its association with sociodemographic characteristics.

Methods

We used data from the "Qualité Diabète Valais" cohort study, conducted in one region of Switzerland (Canton Valais) since 2019. Participants with type 1 or type 2 diabetes completed questionnaires on sociodemographic characteristics and on the use of digital health technology. We defined eHealth profiles based on three features, i.e., ownership or use of (1) internet-connected devices (smartphone, tablet, or computer), (2) mHealth applications, and (3) connected health tools (activity sensor, smart weight scale, or connected blood glucose meter). We assessed the association between sociodemographic characteristics and participants' eHealth profiles using stratified analyses and logistic regression models.

Results

Some 398 participants (38% women) with a mean age of 65 years (min: 25, max: 92) were included. The vast majority (94%) were Swiss citizens or bi-national and 68% were economically inactive; 14% had a primary level education, 51% a secondary level, and 32% a tertiary level. Some 75% of participants had type 2 diabetes. Some 90% of the participants owned internet-connected devices, 43% used mHealth applications, and 44% owned a connected health tool. Older age and a lower educational level were associated with lower odds of all features of the eHealth profile. To a lesser extent, having type 2 diabetes or not being a Swiss citizen were also associated with a lower use of digital health technology. There was no association with sex.

Conclusion

While most participants owned internet-connected devices, only about half of them used mHealth applications or owned connected health tools. Older participants and those with a lower educational level were less likely to use digital health technology. eHealth implementation strategies need to consider these sociodemographic patterns among patients with diabetes.

Advances in the Management of Diabetes Mellitus: A Focus on Personalized Medicine

Diabetes mellitus poses a substantial global health challenge, necessitating innovative approaches to improve patient outcomes. Conventional one-size-fits-all treatment strategies have shown limitations in addressing the diverse nature of the disease. In recent years, personalized medicine has emerged as a transformative solution, tailoring treatment plans based on individual genetic makeup, lifestyle factors, and health characteristics. This review highlights the role of genetic screening in predicting diabetes susceptibility and response to treatment, as well as the potential of pharmacogenomics in optimizing medication choices. Moreover, it discusses the incorporation of lifestyle modifications and behavioral interventions to empower patients in their health journey. Telemedicine and remote patient monitoring are also examined for their role in enhancing accessibility and adherence. Ethical considerations and challenges in implementing personalized medicine are addressed. The review envisions a future where personalized medicine becomes a cornerstone in diabetes management, ensuring improved patient outcomes and fostering more effective and patient-centric care on a global scale.

Exploring the Complex Connection Between Diabetes and Cardiovascular Disease: Analyzing Approaches to Mitigate Cardiovascular Risk in Patients With Diabetes

Cardiovascular disease (CVD) is the primary cause of morbidity and mortality in individuals diagnosed with diabetes mellitus. This narrative review offers a comprehensive examination of the complex correlation between diabetes and cardiovascular complications. The objective of this review is to analyze the most recent evidence on preventive measures and treatment options for mitigating cardiovascular risk in patients with diabetes, by synthesizing existing literature. Insulin resistance plays a crucial role in connecting diabetes and CVD, leading to the development of dyslipidemia and atherogenesis. As a result, the risk of cardiovascular events in individuals with diabetes is significantly elevated. Moreover, the presence of hyperglycemia-induced oxidative stress and inflammation serves to intensify endothelial dysfunction and vascular damage, thereby exacerbating the risk of cardiovascular complications. The interaction between diabetes and CVD frequently speeds up the development of atherosclerotic plaque, making the plaque more prone to rupture. This can lead to severe cardiovascular events such as myocardial infarction and stroke. It is crucial to comprehend the intricate relationship between diabetes and CVD in order to formulate effective strategies aimed at enhancing patient outcomes and mitigating the burden associated with these interconnected chronic conditions. Healthcare practitioners can enhance the quality of life and reduce mortality rates associated with CVD in diabetic patients by thoroughly examining evidence-based preventive measures and treatment options. This approach allows them to make informed decisions when managing cardiovascular risk. In summary, this narrative review provides a valuable resource for healthcare professionals and researchers, presenting a comprehensive analysis of the complex relationship between diabetes and CVD. By providing a comprehensive analysis of the latest evidence and elucidating the underlying mechanisms, this review seeks to establish a foundation for the development of innovative strategies in diabetes management. These strategies have the potential to significantly improve cardiovascular outcomes and enhance overall patient care.

Endocrinologists' Experiences With Telehealth: A Qualitative Study With Implications for Promoting Sustained Use

OBJECTIVE

Endocrinology is well-suited to telehealth, with high rates of use and known benefits. Clinician attitudes toward telehealth will be critical to ensuring sustained use after the pandemic. We examined endocrinologists' experiences with synchronous telehealth to identify factors affecting experiences with and acceptance of the technology.

METHODS

We conducted qualitative interviews and directed-content analysis with a purposive sample of 26 U.S. endocrinologists. Factors affecting clinicians' experiences were mapped to the human-organization-technology fit (HOT-fit) framework.

RESULTS

We found that clinicians' experiences with synchronous telehealth were influenced by: (1) Clinician factors: Clinicians welcomed telehealth but expressed concerns about patient interest, rapport building, and clinical appropriateness, desiring more data to support its use. Many clinicians feared missing clinical findings on virtual examination, despite no such personal experiences. Effects on professional and personal life contributed to satisfaction, through increased flexibility but also increased workload. (2) Organizational factors: Departmental meetings and trainings supported clinicians' technical, logistical, and clinical needs, reducing resistance to telehealth use. Shifting staff responsibilities in clinical workflows improved clinicians' experiences and supported telehealth use, while mixed telehealth and in-person schedules impeded workflow. (3) Technology factors: Most clinicians preferred video visits to telephone. Usability and reliability of telehealth platforms, integration of patient self-monitoring data, and availability of IT support were crucial to a positive experience.

CONCLUSION

Clinician acceptance of telehealth is influenced by clinician, organizational, and technology factors that can be leveraged to improve buy-in. Organizational leaders' attention to addressing these factors will be critical to support endocrinologists' continued provision of telehealth for their patients.

Mobile Health Apps for the Control and Self-management of Type 2 Diabetes Mellitus: Qualitative Study on Users' Acceptability and Acceptance

BACKGROUND

Mobile health apps are promising tools to help patients with type 2 diabetes mellitus (T2DM) improve their health status and thereby achieve diabetes control and self-management. Although there is a wide array of mobile health apps for T2DM available at present, apps are not yet integrated into routine diabetes care. Acceptability and acceptance among patients with T2DM is a major challenge and prerequisite for the successful implementation of apps in diabetes care.

OBJECTIVE

This study provides an in-depth understanding of the perceptions of patients with T2DM before use (acceptability) and after use (acceptance) regarding 4 different mobile health apps for diabetes control and self-management.

METHODS

A descriptive qualitative research design was used in this study. Participants could choose 1 of the 4 selected apps for diabetes control and self-management (ie, Clear.bio in combination with FreeStyle Libre, mySugr, MiGuide, and Selfcare). The selection was based on a systematic analysis of the criteria for (functional) requirements regarding monitoring, data collection, provision of information, coaching, privacy, and security. To explore acceptability, 25 semistructured in-depth interviews were conducted with patients with T2DM before use. This was followed by 4 focus groups to discuss the acceptance after use. The study had a citizen science approach, that is, patients with T2DM collaborated with researchers as coresearchers. All coresearchers actively participated in the preparation of the study, data collection, and data analysis. Data were collected between April and September 2021. Thematic analysis was conducted using a deductive approach using AtlasTi9.

RESULTS

In total, 25 coresearchers with T2DM participated in this study. Of them, 12 coresearchers tested Clear, 5 MiGuide, 4 mySugr, and 4 Selfcare. All coresearchers participated in semistructured interviews, and 18 of them attended focus groups. Personal health was the main driver of app use. Most coresearchers were convinced that a healthy lifestyle would improve blood glucose levels. Although most coresearchers did not expect that they need to put much effort into using the apps, the additional effort to familiarize themselves with the app use was experienced as quite high. None of the coresearchers had a health care professional who provided suggestions on using the apps. Reimbursement from insurance companies and the acceptance of apps for diabetes control and self-management by the health care system were mentioned as important facilitating conditions.

CONCLUSIONS

The research showed that mobile health apps provide support for diabetes control and self-management in patients with T2DM. Integrating app use in care as usual and guidelines for health care professionals are recommended. Future research is needed on how to increase the implementation of mobile health apps in current care pathways. In addition, health care professionals need to improve their digital skills, and lifelong learning is recommended.

Patients, carers and healthcare providers' perspectives on a patient-owned surveillance system for diabetic foot ulcer care: A qualitative study

Objective

Digital health has recently gained a foothold in monitoring and improving diabetes care. We aim to explore the views of patients, carers and healthcare providers (HCPs) regarding the use of a novel patient-owned wound surveillance application as part of outpatient management of patients with diabetic foot ulcers (DFUs).

Methods

Semi-structured online interviews were conducted with patients, carers and HCPs in wound care for DFUs. The participants were recruited from a primary care polyclinic network and two tertiary hospitals in Singapore, within the same healthcare cluster. Purposive maximum variation sampling was used to select participants with differing attributes to ensure heterogeneity. Common themes relating to the wound imaging app were captured.

Results

A total of 20 patients, 5 carers and 20 HCPs participated in the qualitative study. None of the participants have used a wound imaging app before. Regarding a patient-owned wound surveillance app, all were open and receptive to the system and workflow for use in DFU care. Four major themes emerged from patients and carers: (1) technology, (2) application features and usability, (3) feasibility of using the wound imaging application and (4) logistics of care. Four major themes were identified from HCPs: (1) attitudes towards wound imaging app, (2) preferences regarding functionality, (3) perceived challenges for patients/carers and (4) perceived barriers for HCPs.

Conclusion

Our study highlighted several barriers and facilitators from patients, carers and HCPs regarding the use of a patient-owned wound surveillance app. These findings demonstrate the potential of digital health and areas to improve and tailor a DFU wound app suitable for implementation in the local population.

Online medical consultation in China: Evidence from obesity doctors

Objective

Online medical consultation (OMC) is increasingly used in China, but there have been few in-depth studies of consultation arrangements and fee structures of online doctors in China. This research assessed the consultation arrangements and fee structure of OMC in China by undertaking a case study of obesity doctors from four representative OMC platforms.

Methods

Detailed information, including fees, waiting time and doctor information, was collected from four obesity OMC platforms and analyzed using descriptive statistical analysis.

Results

The obesity OMC platforms in China shared similarities in the use of big data and artificial intelligence (AI) but differed across service access, specific consultation arrangements and fees. Big data search and AI response technologies were used by most platforms to match users with doctors and reduce doctors' pressure. The descriptive statistical analysis showed that the higher the rank of the online doctor, the higher the online fee and the longer the wait time. Through a comparison with offline hospitals, we found online doctors' fees exceeded offline hospital doctors' fees by up to 90%.

Conclusions

OMC platforms can gain competitive advantages over offline medical institutions through the following measures: make fuller use of big data and AI technologies to provide users with longer duration, lower cost and more efficient consultation services; provide better user experience than offline medical institutions; use big data and fee advantages to screen doctors to match users' consultation needs instead of screening by the rank of doctors only; and cooperate with commercial insurance providers to provide innovative health care packages.

Evaluation of Support, a self-guided online type 1 diabetes self-management education and support web application-a mixed methods study

Background

Type 1 diabetes requires making numerous daily decisions to maintain normoglycemia. Support is an evidence-based self-guided web application for type 1 diabetes diabetes self-management.

Objective

Evaluate users' satisfaction with Support and investigate changes in self-reported frequency of-, fear of- hypoglycemia, and diabetes-related self-efficacy.

Methods

Adults from a Quebec type 1 diabetes registry used Support. Data was collected through online surveys or extracted from the registry at 0, 6, and 12 months (number of episodes and fear of hypoglycemia). At 6 months, participants reported satisfaction with Support and diabetes-related self-efficacy. A sub-group of 16 users was interviewed about their experience. Transcripts were analyzed using inductive and deductive approaches.

Results

In total, 207 accounts were created (35% men, 96% White, mean age and diabetes duration: 49.3 ± 13.8 and 25.2 ± 14.7 years). At 6 months, the median [Q1; Q3] satisfaction was 40/49 [35; 45] with a mean decrease in hypoglycemia frequency of 0.43 episodes over 3 days (95% CI: -0.86; 0.00, p = 0.051) and of -1.98 score for fear (95% CI: -3.76; -0.20, p = 0.030). Half of the participants reported increased diabetes-related self-efficacy.

Conclusions

Participants reported a high level of satisfaction with Support. Its use has the potential to facilitate hypoglycemia management and increase diabetes-related self-efficacy.

Trial registration

This study is registered on ClinicalTrials.gov NCT04233138.

Prognostic Value of Histological and Immunohistochemical Data in Diabetic Foot Ulcers

Diabetic foot ulcers are an extremely urgent medical and social problem throughout the world. The purpose of this study was to analyse the histological and immunohistochemical features of tissues and cells of different sections of wounds taken during the primary surgical treatment of chronic wounds in patients with diabetic foot syndrome with favourable and unfavourable outcomes.

MATERIAL AND METHODS

A clinical prospective observational study of the treatment outcomes of fifty-three patients with diabetic foot ulcers hospitalized twice in one specialized centre over the course of the year was conducted. The analysis of histological and immunohistochemical data of the tissues of the edges and the centre of the ulcer taken during the primary surgical treatment was performed. While performing histological analyses of wound tissues, special attention was given to the determination of cellular characteristics of leukocyte-necrotic masses, granulation tissue, and loose and dense connective tissue. Immunohistochemistry was performed using a set of monoclonal antibodies, allowing verification of neutrophilic leukocytes, fibroblasts, and endothelial cells.

RESULTS

Unfavourable outcomes (amputation, reamputation, death from cardiovascular diseases, nonhealing ulcer within a year) were registered in 52.8% of cases. Uniform distribution of neutrophils and endothelial cell fibroblasts in all parts of the wound was recorded in patients with a favourable outcome. An unfavourable outcome was predetermined by the uneven content of these cells with a significant increase in neutrophilic leukocytosis in the bottom of the wounds, as well as a significant decrease in the number of fibroblasts and endotheliocytes in the centre of the wounds.

CONCLUSIONS

The datasets obtained during primary surgical treatment are extremely informative to predict the outcome of the treatment of diabetic foot ulcers and indicate more active surgical strategies with the potential to reduce the treatment time, increase its effectiveness, and eventually make the treatment cost-effective.

Associations between e-health literacy and chronic disease self-management in older Chinese patients with chronic non-communicable diseases: a mediation analysis

BACKGROUND

Chronic non-communicable diseases (CNCDs) are an urgent public health issue in China, especially among older adults. Hence, self-management is crucial for disease progression and treatment. Electronic health (e-health) literacy and self-efficacy positively correlate with self-management. However, we know little about their underlying mechanisms in older adults with CNCDs.

OBJECTIVE

To explore the factors that influence chronic disease self-management (CDSM) and verify self-efficacy as the mediator between e-health literacy and self-management behavior in older patients with CNCDs.

METHODS

This cross-sectional study included 289 older patients with CNCDs from Hunan province, China, between July and November 2021. E-health literacy, self-efficacy, social support, and CDSM data were collected through questionnaires. The influence of each factor on CDSM was explored with multiple linear regression analysis. Intermediary effects were computed via a structural equation model.

RESULTS

The total CDSM score in the patients was 29.39 ± 9.60 and only 46 (15.92%) patients used smart healthcare devices. The regression analysis showed e-health literacy, self-efficacy, and social support were the factors that affected CDSM. Furthermore, the structural equation model revealed that self-efficacy directly affected CDSM (β = 0.45, P < 0.01), whereas e-health literacy affected it directly (β = 0.42, P < 0.01) and indirectly (β = 0.429, P < 0.01) through self-efficacy.

CONCLUSIONS

This study revealed that self-management among older patients with CNCDs is at a low level, and few of them use smart healthcare devices. Self-efficacy plays a partial intermediary role between e-health literacy and self-management in older patients with CNCDs. Thus, efforts to improve their CDSM by targeting e-health literacy may be more effective when considering self-efficacy.

Critical questions in diabetes management: What are the most compelling challenges and how can we handle them?

Background

The prevalence of diabetes mellitus is growing worldwide, showing almost a 10-fold increase in the last five decades. Despite advances in the understanding of the disease mechanisms, preventive measures, and treatment options, morbidity and mortality remain high. Moreover, the burden of uncontrolled glycemia and associated complications have a significant impact on healthcare costs. To be ready for the future and emerging issues in the management of diabetes and related disorders, a holistic approach is essential for the prevention of the next generations. So many challenges in the management of diabetes exist globally, which differ according to the health infrastructure, and cultural, economic, and sociodemographic status of the nations.

Conclusions

In this minireview and commentary on previously unaddressed needs relating to the management of diabetes, we discuss the ubiquitous and most compelling challenges and suggest potential solutions in the care of patients with diabetes.

Patients' Experience of New Technologies and Digitalization in Diabetes Care in Germany

BACKGROUND

Little is little known about how people with diabetes experience advancing digitization and new technologies in diabetes.

RESEARCH QUESTION

What are the attitudes of people with diabetes (or, in the case of children with diabetes, their parents) toward digitization and advancing technology in diabetology? What significant advantages and disadvantages do they see, and how do they assess current developments of digitization in diabetology (eg, hybrid closed-loop systems, do-It-Yourself (DIY) closed-loop systems, data protection, and data donation)?

MATERIAL AND METHOD

3,427 people with diabetes (47.7% female, 65.6% type 1 diabetes (T1D), 25.5% type 2 diabetes (T2D), 8.1% parents of children with diabetes; 0.8% other type of diabetes, age 49.2 ± 19.3 years) were interviewed with an online survey.

RESULTS

Overall, survey participants had a very positive attitude toward digitization (82.6%) and considered the potential for optimizing diabetology through digitization to be very high (78.8%). The highest rated advantages of digitization were "greater personal responsibility and self-determination in therapy" (80.0%), "better quality of treatment" (80.0%), and "better communication with the doctor/diabetes team" (77.3%), while the highest rated disadvantages were the "error-proneness of digital applications" (35.9%), the "risk of misuse of patient data" (32.3%) and the "fear that digitization will replace the doctor in many cases" (31.1%). The possibility of evaluating and analyzing glucose data by means of software, and AID systems, and the possibility of improving the interoperability of the various applications are currently rated as the most significant topics.

CONCLUSIONS

The vast majority of people with diabetes are very positive about new technologies in diabetology and expect that it will improve and simplify their diabetes therapy and reduce the burdens associated with diabetes. In particular, people with type 1 diabetes have high expectations for AID systems, viewing them as a kind of "technical cure" for their diabetes.

The Effects of a Lifestyle Intervention Supported by the InterWalk Smartphone App on Increasing Physical Activity Among Persons With Type 2 Diabetes: Parallel-Group, Randomized Trial

Background

Effective and sustainable implementation of physical activity (PA) in type 2 diabetes (T2D) health care has in general not been successful. Efficacious and contemporary approaches to support PA adherence and adoption are required.

Objective

The primary objective of this study was to investigate the effectiveness of including an app-based (InterWalk) approach in municipality-based rehabilitation to increase moderate-and-vigorous PA (MVPA) across 52 weeks compared with standard care among individuals with T2D.

Methods

The study was designed as a parallel-group, randomized trial with 52 weeks’ intervention and subsequent follow-up for effectiveness (52 weeks from baseline). Participants were recruited between January 2015 and December 2016 and randomly allocated (2:1) into 12 weeks of (1) standard care + InterWalk app–based interval walking training (IWT; IWT group; n=140), or (2) standard care + the standard exercise program (StC group; n=74). Following 12 weeks, the IWT group was encouraged to maintain InterWalk app–based IWT (3 times per week for 30-60 minutes) and the StC group was encouraged to maintain exercise without structured support. Moreover, half of the IWT group (IWTsupport group, n=54) received additional motivational support following the 12-week program until 52-week follow-up. The primary outcome was change in objectively measured MVPA time (minutes/day) from baseline to 52-week follow-up. Key secondary outcomes included changes in self-rated physical and mental health–related quality of life (HRQoL), physical fitness, weight, and waist circumference.

Results

Participants had a mean age of 59.6 (SD 10.6) years and 128/214 (59.8%) were men. No changes in MVPA time were observed from baseline to 52-week follow-up in the StC and IWT groups (least squares means [95% CI] 0.6 [–4.6 to 5.8] and –0.2 [–3.8 to 3.3], respectively) and no differences were observed between the groups (mean difference [95% CI] –0.8 [–8.1 to 6.4] minutes/day; P=.82). Physical HRQoL increased by a mean of 4.3 (95% CI 1.8 to 6.9) 12-item Short-Form Health Survey (SF-12) points more in the IWT group compared with the StC group (Benjamini-Hochberg adjusted P=.007) and waist circumference apparently decreased a mean of –2.3 (95% CI –4.1 to –0.4) cm more in the IWT group compared with the StC group but with a Benjamini-Hochberg adjusted P=.06. No between-group differences were observed among the remaining key secondary outcomes.

Conclusions

Among individuals with T2D referred to municipality-based lifestyle programs, randomization to InterWalk app–based IWT did not increase objectively measured MVPA time over 52 weeks compared with standard health care, although apparent benefits were observed for physical HRQoL.

Trial Registration

ClinicalTrials.gov NCT02341690; https://clinicaltrials.gov/ct2/show/NCT02341690

Factors Influencing the Desirability, Acceptability, and Adherence of Patients with Diabetes to Telemedicine

Background and Objectives: Telemedicine solutions have proven their value and efficacy in augmenting diabetes care. In addition to the availability of tools needed to implement telemedicine solutions for patients with diabetes, the patients’ desirability, acceptance, and adherence represent major burdens in implementing them. The main aim of this research is to evaluate which factors are influencing the desirability, acceptance, and adherence of patients with diabetes to telemedicine interventions in diabetes care. Materials and Methods: QTelemeDiab, a previously validated instrument for assessing patients’ desirability, acceptance, and adherence to telemedicine in diabetes care, was used on 114 enrolled patients with diabetes mellitus, in parallel with demographic, socio-economic, disease history, and psychometric data from all patients. Results: Left-skewed score distributions were observed for the QTelemeDiab total score (median = 166; skewness = −1.738), as well as all its components, thus denoting a high desirability, acceptance, and adherence towards telemedicine use. The presence of severe depression was associated with significant decreases in the QTelemeDiab score (148 vs. 167; p < 0.001), as well as on the desirability sub-score (101 vs. 115; p < 0.001) and adherence sub-score (30 vs. 35; p < 0.001). The presence of severe anxiety was associated with significant decreases in QTelemeDiab score (150 vs. 166), as well as the desirability sub-score (104 vs. 114; p = 0.008) and adherence sub-score (30 vs. 34; p = 0.012). Conclusions: There is a high desirability, acceptance, and adherence to the use of telemedicine interventions in patients with diabetes, both in special and in normal epidemiological settings. The presence of severe anxiety decreases the patient’s desirability, acceptance, and adherence, while the presence of severe depression decreases the patient’s desirability and adherence to the use of telemedicine interventions in diabetes care.

What Intervention Elements Drive Weight Loss in Blended-Care Behavior Change Interventions? A Real-World Data Analysis with 25,706 Patients

Background: Blended-care behavior change interventions (BBCI) are a combination of digital care and coaching by health care professionals (HCP), which are proven effective for weight loss. However, it remains unclear what specific elements of BBCI drive weight loss. Objectives: This study aims to identify the distinct impact of HCP-elements (coaching) and digital elements (self-monitoring, self-management, and education) for weight loss in BBCI. Methods: Long-term data from 25,706 patients treated at a digital behavior change provider were analyzed retrospectively using a ridge regression model to predict weight loss at 3, 6, and 12 months. Results: Overall relative weight loss was −1.63 kg at 1 month, −3.61 kg at 3 months, −5.28 kg at 6 months, and −6.55 kg at 12 months. The four factors of BBCI analyzed here (coaching, self-monitoring, self-management, and education) predict weight loss with varying accuracy and degree. Coaching, self-monitoring, and self-management are positively correlated with weight losses at 3 and 6 months. Learn time (i.e., self-guided education) is clearly associated with a higher degree of weight loss. Number of appointments outside of app coaching with a dietitian (coach) was negatively associated with weight loss. Conclusions: The results testify to the efficacy of BBCI for weight loss-with particular positive associations per time point-and add to a growing body of research that characterizes the distinct impact of intervention elements in real-world settings, aiming to inform the design of future interventions for weight management.

Glucose trajectory prediction by deep learning for personal home care of type 2 diabetes mellitus: modelling and applying

Glucose management for people with type 2 diabetes mellitus is essential but challenging due to the multi-factored and chronic disease nature of diabetes. To control glucose levels in a safe range and lessen abnormal glucose variability efficiently and economically, an intelligent prediction of glucose is demanding. A glucose trajectory prediction system based on subcutaneous interstitial continuous glucose monitoring data and deep learning models for ensuing glucose trajectory was constructed, followed by the application of personalised prediction models on one participant with type 2 diabetes in a community. The predictive accuracy was then assessed by RMSE (root mean square error) using blood glucose data. Changes in glycaemic parameters of the participant before and after model intervention were also compared to examine the efficacy of this intelligence-aided health care. Individual Recurrent Neural Network model was developed on glucose data, with an average daily RMSE of 1.59 mmol/L in the application segment. In terms of the glucose variation, the mean glucose decreased by 0.66 mmol/L, and HBGI dropped from 12.99 × 10² to 9.17 × 10². However, the participant also had increased stress, especially in eating and social support. Our research presented a personalised care system for people with diabetes based on deep learning. The intelligence-aided health management system is promising to enhance the outcome of diabetic patients, but further research is also necessary to decrease stress in the intelligence-aided health management and investigate the stress impacts on diabetic patients.

Structured diabetes self-management education and its association with perceived diabetes knowledge, information, and disease distress: Results of a nationwide population-based study

OBJECTIVE

To evaluate, how participation in structured diabetes self-management education (DSME) programs is associated with perceived level of knowledge about diabetes, information needs, information sources and disease distress.

METHODS

We included 796 ever- and 277 never-DSME participants of the population-based survey "Disease knowledge and information needs - Diabetes mellitus (2017)" from Germany. Data on perceived level of diabetes knowledge (12 items), information needs (11 items), information sources (13 items) and disease distress (2 indices) were collected. Multiple logistic regression analyses were used to examine the association of DSME-participation with these outcomes.

RESULTS

DSME-participants showed a higher level of diabetes knowledge compared to never-DSME participants, particularly in aspects concerning diabetes in general (odds ratio 2.53; 95% confidence intervals 1.48-4.33), treatment (2.41; 1.36-4.26), acute complications (1.91; 1.07-3.41) and diabetes in everyday life (1.83; 1.04-3.22). DSME-participants showed higher information needs regarding late complications (1.51; 1.04-2.18) and acute complications (1.71; 1.71-2.48) than DSME never participants. DSME-participants more frequently consulted diabetologists (5.54; 3.56-8.60) and diabetes care specialists (5.62; 3.61-8.75) as information sources. DSME participation was not associated with disease distress.

CONCLUSION

DSME is a valuable tool for improving individual knowledge about diabetes. However, DSME should focus more on psychosocial aspects to reduce the disease burden.

Effectiveness of Digital Counseling Environments on Anxiety, Depression, and Adherence to Treatment Among Patients Who Are Chronically Ill: Systematic Review

Background

Patients who are chronically ill need novel patient counseling methods to support their self-care at different stages of the disease. At present, knowledge of how effective digital counseling is at managing patients’ anxiety, depression, and adherence to treatment seems to be fragmented, and the development of digital counseling will require a more comprehensive view of this subset of interventions.

Objective

This study aims to identify and synthesize the best available evidence on the effectiveness of digital counseling environments at improving anxiety, depression, and adherence to treatment among patients who are chronically ill.

Methods

Systematic searches of the EBSCO (CINAHL), PubMed, Scopus, and Web of Science databases were conducted in May 2019 and complemented in October 2020. The review considered studies that included adult patients aged ≥18 years with chronic diseases; interventions evaluating digital (mobile, web-based, and ubiquitous) counseling interventions; and anxiety, depression, and adherence to treatment, including clinical indicators related to adherence to treatment, as outcomes. Methodological quality was assessed using the standardized Joanna Briggs Institute critical appraisal tool for randomized controlled trials or quasi-experimental studies. As a meta-analysis could not be conducted because of considerable heterogeneity in the reported outcomes, narrative synthesis was used to synthesize the results.

Results

Of the 2056 records screened, 20 (0.97%) randomized controlled trials, 4 (0.19%) pilot randomized controlled trials, and 2 (0.09%) quasi-experimental studies were included. Among the 26 included studies, 10 (38%) digital, web-based interventions yielded significantly positive effects on anxiety, depression, adherence to treatment, and the clinical indicators related to adherence to treatment, and another 18 (69%) studies reported positive, albeit statistically nonsignificant, changes among patients who were chronically ill. The results indicate that an effective digital counseling environment comprises high-quality educational materials that are enriched with multimedia elements and activities that engage the participant in self-care. Because of the methodological heterogeneity of the included studies, it is impossible to determine which type of digital intervention is the most effective for managing anxiety, depression, and adherence to treatment.

Conclusions

This study provides compelling evidence that digital, web-based counseling environments for patients who are chronically ill are more effective than, or at least comparable to, standard counseling methods; this suggests that digital environments could complement standard counseling.

In-person and virtual multidisciplinary intensive lifestyle interventions are equally effective in patients with type 2 diabetes and obesity

BACKGROUND

Intensive lifestyle intervention (ILI) is essential for diabetes management. The Weight Achievement and Intensive Treatment (Why WAIT) program is a 12-week multidisciplinary weight management program that has been implemented in real-world clinical practice since 2005 and has shown long-term maintenance of weight reduction for 5 and 10 years. During the COVID-19 pandemic, the program went virtual using telemedicine and mobile health applications.

AIMS

This retrospective pilot study aims to evaluate the effectiveness of a virtual model of an already established and successful in-person program for diabetes and weight management since 2005.

METHODS

We evaluated 38 patients with diabetes and obesity enrolled in the Why WAIT program between February 2019 and December 2020. Sixteen participants were enrolled in virtual program (VP) and were compared with 22 participants who completed the latest two physical programs (PPs) before COVID-19. We evaluated changes in body weight, A1C, blood pressure (BP), and lipid profile after 12 weeks of ILI.

RESULTS

Body weight decreased by -7.4 ± 3.6 kg from baseline in VP compared with -6.8 ± 3.5 kg in PP (p = 0.6 between groups). A1C decreased by -1.03% ± 1.1% from baseline in VP, and by -1.0% ± 1.2% in PP (p = 0.9 between groups). BP, lipid profile, and all other parameters improved in both groups with no significant difference between them.

CONCLUSION

Virtual multidisciplinary ILI is as effective as the in-person intervention program in improving body weight, A1C, BP, and lipid profile, and in reducing the number of anti-hyperglycemic medications. Results from our study suggest that scaling the Why WAIT program in a virtual format to a larger population of patients with diabetes and obesity is feasible and is potentially as successful as the in-person program.

Popularization of Medical Information

Objectives

Despite the popularization of technology and the high penetration rate of smartphones and mobile devices, differences exist in the accessibility, utilization capabilities, and quality of technology depending on users’ characteristics. Since these discrepancies can threaten health information equity, popularization of medical information is essential. This review article examines domestic and international cases of popularization of medical information, and discusses the related issues, expectations, and practical measures to achieve the popularization of medical information.

Methods

In this study, medical information was categorized as Electronic Health Records/Electronic Medical Records (EHR/EMRs; hospital-driven medical information), personal health records (PHRs; user-driven medical information), and patient-generated health data (PGHD; user-generated medical information [outside hospitals]). This article reviewed the domestic and international use status, acceptance rates, and use cases for each type of medical information. Issues and expectations about policies and cases related to the popularization of medical information were also described, and finally, practical measures to accomplish the popularization of medical information were discussed.

Results

To achieve the popularization of medical information, the following measures should be considered: engaging health consumers to participate in the early stages of information production, cultivating digital literacy, producing easy-to-use and interesting medical content, visualizing health information, and creating a medical thesaurus.

Conclusions

Healthcare providers should make regular efforts to popularize medical information. The popularization of medical information is an essential process to achieve health equity and digital health equity.

Type 1 diabetes mellitus: much progress, many opportunities

As part of the centennial celebration of insulin's discovery, this review summarizes the current understanding of the genetics, pathogenesis, treatment, and outcomes in type 1 diabetes (T1D). T1D results from an autoimmune response that leads to destruction of the β cells in the pancreatic islet and requires lifelong insulin therapy. While much has been learned about T1D, it is now clear that there is considerable heterogeneity in T1D with regard to genetics, pathology, response to immune-based therapies, clinical course, and susceptibility to diabetes-related complications. This Review highlights knowledge gaps and opportunities to improve the understanding of T1D pathogenesis and outlines emerging therapies to treat or prevent T1D and reduce the burden of T1D.

Oral GLP1 Analog: Where Does the Tide Go?

T2D is a potentially preventable disease that has been ranked the seventh leading cause of mortality in the United States. There is strong evidence demonstrating that preventing type 2 diabetes is, in many cases, attainable through lifestyle intervention. Unfortunately, prediabetes is mostly overlooked and awareness with diabetes prevention tools is lacking among primary care physicians. Nationally, efforts were not successful in reversing this epidemic even with an array of diabetes medications. Among the most effective medications for T2D are glucagon-like peptide-1 receptor agonists (GLP-1 RAs), which have been shown to reduce both A1C and body weight. Dulaglutide, liraglutide and injectable semaglutide also reduced cardiovascular events and cardiovascular mortality in patients with established cardiovascular disease or multiple cardiovascular risk factors. In this review, we will examine the first FDA approved oral GLP-1 RA; semaglutide. Moreover, this review will discuss the potential impact oral semaglutide may have on glycemic control, weight loss and cardiovascular comorbidities. It also examines the factors that may impact patient compliance, including cost, side effects and clinical issues. Finally, it deliberates the optimism surrounding the development of oral semaglutide in the treatment of diabetes as well as related conditions, such as obesity and non-alcoholic fatty liver disease (NAFLD).

Diabetes clinic reinvented: will technology change the future of diabetes care?

Diabetes is a chronic disease that affects nearly 463 million people globally and involves multiple co-morbid conditions that require effective treatment and continuous management. These include lifestyle and behavioral modifications, compliance to diabetes medications and close patient monitoring, all of which can be efficiently conducted via telehealth. Integrating digital technology of telehealth and mobile health into diabetes care may improve diabetes management and increase its efficiency. In this review, we examine recent advances in healthcare technology of diabetes. Moreover, we present an example of a comprehensive virtual diabetes clinic, the "Joslin HOME," as an innovative digital ecosystem for future application in diabetes care. This model utilizes digital health technology and comprises frequent short visits with easy two-way scheduling, focused documentation and simple billing methods. In this new model, a multidisciplinary team is connected with their patients using telehealth and mobile health to overcome the barriers of distance and location. It may possibly extend quality diabetes care to remote, underserved or rural areas.

Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices

BACKGROUND

The aim of a recent research project was the investigation of the mechanisms involved in the onset of type 2 diabetes in the absence of familiarity. This has led to the development of a computational model that recapitulates the aetiology of the disease and simulates the immunological and metabolic alterations linked to type-2 diabetes subjected to clinical, physiological, and behavioural features of prototypical human individuals.

RESULTS

We analysed the time course of 46,170 virtual subjects, experiencing different lifestyle conditions. We then set up a statistical model able to recapitulate the simulated outcomes.

CONCLUSIONS

The resulting machine learning model adequately predicts the synthetic dataset and can, therefore, be used as a computationally-cheaper version of the detailed mathematical model, ready to be implemented on mobile devices to allow self-assessment by informed and aware individuals. The computational model used to generate the dataset of this work is available as a web-service at the following address: http://kraken.iac.rm.cnr.it/T2DM .

Health Technology Readiness Profiles Among Danish Individuals With Type 2 Diabetes: Cross-Sectional Study

Background

Information technologies (IT) are increasingly implemented in type 2 diabetes (T2D) treatment as a resource for remotely supported health care. However, possible pitfalls of introducing IT in health care are generally overlooked. Specifically, the effectiveness of IT to improve health care may depend on the user’s readiness for health technology.

Objective

We aim to investigate readiness for health technology in relation to mental well-being, sociodemographic, and disease-related characteristics among individuals with T2D.

Methods

Individuals with T2D (aged ≥18 years) who had been referred to self-management education, exercise, diet counseling, smoking cessation, or alcohol counseling completed a questionnaire survey covering (1) background information, (2) the 5-item World Health Organization Well-Being Index (WHO-5), (3) receptiveness to IT use in physical activity, and (4) the Readiness and Enablement Index for Health Technology (READHY), constituted by dimensions related to self-management, social support, and eHealth literacy. Individuals were divided into profiles using cluster analysis based on their READHY scores. Outcomes included differences across profiles in mental well-being, sociodemographic, and disease-related characteristics.

Results

Participants in the study were 155 individuals with T2D with a mean age of 60.2 (SD 10.7) years, 55.5% (86/155) of which were men and 44.5% (69/155) of which were women. Participants were stratified into 5 health technology readiness profiles based on the cluster analysis: Profile 1, high health technology readiness; Profile 2, medium health technology readiness; Profile 3, medium health technology readiness and high level of emotional distress; Profile 4, medium health technology readiness and low-to-medium eHealth literacy; Profile 5, low health technology readiness. No differences in sociodemographic and disease-related characteristics were observed across profiles; however, we identified 3 vulnerable subgroups of individuals: Profile 3 (21/155, 13.5%), younger individuals (mean age of 53.4 years, SD 8.9 years) with low mental well-being (mean 42.7, SD 14.7) and emotional distress (mean 1.69, SD 0.38); Profile 4 (20/155, 12.9%), older individuals (mean age 66.3 years, SD 9.0 years) with less IT use (50.0% used IT for communication) and low-to-medium eHealth literacy; and Profile 5 (36/155, 23.2%) with low mental well-being (mean 43.4, SD 20.1) and low readiness for health technology.

Conclusions

Implementation of IT in health care of individuals with T2D should be based on comprehensive consideration of mental well-being, emotional distress, and readiness for health technology rather than sociodemographic and disease-related characteristics to identify the individuals in need of social support, self-management education, and extensive IT support. A one-size-fits-all approach to IT implementation in health care will potentially increase the risk of treatment failure among the most vulnerable individuals.

The present and future scope of real-world evidence research in diabetes: What questions can and cannot be answered and what might be possible in the future?

The last decade has witnessed an exponential growth in the opportunities to collect and link health-related data from multiple resources, including primary care, administrative, and device data. The availability of these "real-world," "big data" has fuelled also an intense methodological research into methods to handle them and extract actionable information. In medicine, the evidence generated from "real-world data" (RWD), which are not purposely collected to answer biomedical questions, is commonly termed "real-world evidence" (RWE). In this review, we focus on RWD and RWE in the area of diabetes research, highlighting their contributions in the last decade; and give some suggestions for future RWE diabetes research, by applying well-established and less-known tools to direct RWE diabetes research towards better personalized approaches to diabetes care. We underline the essential aspects to consider when using RWD and the key features limiting the translational potential of RWD in generating high-quality and applicable RWE. Only if viewed in the context of other study designs and statistical methods, with its pros and cons carefully considered, RWE will exploit its full potential as a complementary or even, in some cases, substitutive source of evidence compared to the expensive evidence obtained from randomized controlled trials.