Proactive Identification of Patients with Diabetes at Risk of Uncontrolled Outcomes during a Diabetes Management Program: Conceptualization and Development Study Using Machine Learning

BACKGROUND

The growth in the capabilities of telehealth have made it possible to identify individuals with a higher risk of uncontrolled diabetes and provide them with targeted support and resources to help them manage their condition. Thus, predictive modeling has emerged as a valuable tool for the advancement of diabetes management.

OBJECTIVE

This study aimed to conceptualize and develop a novel machine learning (ML) approach to proactively identify participants enrolled in a remote diabetes monitoring program (RDMP) who were at risk of uncontrolled diabetes at 12 months in the program.

METHODS

Registry data from the Livongo for Diabetes RDMP were used to design separate dynamic predictive ML models to predict participant outcomes at each monthly checkpoint of the participants' program journey (month-n models) from the first day of onboarding (month-0 model) up to the 11th month (month-11 model). A participant's program journey began upon onboarding into the RDMP and monitoring their own blood glucose (BG) levels through the RDMP-provided BG meter. Each participant passed through 12 predicative models through their first year enrolled in the RDMP. Four categories of participant attributes (ie, survey data, BG data, medication fills, and health signals) were used for feature construction. The models were trained using the light gradient boosting machine and underwent hyperparameter tuning. The performance of the models was evaluated using standard metrics, including precision, recall, specificity, the area under the curve, the F1-score, and accuracy.

RESULTS

The ML models exhibited strong performance, accurately identifying observable at-risk participants, with recall ranging from 70% to 94% and precision from 40% to 88% across the 12-month program journey. Unobservable at-risk participants also showed promising performance, with recall ranging from 61% to 82% and precision from 42% to 61%. Overall, model performance improved as participants progressed through their program journey, demonstrating the importance of engagement data in predicting long-term clinical outcomes.

CONCLUSIONS

This study explored the Livongo for Diabetes RDMP participants' temporal and static attributes, identification of diabetes management patterns and characteristics, and their relationship to predict diabetes management outcomes. Proactive targeting ML models accurately identified participants at risk of uncontrolled diabetes with a high level of precision that was generalizable through future years within the RDMP. The ability to identify participants who are at risk at various time points throughout the program journey allows for personalized interventions to improve outcomes. This approach offers significant advancements in the feasibility of large-scale implementation in remote monitoring programs and can help prevent uncontrolled glycemic levels and diabetes-related complications. Future research should include the impact of significant changes that can affect a participant's diabetes management.

Implementation of an Electronic Clinical Decision Support System for the Early Recognition and Management of Dysglycemia in an Inpatient Mental Health Setting Using CogStack: Protocol for a Pilot Hybrid Type 3 Effectiveness-Implementation Randomized Controlled Cluster Trial

BACKGROUND

Severe mental illnesses (SMIs), including schizophrenia, bipolar affective disorder, and major depressive disorder, are associated with an increased risk of physical health comorbidities and premature mortality from conditions including cardiovascular disease and diabetes. Digital technologies such as electronic clinical decision support systems (eCDSSs) could play a crucial role in improving the clinician-led management of conditions such as dysglycemia (deranged blood sugar levels) and associated conditions such as diabetes in people with a diagnosis of SMI in mental health settings.

OBJECTIVE

We have developed a real-time eCDSS using CogStack, an information retrieval and extraction platform, to automatically alert clinicians with National Health Service Trust-approved, guideline-based recommendations for dysglycemia monitoring and management in secondary mental health care. This novel system aims to improve the management of dysglycemia and associated conditions, such as diabetes, in SMI. This protocol describes a pilot study to explore the acceptability, feasibility, and evaluation of its implementation in a mental health inpatient setting.

METHODS

This will be a pilot hybrid type 3 effectiveness-implementation randomized controlled cluster trial in inpatient mental health wards. A ward will be the unit of recruitment, where it will be randomly allocated to receive either access to the eCDSS plus usual care or usual care alone over a 4-month period. We will measure implementation outcomes, including the feasibility and acceptability of the eCDSS to clinicians, as primary outcomes, alongside secondary outcomes relating to the process of care measures such as dysglycemia screening rates. An evaluation of other implementation outcomes relating to the eCDSS will be conducted, identifying facilitators and barriers based on established implementation science frameworks.

RESULTS

Enrollment of wards began in April 2022, after which clinical staff were recruited to take part in surveys and interviews. The intervention period of the trial began in February 2023, and subsequent data collection was completed in August 2023. Data are currently being analyzed, and results are expected to be available in June 2024.

CONCLUSIONS

An eCDSS can have the potential to improve clinician-led management of dysglycemia in inpatient mental health settings. If found to be feasible and acceptable, then, in combination with the results of the implementation evaluation, the system can be refined and improved to support future successful implementation. A larger and more definitive effectiveness trial should then be conducted to assess its impact on clinical outcomes and to inform scalability and application to other conditions in wider mental health care settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04792268; https://clinicaltrials.gov/study/NCT04792268.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49548.

Potassium permanganate in treatment of diabetic foot ulcer: A randomized clinical trial

Background and Aims

Diabetic foot ulcers (DFU) are a severe complication in diabetes patients, often resulting in significant morbidity and mortality due to non-healing. This study investigated the effectiveness of 5% topical potassium permanganate on these ulcers.

Methods

A clinical trial was conducted on 23 patients with Wagner grade I and II DFU. Patients in the control group received standard treatment, while those in the intervention group also received 5% potassium permanganate topically. Data were recorded at 0, 7, 14, and 21 days for analysis.

Results

Among 23 patients studied, 7 (30.4%) were male and 16 (43.7%) female, with an average age of 59 ± 4 years. Both groups showed a statistically significant decrease in wound size and infection over time (p < 0.001). The intervention group, however, had a more substantial reduction in wound size and infection rate (p < 0.05).

Conclusion

Potassium permanganate, when applied topically, is both well-tolerated and effective in enhancing wound healing and reducing infection in DFU, suggesting its potential as a complementary treatment.

Target Product Profile for a Machine Learning-Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study

BACKGROUND

Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation.

OBJECTIVE

This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England.

METHODS

This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence's Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from "definitely exclude" to "definitely include," and suggest edits. The document will be iterated between rounds based on participants' feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote.

RESULTS

Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024.

CONCLUSIONS

The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50568.

HMGB1-RAGE axis contributes to myocardial ischemia/reperfusion injury via regulation of cardiomyocyte autophagy and apoptosis in diabetic mice

Patients with acute myocardial infarction complicated with diabetes are more likely to develop myocardial ischemia/reperfusion (I/R) injury (MI/RI) during reperfusion therapy. Both HMGB1 and RAGE play important roles in MI/RI. However, the specific mechanisms of HMGB1 associated with RAGE are not fully clarified in diabetic MI/RI. This study aimed to investigate whether the HMGB1-RAGE axis induces diabetic MI/RI via regulating autophagy and apoptosis. A db/db mouse model of MI/RI was established, where anti-HMGB1 antibody and RAGE inhibitor (FPS-ZM1) were respectively injected after 10 min of reperfusion. The results showed that treatment with anti-HMGB1 significantly reduced the infarct size, serum LDH, and CK-MB level. Similar situations also occurred in mice administrated with FPS-ZM1, though the HMGB1 level was unchanged. Then, we found that treatment with anti-HMGB1 or FPS-ZM1 performed the same effects in suppressing the autophagy and apoptosis, as reflected by the results of lower LAMP2 and LC3B levels, increased Bcl-2 level, reduced BAX and caspase-3 levels. Moreover, the Pink1/Parkin levels were also inhibited at the same time. Collectively, this study indicates that the HMGB1-RAGE axis aggravated diabetic MI/RI via apoptosis and Pink1/Parkin mediated autophagy pathways, and inhibition of HMGB1 or RAGE contributes to alleviating those adverse situations.

Topical Insulin for Ocular Surface Disease

Background: Insulin and insulin-like growth factor (IGF)-1 receptors are present in ocular tissues such as corneal epithelium, keratocytes, and conjunctival cells. Insulin plays a crucial role in the growth, differentiation, and proliferation of corneal epithelial cells, as well as in wound healing processes in various tissues. Purpose: This review explores the potential role of topical insulin in the treatment of ocular surface diseases. Specifically, it examines its impact on corneal nerve regeneration, sub-basal plexus corneal nerves, and its application in conditions like corneal epithelial defects, dry eye disease, and diabetic keratopathy. Methods: The review analyzes studies conducted over the past decade that have investigated the use of topical insulin in ocular surface diseases. It focuses on indications, drug preparation methods, side effects, efficacy outcomes, and variations in insulin concentrations and dosages used. Results: While off-label use of topical insulin has shown promising results in refractory corneal epithelial defects, its efficacy in dry eye disease is yet to be demonstrated. Variations in concentrations, dilutions, and dosing guidelines have been reported. However, limited data on ocular penetration, ocular toxicity, and systemic side effects pose challenges to its widespread utility. Conclusion: This review synthesizes findings from ocular investigations on topical insulin to assess its potential applicability in treating ocular surface and corneal diseases. By highlighting indications, preparation methods, side effects, and efficacy outcomes, it aims to provide insights into the current status and future prospects of using topical insulin in ophthalmic practice.

Leveraging Generative AI Tools to Support the Development of Digital Solutions in Health Care Research: Case Study

BACKGROUND

Generative artificial intelligence has the potential to revolutionize health technology product development by improving coding quality, efficiency, documentation, quality assessment and review, and troubleshooting.

OBJECTIVE

This paper explores the application of a commercially available generative artificial intelligence tool (ChatGPT) to the development of a digital health behavior change intervention designed to support patient engagement in a commercial digital diabetes prevention program.

METHODS

We examined the capacity, advantages, and limitations of ChatGPT to support digital product idea conceptualization, intervention content development, and the software engineering process, including software requirement generation, software design, and code production. In total, 11 evaluators, each with at least 10 years of experience in fields of study ranging from medicine and implementation science to computer science, participated in the output review process (ChatGPT vs human-generated output). All had familiarity or prior exposure to the original personalized automatic messaging system intervention. The evaluators rated the ChatGPT-produced outputs in terms of understandability, usability, novelty, relevance, completeness, and efficiency.

RESULTS

Most metrics received positive scores. We identified that ChatGPT can (1) support developers to achieve high-quality products faster and (2) facilitate nontechnical communication and system understanding between technical and nontechnical team members around the development goal of rapid and easy-to-build computational solutions for medical technologies.

CONCLUSIONS

ChatGPT can serve as a usable facilitator for researchers engaging in the software development life cycle, from product conceptualization to feature identification and user story development to code generation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500.

Healing rates and outcomes following closed transmetatarsal amputations: A systematic review and random effects meta-analysis of proportions

Transmetatarsal amputation (TMA) is a common surgical procedure for addressing severe forefoot pathologies, such as peripheral vascular disease and diabetic foot infections. Variability in research methodologies and findings within the existing literature has hindered a comprehensive understanding of healing rates and complications following TMA. This meta-analysis and systematic review aims to consolidate available evidence, synthesising data from multiple studies to assess healing rates and complications associated with closed TMA procedures. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a systematic search of Medline, Embase, and Cochrane databases was conducted for articles published from January 1st, 1988, to June 1st, 2023. Inclusion criteria comprised studies reporting healing rates in non-traumatic transmetatarsal amputation patients with more than 10 participants, excluding open TMAs. Two independent reviewers selected relevant studies, with disagreements resolved through discussion. Data extracted from eligible studies included patient demographics, healing rates, complications, and study quality. Among 22 studies encompassing 1569 transmetatarsal amputations, the pooled healing rate was 67.3%. Major amputation rates ranged from 0% to 55.6%, with a random-effects pooled rate of 23.9%. Revision rates varied from 0% to 36.4%, resulting in a pooled rate of 14.8%. 30-day mortality ranged from 0% to 9%, with a fixed-effects pooled rate of 2.6%. Post-operative infection rates ranged from 3.0% to 30.7%, yielding a random-effects pooled rate of 16.7%. Dehiscence rates ranged from 1.7% to 60.0%, resulting in a random-effects pooled rate of 28.8%. Future studies should aim for standardised reporting and assess the physiological and treatment factors influencing healing and complications.

Development of a requirement for exogenous insulin treatment in dogs with hyperglycemia

BACKGROUND

It has been suggested that overt diabetes mellitus in dogs be defined based on a persistent fasting blood glucose concentration (BGC) >144 mg/dL.

OBJECTIVE

Determine the number of dogs with randomly identified hyperglycemia without insulin-treated diabetes mellitus (ITDM) that later develop a need for exogenous insulin treatment.

ANIMALS

A total of 1318 dogs examined at a university teaching hospital without ITDM and with randomly identified hyperglycemia.

METHODS

Retrospective longitudinal study. Hyperglycemia was defined as randomly identified BGC above >112 mg/dL, moderate hyperglycemia as BGC >144 mg/dL but <200 mg/dL and pronounced hyperglycemia as BGC ≥200 mg/dL. Dogs were defined as having ITDM if they were treated with insulin. Follow-up was attempted 7 to 12 years after hyperglycemia was documented to determine if over time dogs developed a need for exogenous insulin treatment.

RESULTS

Twenty-nine of 824 dogs (3.5%) with hyperglycemia and follow-up information developed ITDM, including 3/824 dogs (0.4%) with moderate hyperglycemia, and 2/824 dogs (0.2%) with pronounced hyperglycemia. Most dogs with hyperglycemia that developed ITDM (24/29, 83%) had BGC ≤144 mg/dL. Among dogs that eventually developed a need for exogenous insulin treatment, no association was found between the degree of hyperglycemia and the time interval between documentation of hyperglycemia and diagnosis of ITDM. Logistic regression determined that BGC is not significantly associated with ITDM.

CONCLUSIONS AND CLINICAL IMPORTANCE

Most dogs with randomly identified hyperglycemia did not develop a need for exogenous insulin treatment. Other criteria could be required to augment the definition of overt DM in non-insulin treated dogs.

User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the world. Common comorbidities are central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome. Cardiovascular disease is the most common cause of death among people with NAFLD, and lifestyle changes can improve health outcomes.

OBJECTIVE

This study aims to explore the acceptability of a digital health program in terms of engagement, retention, and user satisfaction in addition to exploring changes in clinical outcomes, such as weight, cardiometabolic risk factors, and health-related quality of life.

METHODS

We conducted a prospective, open-label, single-arm, 12-week study including 38 individuals with either a BMI >30, metabolic syndrome, or type 2 diabetes mellitus and NAFLD screened by FibroScan. An NAFLD-specific digital health program focused on disease education, lowering carbohydrates in the diet, food logging, increasing activity level, reducing stress, and healthy lifestyle coaching was offered to participants. The coach provided weekly feedback on food logs and other in-app activities and opportunities for participants to ask questions. The coaching was active throughout the 12-week intervention period. The primary outcome was feasibility and acceptability of the 12-week program, assessed through patient engagement, retention, and satisfaction with the program. Secondary outcomes included changes in weight, liver fat, body composition, and other cardiometabolic clinical parameters at baseline and 12 weeks.

RESULTS

In total, 38 individuals were included in the study (median age 59.5, IQR 46.3-68.8 years; n=23, 61% female). Overall, 34 (89%) participants completed the program and 29 (76%) were active during the 12-week program period. The median satisfaction score was 6.3 (IQR 5.8-6.7) of 7. Mean weight loss was 3.5 (SD 3.7) kg (P<.001) or 3.2% (SD 3.4%), with a 2.2 (SD 2.7) kg reduction in fat mass (P<.001). Relative liver fat reduction was 19.4% (SD 23.9%). Systolic blood pressure was reduced by 6.0 (SD 13.5) mmHg (P=.009). The median reduction was 0.14 (IQR 0-0.47) mmol/L for triglyceride levels (P=.003), 3.2 (IQR 0.0-5.4) µU/ml for serum insulin (s-insulin) levels (P=.003), and 0.5 (IQR -0.7 to 3.8) mmol/mol for hemoglobin A1c (HbA1c) levels (P=.03). Participants who were highly engaged (ie, who used the app at least 5 days per week) had greater weight loss and liver fat reduction.

CONCLUSIONS

The 12-week-long digital health program was feasible for individuals with NAFLD, receiving high user engagement, retention, and satisfaction. Improved liver-specific and cardiometabolic health was observed, and more engaged participants showed greater improvements. This digital health program could provide a new tool to improve health outcomes in people with NAFLD.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05426382; https://clinicaltrials.gov/study/NCT05426382.

Hypoglycemic Effects and Quality Marker Screening of Dendrobium nobile Lindl. at Different Growth Years

(1) Background: The effect of Dendrobium nobile Lindl. (D. nobile) on hyperglycemic syndrome has only been recently known for several years. Materials of D. nobile were always collected from the plants cultivated in various growth ages. However, regarding the efficacy of D. nobile on hyperglycemic syndrome, it was still unknown as to which cultivation age would be selected. On the other hand, with the lack of quality markers, it is difficult to control the quality of D. nobile to treat hyperglycemic syndrome. (2) Methods: The effects of D. nobile cultivated at year 1 and year 3 were checked on alloxan-induced diabetic mice while their body weight, diet, water intake, and urinary output were monitored. Moreover, levels of glycosylated serum protein and insulin were measured using Elisa kits. The constituents of D. nobile were identified and analyzed by using UPLC-Q/trap. Quality markers were screened out by integrating the data from UPLC-Q/trap into a network pharmacology model. (3) Results: The D. nobile cultivated at both year 1 and year 3 showed a significant effect on hyperglycemic syndrome at the high dosage level; however, regarding the significant level, D. nobile from year 1 showed the better effect. In D. nobile, most of the metabolites were identified as alkaloids and sesquiterpene glycosides. Alkaloids, represented by dendrobine, were enriched in D. nobile from year 1, while sesquiterpene glycosides were enriched in D. nobile from year 3. Twenty one metabolites were differentially expressed between D. nobile from year 1 and year 3. The aforementioned 21 metabolites were enriched to 34 therapeutic targets directly related to diabetes. (4) Conclusions: Regarding the therapy for hyperglycemic syndrome, D. nobile cultivated at year 1 was more recommended than that at year 3. Alkaloids were recommended to be used as markers to control the quality of D. nobile for hyperglycemic syndrome treatment.

The potential effect of ambrisentan as monotherapy and combined with tadalafil on diabetic erectile dysfunction in rats

INTRODUCTION

This study investigated the role of ambrisentan; the selective endothelin type-A receptor (ETAR) blocker on experimental diabetic erectile dysfunction in rats.

MATERIALS AND METHODS

Eighty-four adult male Sprague Albino rats were divided randomly into 7 groups. Three control groups received 1 mL saline, 0.2 mg/kg/d ambrisentan and 1.5 mg/kg/d tadalafil, respectively orally for 4 weeks. The remaining four groups were fed high fat diet for 14 days. Diabetes was induced by a single intra-peritoneal injection of 40 mg/kg streptozotocin. After 72 h, diabetes was confirmed by plasma glucose level ⩾250 mg/dL. Diabetic rats were divided randomly into four groups, numbered from 4 to 7. The fourth group was the diabetic-control group, while the fifth and sixth groups received ambrisentan and tadalafil respectively. The seventh group received a combination of both drugs. Treatment continued for 4 weeks then, copulatory, intracavernous pressure measurement, and laboratory tests were conducted.

RESULTS

In diabetic rats, ambrisentan and tadalafil improved fasting glucose, insulin, insulin resistance, testosterone, nitric oxide, and rho kinase (ROCK) values compared to diabetic group with the maximum improvement achieved in ambrisentan/tadalafil group (p < 0.05). Ambrisentan also enhanced ICP and improved latency to erection and number of mounts with a tolerable SBP. Yet, ambrisentan/tadalafil combined therapy resulted in deterioration in SBP with consecutive worsening in ICP and mating indices.

CONCLUSION

Ambrisentan showed significant therapeutic potential to prevent and improve diabetic ED in rats comparable to tadalafil.

Urinary Vacuolar Casts Are a Unique Type of Casts in Advanced Proteinuric Glomerulopathies

Key Points

Vacuolar casts are a distinct type of casts identifiable by urinary sediment microscopy. Identification of urinary vacuolar casts is associated with the presence of an advanced and severe form of a proteinuric glomerular disease.

Background

Identification of casts by urinary sediment microscopy is a valuable diagnostic clinical tool for the evaluation of kidney disease. Vacuolar casts are an unrecognized unique type of casts characterized by the presence of nonpolarizable, clear vesicles of various sizes contained within a cast matrix, different from lipid casts, erythrocyte casts, or any other casts. We aimed to gain better understanding of the clinical relevance of these casts by establishing a multinational collaborative group to search for cases in which vacuolar casts were identified.

Methods

Leveraging an educational social media platform, we conducted a multinational observational study extracting cases of patients who presented with urinary vacuolar casts during evaluation for impaired kidney function. Parameters assessed included degree of proteinuria and kidney dysfunction, clinical and histopathological diagnosis, and severity of renal parenchymal scarring on biopsy. A control group of patients without vacuolar casts was included for comparison.

Results

Forty-six patients with urinary vacuolar casts were compiled from six countries. Nephrotic range proteinuria (82%), glomerular etiology (98%), and advanced CKD stage (62% 3B-5) were salient features. Histopathological diagnosis was available in 26 (57%) patients. Combining clinical and pathological diagnoses, diabetic nephropathy (48%), arterionephrosclerosis (30%), podocytopathies (15%), and proliferative glomerulonephritides (15%) accounted for most patients. Vacuolization of tubules or podocytes was present in 61% of the specimens. When compared with patients with histopathological diagnoses in which vacuolar casts were not found (n =186), patients with vacuolar casts more frequently had a glomerular etiology (100% versus 71%, P = 0.002), had greater proteinuria (median urine protein-to-creatinine 10.3 versus 2.2 g/g, P < 0.001), and had greater proportion of patients with ≥30% glomerular obsolescence (46% versus 20%, P = 0.003).

Conclusions

Thus, urinary vacuolar casts are strongly associated with advanced glomerulopathies with severe proteinuria. Future studies should examine their origin, composition, and prognostic value.

Podcast

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2024_01_26_KID0000000000000346.mp3

Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review

BACKGROUND

Diabetes mellitus prevalence is increasing among adults and children around the world. Diabetes care is complex; examining the diet, type of medication, diabetes recognition, and willingness to use self-management tools are just a few of the challenges faced by diabetes clinicians who should make decisions about them. Making the appropriate decisions will reduce the cost of treatment, decrease the mortality rate of diabetes, and improve the life quality of patients with diabetes. Effective decision-making is within the realm of multicriteria decision-making (MCDM) techniques.

OBJECTIVE

The central objective of this study is to evaluate the effectiveness and applicability of MCDM methods and then introduce a novel categorization framework for their use in this field.

METHODS

The literature search was focused on publications from 2003 to 2023. Finally, by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method, 63 articles were selected and examined.

RESULTS

The findings reveal that the use of MCDM methods in diabetes research can be categorized into 6 distinct groups: the selection of diabetes medications (19 publications), diabetes diagnosis (12 publications), meal recommendations (8 publications), diabetes management (14 publications), diabetes complication (7 publications), and estimation of diabetes prevalence (3 publications).

CONCLUSIONS

Our review showed a significant portion of the MCDM literature on diabetes. The research highlights the benefits of using MCDM techniques, which are practical and effective for a variety of diabetes challenges.

Estimation of the Various Urinary Biomarkers among the Non-Hypertensive Type 2 Diabetic Patients with Nephropathy

Introduction

Alteration in the various markers is seen in diabetic nephropathy (DN). In the current research, four different markers were evaluated and were examined for their diagnostic value in the nephropathic type 2 diabetes patients.

Methods

A prospective clinical trial was piloted with diabetic male subjects with nephropathy. The subjects were followed up for 9 months. Thirty subjects were recruited as type 2 diabetes mellitus patients without nephropathy as controls. The interventional groups were grouped again as microalbuminuria, normoalbuminuria, and hyperfiltration. All of them underwent testing for urinary biomarkers like urine protein, ACR, HbA1C, and estimated glomerular filtration rate (eGFR). Correlation and logistic regression were used to compare all diagnostic tests across various groupings.

Results

The greatest area under curve (AUC) values were .90 and .91 for AGT and AGT/Cr, respectively. The AUC, specificity, sensitivity, and cut-off value of AGT/Cr were, respectively, .91, 85%, 91%, and 4.36 mg/g. When using urine as the cut-off, the sensitivity was 42 and 100 for ACR and eGFR both. All other biomarkers had lower values than the AGT. Less than. 50 was evident for NGAL/Cr and NAGL.

Conclusions

To identify DN, before the initiation of the albuminuria, compared to other diagnostic markers, urinary AGT demonstrated a greater diagnostic value. Further research is suggested to corroborate the findings.

The Goldilocks Dilemma on Balancing User Response and Reflection in mHealth Interventions: Observational Study

Background

Mobile health (mHealth) has the potential to radically improve health behaviors and quality of life; however, there are still key gaps in understanding how to optimize mHealth engagement. Most engagement research reports only on system use without consideration of whether the user is reflecting on the content cognitively. Although interactions with mHealth are critical, cognitive investment may also be important for meaningful behavior change. Notably, content that is designed to request too much reflection could result in users' disengagement. Understanding how to strike the balance between response burden and reflection burden has critical implications for achieving effective engagement to impact intended outcomes.

Objective

In this observational study, we sought to understand the interplay between response burden and reflection burden and how they impact mHealth engagement. Specifically, we explored how varying the response and reflection burdens of mHealth content would impact users' text message response rates in an mHealth intervention.

Methods

We recruited support persons of people with diabetes for a randomized controlled trial that evaluated an mHealth intervention for diabetes management. Support person participants assigned to the intervention (n=148) completed a survey and received text messages for 9 months. During the 2-year randomized controlled trial, we sent 4 versions of a weekly, two-way text message that varied in both reflection burden (level of cognitive reflection requested relative to that of other messages) and response burden (level of information requested for the response relative to that of other messages). We quantified engagement by using participant-level response rates. We compared the odds of responding to each text and used Poisson regression to estimate associations between participant characteristics and response rates.

Results

The texts requesting the most reflection had the lowest response rates regardless of response burden (high reflection and low response burdens: median 10%, IQR 0%-40%; high reflection and high response burdens: median 23%, IQR 0%-51%). The response rate was highest for the text requesting the least reflection (low reflection and low response burdens: median 90%, IQR 61%-100%) yet still relatively high for the text requesting medium reflection (medium reflection and low response burdens: median 75%, IQR 38%-96%). Lower odds of responding were associated with higher reflection burden (P<.001). Younger participants and participants who had a lower socioeconomic status had lower response rates to texts with more reflection burden, relative to those of their counterparts (all P values were <.05).

Conclusions

As reflection burden increased, engagement decreased, and we found more disparities in engagement across participants' characteristics. Content encouraging moderate levels of reflection may be ideal for achieving both cognitive investment and system use. Our findings provide insights into mHealth design and the optimization of both engagement and effectiveness.

The Sukaribit Smartphone App for Better Self-Management of Type 2 Diabetes: Randomized Controlled Feasibility Study

BACKGROUND

A new app, Sukaribit, was designed to enable contact between the caregiver and the patient with the intent to improve self-care and glycemic control (hemoglobin A1c [HbA1c]).

OBJECTIVE

This study investigated the feasibility of the study methodology and the intervention in preparation for a larger effectiveness study.

METHODS

Adults with type 2 diabetes were recruited in this randomized controlled feasibility study with a mixed methods design. The intervention group (n=28) tried Sukaribit for 2 months. They were encouraged to report blood glucose levels and medications, and they received feedback from a physician. The control group (n=31) received standard care. Both groups were evaluated with pre and postmeasurements of glycemic control (HbA1c), diabetes distress, physical activity, and self-care. Feasibility was evaluated against 5 progression criteria regarding recruitment, study methods, and active participation.

RESULTS

Of the 5 progression criteria, only 2 were met or partially met. The recruitment process exceeded expectations, and data collection worked well for self-reported data but not for HbA1c measured with a home testing kit. The participants were less active than anticipated, and the effect sizes were small. Only the number of blood glucose tests per day was positively affected by the intervention, with 0.6 more tests per day in the intervention group.

CONCLUSIONS

Recruitment of participants to a future fully powered study may work with minor adjustments. The collection of HbA1c using home testing constituted a major problem, and an alternative strategy is warranted. Finally, the app was not used as intended. In order to proceed with a larger study, the app and study procedures need improvement.

Evaluating the cost-effectiveness of diabetic foot ulcer management by wound care specialists in Indonesia

Diabetic foot ulcers affect quality of life and economically burden patients and the Indonesian healthcare system. The comparative cost-effectiveness of wound care specialists in private practices (e.g., wound clinics) and wound care nurses in national hospitals remains unknown. Thus, we used a decision tree to compare the cost and healing rates for patients after 12 weeks of wound care. Uncertainty was addressed using one-way and probabilistic sensitivity analyses. Among 89 participants (42 in the national hospital and 47 in the private practice), no significant differences were observed between the two groups in terms of sex, age, education level, smoking status, duration of diabetes, Wagner wound classification, glycated haemoglobin levels, neuropathy status, ankle-brachial index, baseline characteristics, quality of life, DMIST (depth, maceration, inflammation/infection, size, tissue type of the wound bed, type of wound edge, and tunnelling/undermining) score and wound location (p > 0.05). However, significant differences were observed for days from first visit/assessment until complete healing, mean quality of life (p ≤ 0.001) and wound size (p = 0.047). Wound care specialists in private practices had a significantly lower cost of 2,804,423.3 Indonesian rupiah compared to 6,483,493.4 Indonesian rupiah for wound care nurses in national hospitals. The incremental cost-effectiveness ratio was -165,723.9. Therefore, wound care specialists in private practices are more cost-effective for managing diabetic foot ulcers. Probability sensitivity analysis confirmed that 80%-90% of the scenarios were cost-effective. These findings may inform healthcare resource allocation in Indonesia. Additionally, evidence-based cost-effectiveness measures were strengthened in private practices and national hospitals.

Analysis of risk factors in diabetics resulted from polycystic ovary syndrome in women by EDA analysis and machine learning techniques

This study discusses the relationship between Polycystic Ovary Syndrome (PCOS) and diabetes in women, which has become increasingly prevalent due to changing lifestyles and environmental factors. The characteristic that distinguishes women with PCOS is hyperandrogenism which results from abnormal ovarian or adrenal function, which leads to the overproduction of androgens. Excessive androgens in women increase the risk of Type 2 diabetes (T2D) and insulin resistance (IR). Nowadays, diabetes affects people of all ages and is linked to factors such as lifestyle, genetics, stress, and aging. Diabetes, the uncontrolled high blood sugar level can potentially harm kidneys, nerves, eyes, and other organs and there is no cure, making it a concerning disease in developing nations. This research tried to submit the evidence through feature-wise correlation analyses between PCOS and diabetes. Hence, this model utilized the Exploratory Data Analysis (EDA) and the Elbow clustering algorithms for the experimental purpose in which the EDA deeply analyzed the features of PCOS and diabetes and recorded a positive correlation of 95%. The Elbow clustering technique is employed for verifying the correlations identified through EDA. Although limited research exists on this specific disease, this work provides potential evidence for the research community by evaluating the clustering results using Silhouette Score, Calinski-Harabasz Index, and Davies-Bouldin Index.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Exploring the Usability and Acceptability of a Well-Being App for Adolescents Living With Type 1 Diabetes: Qualitative Study

Background

Adolescents living with either type 1 diabetes (T1D) or type 2 diabetes (T2D) have an increased risk of psychological disorders due to the demands of managing a chronic illness and the challenges of adolescence. Psychological disorders during adolescence increase the risk of suboptimal glycemic outcomes and may lead to serious diabetes-related complications. Research shows that digital health interventions may increase access to psychological support for adolescents and improve physical and mental health outcomes for youth with diabetes. To our knowledge, there are no evidence-based, publicly available mental health apps with a focus on improving the psychological well-being of adolescents with diabetes.

Objective

This study aimed to explore the acceptability and usability of our evidence-based well-being app for New Zealand adolescents, Whitu: 7 Ways in 7 Days (Whitu), to allow us to further tailor it for youth with diabetes. We interviewed adolescents with T1D and T2D, their parents, and health care professionals to explore their views on the Whitu app and suggestions for tailoring the app for adolescent with diabetes. We also explored the cultural acceptability of the Whitu app for Māori and Pacific adolescents.

Methods

A total of 34 participants, comprising 13 adolescents aged 12-16 years (11 with T1D and 2 with T2D), 10 parents, and 11 health care professionals, were recruited from a specialist diabetes outpatient clinic and Facebook diabetes groups. Each participant attended one 1-hour focus group on Zoom, in person, or via phone. Researchers gathered general feedback on what makes an effective and engaging app for adolescents with diabetes, as well as specific feedback about Whitu. Transcribed audio recordings of the focus groups were analyzed using directed content analysis.

Results

Adolescents with T1D, their parents, and health care professionals found Whitu to be acceptable and usable. Adolescents with T1D and their parents signaled a preference for more diabetes-specific content. Health care professionals expressed less awareness and trust of digital health interventions and, as such, recommended that they be used with external support. Due to challenges in recruitment and retention, we were unable to include the views of adolescents with T2D in this qualitative study.

Conclusions

There appears to be sufficient openness to the use of an app such as Whitu for supporting the well-being of adolescents with T1D, albeit with modifications to make its content more diabetes specific. Based on this qualitative study, we have recently developed a diabetes-specific version of Whitu (called LIFT: Thriving with Diabetes). We are also planning a qualitative study to explore the views of youth with T2D and their perspectives on the new LIFT app, where we are using alternative research approaches to recruit and engage adolescents with T2D and their families.

Ameliorative Effects of Cumin Extract-Encapsulated Chitosan Nanoparticles on Skeletal Muscle Atrophy and Grip Strength in Streptozotocin-Induced Diabetic Rats

Skeletal muscle atrophy is a disorder characterized by reductions in muscle size and strength. Cumin extract (CE) possesses anti-inflammatory, antioxidant, and hypoglycemic properties. Its pharmaceutical applications are hindered by its low water solubility and by its cytotoxicity when administered at high doses. In this study, we have developed a simplified water distillation method using a rotary evaporator to isolate the active components in cumin seeds. The anti-inflammatory effects of CE and its potential to ameliorate skeletal muscle atrophy in rats with streptozotocin (STZ)-induced diabetes were evaluated. The half-maximal inhibitory concentration (IC50) of CE for cells was 80 μM. By encapsulating CE in chitosan nanoparticles (CECNs), an encapsulation efficacy of 87.1% was achieved with a slow release of 90% of CE after 24 h of culturing, resulting in CECNs with significantly reduced cytotoxicity (IC50, 1.2 mM). Both CE and CECNs significantly reduced the inflammatory response in interleukin (IL)-6 and IL-1β assays. STZ-induced diabetic rats exhibited sustained high blood glucose levels (>16.5 mmol/L), small and damaged pancreatic β islets, and skeletal muscle atrophy. CE and CECN treatments ameliorated skeletal muscle atrophy, recovered muscle fiber striated appearance, increased grip strength, and decreased IL-6 level. Furthermore, CE and CECNs led to a reduction of damage to the pancreas, restoring its morphological phenotype, increasing serum insulin levels, and lowering blood glucose levels in STZ-induced diabetic rats. Taken together, treatment with CECNs over a 6-week period yielded positive ameliorative effects in STZ-induced rats of muscle atrophy.

Protective Effects of Sitagliptin on Streptozotocin-Induced Hepatic Injury in Diabetic Rats: A Possible Mechanisms

Diabetes is a ubiquitous disease that causes several complications. It is associated with insulin resistance, which affects the metabolism of proteins, carbohydrates, and fats and triggers liver diseases such as fatty liver disease, steatohepatitis, fibrosis, and cirrhosis. Despite the effectiveness of Sitagliptin (ST) as an antidiabetic drug, its role in diabetes-induced liver injury is yet to be fully investigated. Therefore, this study aims to investigate the effect of ST on hepatic oxidative injury, inflammation, apoptosis, and the mTOR/NF-κB/NLRP3 signaling pathway in streptozotocin (STZ)-induced liver injury. Rats were allocated into four groups: two nondiabetic groups, control rats and ST rats (100 mg/kg), and two diabetic groups induced by STZ, and they received either normal saline or ST for 90 days. Diabetic rats showed significant hyperglycemia, hyperlipidemia, and elevation in liver enzymes. After STZ induction, the results revealed remarkable increases in hepatic oxidative stress, inflammation, and hepatocyte degeneration. In addition, STZ upregulated the immunoreactivity of NF-κB/p65, NLRP3, and mTOR but downregulated IKB-α in liver tissue. The use of ST mitigated metabolic and hepatic changes induced by STZ; it also reduced oxidative stress, inflammation, and hepatocyte degeneration. The normal expression of NF-κB/p65, NLRP3, mTOR, and IKB-α were restored with ST treatment. Based on that, our study revealed for the first time the hepatoprotective effect of ST that is mediated by controlling inflammation, oxidative stress, and mTOR/NF-κB/NLRP3 signaling.

Association Between Serum Glycated Hemoglobin Levels at Early Gestation and the Risk of Subsequent Pregnancy Loss in Pregnant Women Without Diabetes Mellitus: Prospective Cohort Study

BACKGROUND

As a severe morbidity during pregnancy, the etiology of spontaneous pregnancy loss (SPL) remains largely unknown. Serum glycated hemoglobin (HbA1c) level is an established predictor of SPL risk among women with diabetes, but little is known about whether such an association exists among pregnant women without diabetes when glycemic levels are within the normal range.

OBJECTIVE

This study aimed to quantify the association between maternal HbA1c levels in early pregnancy and subsequent SPL risk in a cohort of pregnant women without diabetes.

METHODS

This prospective cohort study involved 10,773 pregnant women without diabetes enrolled at their first antenatal care visit at a hospital's early pregnancy clinic from March 2016 to December 2018 in Shanghai, China. HbA1c and fasting blood glucose (FBG) levels were examined at enrollment. Participants with diabetes before or pregnancy or those diagnosed with gestational diabetes were excluded. Diagnosis of SPL, defined as fetal death occurring before 28 gestational weeks, was derived from medical records and confirmed via telephone interviews. We used generalized linear models to quantify the associations of continuous and dichotomized maternal HbA1c levels with SPL risk and reported crude and adjusted risk ratios (RRs) and 95% CIs. A restricted cubic spline (RCS) regression model was used to assess the potential nonlinear dose-response relationship. Adjusted covariates included maternal age, education level, preconception BMI, gestational weeks, gravidity, history of adverse pregnancy outcomes, family history of diabetes, folic acid supplementation, and smoking and drinking during the periconception period.

RESULTS

In total, 273 (2.5%) SPL cases occurred. Every 0.5% increase in HbA1c levels was linearly associated with a 23% increase in SPL risk (adjusted RR [aRR] 1.23; 95% CI 1.01-1.50). The RCS model revealed that this association was linear (P=.77 for the nonlinearity test). Analyses based on dichotomized HbA1c levels showed a significantly increased risk of SPL when HbA1c levels were ≥5.9% (aRR 1.67; 95% CI 0.67-3.67), and the significance threshold was ≥5.6% (aRR 1.60; 95% CI 1.01-2.54). Sensitivity analyses showed similar results when including the participants with missing SPL records or HbA1c data. Linear associations of HbA1c levels remained significant even in the subgroups without overweight, alcohol consumption, and a family history of diabetes and adverse pregnancy outcomes. Every 1 mmol/L increment in maternal FBG levels was associated with a >2-fold higher risk of SPL (aRR 2.12; 95% CI 1.61-2.80; P<.001).

CONCLUSIONS

Higher HbA1c levels in early pregnant women without diabetes are associated with an increased SPL risk in a dose-response manner. Pregnant women with an HbA1c level above 5.6% at early gestation need attention for its potentially increased risk for SPL. Our findings support the need to monitor HbA1c levels to identify individuals at high risk of subsequent SPL in the general population of pregnant women.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02737644; https://clinicaltrials.gov/study/NCT02737644.

Glycemic control and neonatal outcomes in twin pregnancies with gestational diabetes mellitus

BACKGROUND

Preliminary data suggest that strict glycemic control in twin pregnancies with gestational diabetes mellitus may not improve outcomes but might increase the risk of fetal growth restriction.

OBJECTIVE

This study aimed to investigate the association of maternal glycemic control with the risk of gestational diabetes mellitus-related complications and small for gestational age in twin pregnancies complicated by gestational diabetes mellitus.

STUDY DESIGN

This was a retrospective cohort study of all patients with a twin pregnancy complicated by gestational diabetes mellitus in a single tertiary center between 2011 and 2020, and a matched control group of patients with a twin pregnancy without gestational diabetes mellitus in a 1:3 ratio. The exposure was the level of glycemic control, described as the proportion of fasting, postprandial, and overall glucose values within target. Good glycemic control was defined as a proportion of values within target above the 50th percentile. The first coprimary outcome was a composite variable of neonatal morbidity, defined as at least 1 of the following: birthweight >90th centile for gestational age, hypoglycemia requiring treatment, jaundice requiring phototherapy, birth trauma, or admission to the neonatal intensive care unit at term. A second coprimary outcome was small for gestational age, defined as birthweight <10th centile or <3rd centile for gestational age. Associations between the level of glycemic control and the study outcomes were estimated using logistic regression analysis and were expressed as adjusted odds ratio with 95% confidence interval.

RESULTS

A total of 105 patients with gestational diabetes mellitus in a twin pregnancy met the study criteria. The overall rate of the primary outcome was 32.4% (34/105), and the overall proportion of pregnancies with a small for gestational age newborn at birth was 43.8% (46/105). Good glycemic control was not associated with a reduction in the risk of composite neonatal morbidity when compared with suboptimal glycemic control (32.1% vs 32.7%; adjusted odds ratio, 2.06 [95% confidence interval, 0.77-5.49]). However, good glycemic control was associated with higher odds of small for gestational age compared with nongestational diabetes mellitus pregnancies, especially in the subgroup of diet-treated gestational diabetes mellitus (65.5% vs 34.0%, respectively; adjusted odds ratio, 4.17 [95% confidence interval, 1.74-10.01] for small for gestational age <10th centile; and 24.1% vs 7.0%, respectively; adjusted odds ratio, 3.97 [95% confidence interval, 1.42-11.10] for small for gestational age <3rd centile). In contrast, the rate of small for gestational age in gestational diabetes mellitus pregnancies with suboptimal control was not considerably different when compared with non-gestational diabetes mellitus pregnancies. In addition, in cases of diet-treated gestational diabetes mellitus, good glycemic control was associated with a left-shift of the distribution of birthweight centiles, whereas the distribution of birthweight centiles among gestational diabetes mellitus pregnancies with suboptimal control was similar to that of nongestational diabetes mellitus pregnancies.

CONCLUSION

In patients with gestational diabetes mellitus in a twin pregnancy, good glycemic control is not associated with a reduction in the risk of gestational diabetes mellitus-related complications but may increase the risk of a small for gestational age newborn in the subgroup of patients with mild (diet-treated) gestational diabetes mellitus. These findings further question whether the gestational diabetes mellitus glycemic targets used in singleton pregnancies also apply to twin pregnancies and support the concern that applying the same diagnostic criteria and glycemic targets in twin pregnancies may result in overdiagnosis and overtreatment of gestational diabetes mellitus and potential neonatal harm.

Patient and Physician Perspectives on the Use of a Connected Ecosystem for Diabetes Management: International Cross-Sectional Observational Study

BACKGROUND

Collaboration between people with type 2 diabetes (T2DM) and their health care teams is important for optimal control of the disease and outcomes. Digital technologies could potentially tie together several health care-related devices and platforms into connected ecosystems (CES), but attitudes about CES are unknown.

OBJECTIVE

We surveyed convenience samples of patients and physicians to better understand which patient characteristics are associated with higher likelihoods of (1) participating in a potential CES program, as self-reported by patients with T2DM and (2) clinical benefit from participation in a potential CES program, as reported by physicians.

METHODS

Adults self-reporting a diagnosis of T2DM and current insulin use (n=197), and 33 physicians whose practices included ≥20% of such patients, were enrolled in the United States, France, and Germany. We surveyed both groups about the likelihood of patient participation in a CES. We then examined the associations between patients' clinical and sociodemographic characteristics and this likelihood. We also described characteristics of patients likely to clinically benefit from CES use, according to physicians.

RESULTS

Compared with patients in Germany and France, US patients were younger (mean age 45.3 [SD 11.9] years vs 61.9 [SD 9.2] and 65.8 [SD 9.4] years, respectively), more often female, more highly educated, and more often working full-time. In all, 51 (44.7%) US patients, 16 (36.4%) German patients, and 18 (46.3%) French patients indicated strong interest in a CES program, and 115 (78.7%) reported currently using ≥1 connected device or app. However, physicians believed that only 11.3%-19.2% of their patients were using connected devices or apps to manage their disease. Physicians also reported infrequently recommending or prescribing connected devices to their patients, although ≥80% (n=28) of them thought that a CES could help support their patients in managing their disease. The factors most predictive of patient likelihood of participating in a CES program were cost, inclusion of medication reminders, and linking blood glucose levels to behaviors such as eating and exercise. In all countries, the most common patient expectations for a CES program were that it could help them eat more healthfully, increase their physical activity, increase their understanding of how blood glucose relates to behavior such as exercise and eating, and reduce stress. Physicians thought that newly diagnosed patients, sicker patients-those who had been hospitalized for diabetes, were currently using insulin, or who had any comorbid condition-and patients who were nonadherent to treatment were most likely to benefit from CES use.

CONCLUSIONS

In this study, there was a high degree of interest in the future use of CES, although additional education is needed among both patients with T2DM and their physicians to achieve the full potential of such systems to improve self-management and clinical care for the disease.

Demographic, Clinical, and Quality of Life Profiles of Older People With Diabetes During the COVID-19 Pandemic: Cross-Sectional Study

BACKGROUND

Diabetes mellitus, one of the main diseases that affects the Brazilian population older than 60 years, is defined as a divergent group of metabolic disorders that present a high level of glycemia (hyperglycemia), causing damage to various organs and systems of the body, including the heart, kidneys, eyes, and nervous system. It is believed that in 2025, in Brazil alone, there will be more than 18.5 million individuals diagnosed with diabetes mellitus. Therefore, it is important to know the individuals' quality of life in the context of life and culture.

OBJECTIVE

This study aimed to assess the demographic, clinical, and quality of life profiles of older adults with diabetes during the COVID-19 pandemic in a university hospital complex in the northern Amazon region.

METHODS

We conducted a cross-sectional, exploratory, noninterventional, descriptive, and analytical study using a nonrandom sample of 54 older people diagnosed with diabetes mellitus at the geriatrics outpatient clinic of the medium and high complexity university hospital in the western Brazilian Amazon between 2020 and 2022. We used 3 instruments, namely, a sociodemographic questionnaire, a clinical conditions questionnaire, and Diabetes-39. Qualitative data were described using absolute and relative frequencies. The Kolmogorov-Smirnov normality test was applied, and the z test was used for inferential analysis. SPSS software (version 27) was used for data analysis, and the significance level was 5%.

RESULTS

Of the 54 interviewees, the majority were women, married, retired, and had a good quality of life. Of these, 48.1% (n=26) were infected by COVID-19, 61.5% (n=16) of whom progressed to long COVID, presenting with fatigue or muscle weakness. As for the quality of life, the "social overload" (P<.001) and "sexual functioning" (P<.001) dimensions had with low scores compared to the "energy and mobility" (P=.005), "diabetes control" (P<.001), and "anxiety and worry" (P<.001) dimensions. Quality of life was negatively impacted in the "anxiety and worry" dimension. Among those affected by COVID-19, most progressed to long COVID; however, there was a lack of data on this theme in the population of older people with diabetes.

CONCLUSIONS

The majority of interviewees progressed to long COVID, with their quality of life negatively impacted in the "anxiety and worry" dimension, reflecting that health actions prioritizing mental health should be implemented by health professionals.

Think Aloud Testing of a Smartphone App for Lifestyle Change Among Persons at Risk of Type 2 Diabetes: Usability Study

BACKGROUND

Type 2 diabetes mellitus (DM2) is a leading cause of morbidity and mortality worldwide and is considered a global epidemic. Despite the growing evidence on the effectiveness of mobile health interventions in the management of DM2, the evidence on the effect of mobile health interventions in prevention of DM2 is sparse. Therefore, we have developed an app aiming to promote initiation of behavioral change and adherence to healthy behavior. Before commencing a small-scale randomized controlled trial to assess the feasibility of using an app for initiation and adherence of healthy behavior in people at risk of DM2, testing the usability of the app in the target population is warranted.

OBJECTIVE

The aim of this study was to assess the usability of an app among people at risk of DM2.

METHODS

A qualitative study with the use of a think aloud (TA) procedure was conducted from April to November 2022. The TA procedure consisted of 10 problem-solving tasks and a semistructured interview which was carried out after the tasks. These interviews served to gain more in-depth knowledge of the users experience of the problem-solving tasks. The TA-sessions and the postactivity interviews were recorded and transcribed verbatim, and the data were coded and analyzed following the principles of thematic analysis.

RESULTS

In total, 7 people at risk of DM2 with a median age of 66 (range 41-75) years participated in this study. The analysis resulted in the following themes: (1) user interface design; and (2) suggestions for improvements of the functionality of the app.

CONCLUSIONS

Overall, the participants were satisfied with the usability of the app. Through the TA-sessions, real time perspective on the appeal, relevance, and utility of the app were gained. Only minor changes to the functionality of the prototype app were reported as necessary to improve the usability of the app. Points of guidance from the participants in this study have been adopted and incorporated into the final design of the app now being assessed for feasibility in a small-scale randomized controlled trial.

Telehealth Diabetes Prevention Program for Adults With Prediabetes in an Academic Medical Center Setting: Protocol for a Hybrid Type III Trial

BACKGROUND

Diabetes is a costly epidemic in the United States associated with both health and economic consequences. These consequences can be mitigated by participation in structured lifestyle change programs such as the National Diabetes Prevention Program (DPP) led by the Centers for Disease Control and Prevention. Mississippi consistently has among the highest rates of diabetes and prediabetes nationally. Implementing the National DPP through large health care systems can increase reach and accessibility for populations at the highest risk for diabetes. Translational research on the National DPP in Mississippi has not been studied.

OBJECTIVE

This study aims to evaluate the implementation and impact of the National DPP delivered using telehealth modalities at the University of Mississippi Medical Center in Jackson, Mississippi.

METHODS

An effectiveness-implementation hybrid type III research design is proposed. The study design is guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework and the Practical, Robust Implementation and Sustainability Model. Participants are being recruited via provider referral, and the DPP is being delivered by trained lifestyle coaches. Study participants include adult (≥18 years) patients eligible for the DPP with at least 1 encounter at 1 of 3 ambulatory clinic specialties (lifestyle medicine, family medicine, and internal medicine) between January 2019 and December 2023. The National DPP eligibility criteria include a BMI ≥25 kg/m2 and hemoglobin A1c between 5.7% and 6.4%. The University of Mississippi Medical Center criteria include Medicare or Medicaid beneficiaries. The University of Mississippi Medical Center's a priori implementation plan was developed using the Consolidated Framework for Implementation Research and includes 23 discrete strategies. The primary aim will use an embedded mixed method process analysis to identify and mitigate challenges to implementation. The secondary aim will use a nonrandomized quasi-experimental design to assess the comparative effectiveness of the DPP on health care expenditures. A propensity score matching method will be implemented to compare case subjects to control subjects. The primary outcomes include patient referrals, participant enrollment, retention, engagement, the incidence of diabetes, and health care resource use and costs.

RESULTS

At baseline, of the 26,151 patients across 3 ambulatory clinic specialties, 1010 (3.9%) had prediabetes and were eligible for the National DPP. Of the 1010 patients, more than half (n=562, 55.6%) were aged 65 years or older, 79.5% (n=803) were Medicare beneficiaries, 65.9% (n=666) were female, and 70.8% (n=715) were obese.

CONCLUSIONS

This is the first translational study of the National DPP in Mississippi. The findings will inform implementation strategies impacting the uptake and sustainability of the National DPP delivered in an academic medical setting using distance learning and telehealth modalities.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04822480; https://clinicaltrials.gov/study/NCT03622580.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/50183.

An AI Dietitian for Type 2 Diabetes Mellitus Management Based on Large Language and Image Recognition Models: Preclinical Concept Validation Study

BACKGROUND

Nutritional management for patients with diabetes in China is a significant challenge due to the low supply of registered clinical dietitians. To address this, an artificial intelligence (AI)-based nutritionist program that uses advanced language and image recognition models was created. This program can identify ingredients from images of a patient's meal and offer nutritional guidance and dietary recommendations.

OBJECTIVE

The primary objective of this study is to evaluate the competence of the models that support this program.

METHODS

The potential of an AI nutritionist program for patients with type 2 diabetes mellitus (T2DM) was evaluated through a multistep process. First, a survey was conducted among patients with T2DM and endocrinologists to identify knowledge gaps in dietary practices. ChatGPT and GPT 4.0 were then tested through the Chinese Registered Dietitian Examination to assess their proficiency in providing evidence-based dietary advice. ChatGPT's responses to common questions about medical nutrition therapy were compared with expert responses by professional dietitians to evaluate its proficiency. The model's food recommendations were scrutinized for consistency with expert advice. A deep learning-based image recognition model was developed for food identification at the ingredient level, and its performance was compared with existing models. Finally, a user-friendly app was developed, integrating the capabilities of language and image recognition models to potentially improve care for patients with T2DM.

RESULTS

Most patients (182/206, 88.4%) demanded more immediate and comprehensive nutritional management and education. Both ChatGPT and GPT 4.0 passed the Chinese Registered Dietitian examination. ChatGPT's food recommendations were mainly in line with best practices, except for certain foods like root vegetables and dry beans. Professional dietitians' reviews of ChatGPT's responses to common questions were largely positive, with 162 out of 168 providing favorable reviews. The multilabel image recognition model evaluation showed that the Dino V2 model achieved an average F1 score of 0.825, indicating high accuracy in recognizing ingredients.

CONCLUSIONS

The model evaluations were promising. The AI-based nutritionist program is now ready for a supervised pilot study.

Diabetes Life Expectancy Prediction Model Inputs and Results From Patient Surveys Compared With Electronic Health Record Abstraction: Survey Study

Background

Prediction models are being increasingly used in clinical practice, with some requiring patient-reported outcomes (PROs). The optimal approach to collecting the needed inputs is unknown.

Objective

Our objective was to compare mortality prediction model inputs and scores based on electronic health record (EHR) abstraction versus patient survey.

Methods

Older patients aged ≥65 years with type 2 diabetes at an urban primary care practice in Chicago were recruited to participate in a care management trial. All participants completed a survey via an electronic portal that included items on the presence of comorbid conditions and functional status, which are needed to complete a mortality prediction model. We compared the individual data inputs and the overall model performance based on the data gathered from the survey compared to the chart review.

Results

For individual data inputs, we found the largest differences in questions regarding functional status such as pushing/pulling, where 41.4% (31/75) of participants reported difficulties that were not captured in the chart with smaller differences for comorbid conditions. For the overall mortality score, we saw nonsignificant differences (P=.82) when comparing survey and chart-abstracted data. When allocating participants to life expectancy subgroups (<5 years, 5-10 years, >10 years), differences in survey and chart review data resulted in 20% having different subgroup assignments and, therefore, discordant glucose control recommendations.

Conclusions

In this small exploratory study, we found that, despite differences in data inputs regarding functional status, the overall performance of a mortality prediction model was similar when using survey and chart-abstracted data. Larger studies comparing patient survey and chart data are needed to assess whether these findings are reproduceable and clinically important.

Expression of advanced glycation end products and their receptors in diabetic periodontitis patients

AIM

The systematic review aimed to compare the levels of advanced glycation end products (AGEs) and RAGE (AGE receptors) expression in diabetic periodontitis patients with non-diabetic periodontitis patients and to identify the relationship of AGE and RAGE levels with periodontal disease severity.

MATERIALS AND METHODS

The literature search was carried out according to PRISMA guidelines by two independent researchers using four online databases: PubMed, Scopus, Web of Science Core Collection, and Pro-Quest. Relevant studies published between 2000 and March 2023 were included in this review. The association of diabetes and AGE/RAGE levels on periodontal health, periodontal pocket depth (PPD), and clinical attachment loss (CAL) was studied.

RESULTS

Sixteen cross-sectional studies, including 2794 patients (age range 15-75 years), were identified in the final stage. An elevated AGE level was observed among patients with diabetes and chronic periodontal disease compared to the non-diabetic group. Furthermore, the levels of AGE and RAGE are associated with CAL and PPD. Potential confounding factors like genetic and methodological differences were also responsible for AGE and RAGE variation.

CONCLUSION

Levels of AGEs and RAGE expressions in diabetic periodontitis patients differ from non-diabetic periodontitis patients. The differences may impact the course and severity of periodontal disease.

Esculeoside A Decreases Diabetic Cardiomyopathy in Streptozotocin-Treated Rats by Attenuating Oxidative Stress, Inflammation, Fibrosis, and Apoptosis: Impressive Role of Nrf2

Background and Objectives: This experiment evaluated the preventative influence of the tomato-derived Esculeoside A (ESA) on diabetic cardiomyopathy in type 1 diabetes mellitus (T1DM) in rats induced by streptozotocin (STZ). It also examined whether the activation of Nrf2 signaling affords this protection. Materials and Methods: Adult male Wistar control nondiabetic rats and rats with T1DM (STZ-T1DM) were given either carboxymethylcellulose as a vehicle or ESA (100 mg/kg) (eight rats/group) orally daily for 12 weeks. A group of STZ-T1DM rats was also treated with 100 mg/kg ESA and co-treated i.p. with 2 mg/kg (twice/week), brusatol, and Nrf2 inhibitors for 12 weeks. Results and Conclusions: Treatment with ESA prevented the gain in heart weight and cardiomyocyte hypertrophy and improved the left ventricular (LV) systolic and diastolic function (LV) in the STZ-T1DM rat group. Likewise, it reduced their serum levels of triglycerides, cholesterol, and low-density lipoproteins (LDL-c), as well as their LV mRNA, cytoplasmic total, and nuclear total levels of NF-κB. ESA also reduced the total levels of malondialdehyde, tumor necrosis factor-α, interleukine-6 (IL-6), Bax, cytochrome-c, and caspase-3 in the LV of the STZ-T1DM rats. In parallel, ESA enhanced the nuclear and cytoplasmic levels of Nrf2 and the levels of superoxide dismutase, glutathione, and heme oxygenase-1, but decreased the mRNA and cytoplasmic levels of keap-1 in the LVs of the STZ-T1DM rats. Interestingly, ESA did not affect the fasting insulin and glucose levels of the diabetic rats. All of these beneficially protective effects of ESA were not seen in the ESA-treated rats that received brusatol. In conclusion, ESA represses diabetic cardiomyopathy in STZ-diabetic hearts by activating the Nrf2/antioxidant/NF-κB axis.

An Evidence-Based Framework for Creating Inclusive and Personalized mHealth Solutions-Designing a Solution for Medicaid-Eligible Pregnant Individuals With Uncontrolled Type 2 Diabetes

Mobile health (mHealth) apps can be an evidence-based approach to improve health behavior and outcomes. Prior literature has highlighted the need for more research on mHealth personalization, including in diabetes and pregnancy. Critical gaps exist on the impact of personalization of mHealth apps on patient engagement, and in turn, health behaviors and outcomes. Evidence regarding how personalization, engagement, and health outcomes could be aligned when designing mHealth for underserved populations is much needed, given the historical oversights with mHealth design in these populations. This viewpoint is motivated by our experience from designing a personalized mHealth solution focused on Medicaid-enrolled pregnant individuals with uncontrolled type 2 diabetes, many of whom also experience a high burden of social needs. We describe fundamental components of designing mHealth solutions that are both inclusive and personalized, forming the basis of an evidence-based framework for future mHealth design in other disease states with similar contexts.

The Use of mHealth Apps for the Assessment and Management of Diabetes-Related Foot Health Outcomes: Systematic Review

BACKGROUND

Globally, diabetes affects approximately 500 million people and is predicted to affect up to 700 million people by 2045. In Australia, the ongoing impact of colonization produces inequity in health care delivery and inequality in health care outcomes for First Nations Peoples, with diabetes rates 4 times those of non-Indigenous Australians. Evidence-based clinical practice has been shown to reduce complications of diabetes-related foot disease, including ulceration and amputation, by 50%. However, factors such as a lack of access to culturally safe care, geographical remoteness, and high costs associated with in-person care are key barriers for First Nations Peoples in accessing evidence-based care, leading to the development of innovative mobile health (mHealth) apps as a way to increase access to health services and improve knowledge and self-care management for people with diabetes.

OBJECTIVE

This study aims to evaluate studies investigating the use of mHealth apps for the assessment and management of diabetes-related foot health in First Nations Peoples in Australia and non-Indigenous populations globally.

METHODS

PubMed, Informit's Indigenous Collection database, Ovid MEDLINE, Embase, CINAHL Complete, and Scopus were searched from inception to September 8, 2022. Hand searches of gray literature and reference lists of included studies were conducted. Studies describing mHealth apps developed for the assessment and management of diabetes-related foot health were eligible. Studies must include an evaluation (qualitative or quantitative) of the mHealth app. No language, publication date, or publication status restrictions were used. Quality appraisal was performed using the revised Cochrane risk-of-bias tool for randomized trials and the Health Evidence Bulletins Wales checklists for observational, cohort, and qualitative studies.

RESULTS

No studies specifically including First Nations Peoples in Australia were identified. Six studies in non-Indigenous populations with 361 participants were included. Foot care education was the main component of all mHealth apps. Of the 6 mHealth apps, 2 (33%) provided functionality for participants to enter health-related data; 1 (17%) included a messaging interface. The length of follow-up ranged from 1-6 months. Of the 6 studies, 1 (17%) reported high levels of acceptability of the mHealth app content for self-care by people with diabetes and diabetes specialists; the remaining 5 (83%) reported that participants had improved diabetes-related knowledge and self-management skills after using their mHealth app.

CONCLUSIONS

The findings from this systematic review provide an overview of the features deployed in mHealth apps and indicate that this type of intervention can improve knowledge and self-care management skills in non-Indigenous people with diabetes. Future research needs to focus on mHealth apps for populations where there is inadequate or ineffective service delivery, including for First Nations Peoples and those living in geographically remote areas, as well as evaluate direct effects on diabetes-related foot disease outcomes.

TRIAL REGISTRATION

PROSPERO CRD42022349087; https://tinyurl.com/35u6mmzd.

An mHealth Text Messaging Program Providing Symptom Detection Training and Psychoeducation to Improve Hypoglycemia Self-Management: Intervention Development Study

BACKGROUND

Hypoglycemia remains a challenge for roughly 25% of people with type 1 diabetes (T1D) despite using advanced technologies such as continuous glucose monitors (CGMs) or automated insulin delivery systems. Factors impacting hypoglycemia self-management behaviors (including reduced ability to detect hypoglycemia symptoms and unhelpful hypoglycemia beliefs) can lead to hypoglycemia development in people with T1D who use advanced diabetes technology.

OBJECTIVE

This study aims to develop a scalable, personalized mobile health (mHealth) behavioral intervention program to improve hypoglycemia self-management and ultimately reduce hypoglycemia in people with T1D who use advanced diabetes technology.

METHODS

We (a multidisciplinary team, including clinical and health psychologists, diabetes care and education specialists, endocrinologists, mHealth interventionists and computer engineers, qualitative researchers, and patient partners) jointly developed an mHealth text messaging hypoglycemia behavioral intervention program based on user-centered design principles. The following five iterative steps were taken: (1) conceptualization of hypoglycemia self-management processes and relevant interventions; (2) identification of text message themes and message content development; (3) message revision; (4) patient partner assessments for message readability, language acceptability, and trustworthiness; and (5) message finalization and integration with a CGM data-connected mHealth SMS text message delivery platform. An mHealth web-based SMS text message delivery platform that communicates with a CGM glucose information-sharing platform was also developed.

RESULTS

The mHealth SMS text messaging hypoglycemia behavioral intervention program HypoPals, directed by patients' own CGM data, delivers personalized intervention messages to (1) improve hypoglycemia symptom detection and (2) elicit self-reflection, provide fact-based education, and suggest practical health behaviors to address unhelpful hypoglycemia beliefs and promote hypoglycemia self-management. The program is designed to message patients up to 4 times per day over a 10-week period.

CONCLUSIONS

A rigorous conceptual framework, a multidisciplinary team (including patient partners), and behavior change techniques were incorporated to create a scalable, personalized mHealth SMS text messaging behavioral intervention. This program was systematically developed to improve hypoglycemia self-management in advanced diabetes technology users with T1D. A clinical trial is needed to evaluate the program's efficacy for future clinical implementation.

Effects of a Community Health Worker-Led Health Literacy Intervention on Lifestyle Modification Among Patients With Hypertension and Diabetes in the City of Harare, Zimbabwe: Protocol for a Cluster Randomized Controlled Trial

BACKGROUND

Hypertension and diabetes are among the most common noncommunicable diseases in Zimbabwe. These 2 conditions are largely prevented and controlled by lifestyle modifications, such as healthy eating habits, physical activity, and avoiding the use of tobacco and alcohol.

OBJECTIVE

This study aims to evaluate the effects of a community health worker (CHW)-led health literacy intervention on lifestyle modification among patients with diabetes and hypertension in the City of Harare, Zimbabwe, in terms of (1) adherence to recommended lifestyle changes, (2) blood pressure and blood glucose levels, and (3) medication adherence.

METHODS

This is a 6-month-long cluster randomized controlled trial, which will be conducted in primary health care clinics in the city of Harare. A total of 14 clinics will be randomly allocated into either the intervention or control group. A total of 680 (49 participants per clinic) adult patients with hypertension and diabetes will be enrolled for the trial. Participants in the intervention arm will receive a simple health literacy intervention on lifestyle modification, which will be delivered by trained CHWs, while those in the control arm will receive usual care. The intervention consists of 4 face-to-face interactive educational sessions and monthly support visits by trained CHWs and will be carried out over a period of 6 months. The primary study outcomes will be blood pressure and blood glucose levels and levels of adherence to the recommended lifestyle modifications. Other outcomes will include adherence to medication. Data management and analysis will be done using Epi Info software, and the data will be analyzed using the intention-to-treat principle.

RESULTS

Recruitment of study participants commenced on June 1, 2023, and was completed on July 30, 2023. Baseline data are being collected after participants' recruitment, and the final data collection will be completed by January 31, 2024.

CONCLUSIONS

There is an information dearth regarding the effectiveness of CHW-led interventions for the management and control of hypertension in Zimbabwe. Our study offers an opportunity to show the effectiveness of CHWs in addressing the gaps in the management of hypertension and diabetes. The findings from our study will provide crucial evidence on the effectiveness and feasibility of a simple intervention delivered by CHWs in resource-constrained areas.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47512.

Long non-coding RNAs: The hidden players in diabetes mellitus-related complications

BACKGROUND AND AIM

Long non-coding RNAs (lncRNAs) have been recognized as important regulators of gene expression in various human diseases. Diabetes mellitus (DM) is a long-term metabolic disorder associated with serious macro and microvascular complications. This review discusses the potential lncRNAs involved in DM-related complications such as dysfunction of pancreatic beta islets, nephropathy, retinopathy, cardiomyopathy, and peripheral neuropathy.

METHODS

An extensive literature search was conducted in the Scopus database to find information from reputed biomedical articles published on lncRNAs and diabetic complications from 2014 to 2023. All review articles were collected and statistically analyzed, and the findings were summarized. In addition, the potential lncRNAs involved in DM-related complications, molecular mechanisms, and gene targets were discussed in detail.

RESULTS

The lncRNAs ANRIL, E33, MALAT1, PVT1, Erbb4-IR, Gm4419, Gm5524, MIAT, MEG3, KNCQ1OT1, Uc.48+, BC168687, HOTAIR, and NONRATT021972 were upregulated in several diabetic complications. However, βlinc1, H19, PLUTO, MEG3, GAS5, uc.322, HOTAIR, MIAT, TUG1, CASC2, CYP4B1-PS1-001, SOX2OT, and Crnde were downregulated. Remarkably, lncRNAs MALAT1, ANRIL, MIAT, MEG3, H19, and HOTAIR were overlapping in more than one diabetic complication and were considered potential lncRNAs.

CONCLUSION

Several lncRNAs are identified as regulators of DM-related complications. The expression of lncRNAs is up or downregulated depending on the disease context, target genes, and regulatory partners. However, most lncRNAs target oxidative stress, inflammation, apoptosis, fibrosis, and angiogenesis pathways to mediate their protective/pathogenic mechanism of action and contribute to DM-related complications.

Factors associated with cutaneous colonization of Mucormycetes in diabetic and non-diabetic individuals

This study was conducted to assess factors associated with cutaneous colonization of Mucormycetes in diabetic and non-diabetic individuals. A total of 800 swab samples from 200 participants including 100 diabetics and 100 non-diabetics were collected from four different body sites: (1) the forehead, (2) nasal cavity, (3) hands and (4) feet. Fungal isolation, fungal identification and antibiotic sensitivity tests were performed on the isolates. Overall, 12.0 % of the participants showed Mucormycetes colonization while the commonest fungal isolates were Mucor Species (Spp.). followed by Rhizopus spp. Diabetics had a 11 times higher odds of colonization compared to non-diabetics. The majority of the isolates were resistant to itraconazole; however, all isolates were sensitive to amphotericin B. A significant association was observed between profession and Mucormycetes (P=0.03) with significantly higher colonization in retired people compared to business people. Higher odds of colonization were demonstrated among older ages, lower class status and individuals with prolonged contact time with soil.

Recent Advances in Electrospun Nanofiber-Based Strategies for Diabetic Wound Healing Application

Diabetic ulcers are the second largest complication caused by diabetes mellitus. A great number of factors, including hyperchromic inflammation, susceptible microbial infection, inferior vascularization, the large accumulation of free radicals, and other poor healing-promoting microenvironments hold back the healing process of chronic diabetic ulcer in clinics. With the increasing clinical cases of diabetic ulcers worldwide, the design and development of advanced wound dressings are urgently required to accelerate the treatment of skin wounds caused by diabetic complications. Electrospinning technology has been recognized as a simple, versatile, and cost-reasonable strategy to fabricate dressing materials composed of nanofibers, which possess excellent extracellular matrix (ECM)-mimicking morphology, structure, and biological functions. The electrospinning-based nanofibrous dressings have been widely demonstrated to promote the adhesion, migration, and proliferation of dermal fibroblasts, and further accelerate the wound healing process compared with some other dressing types like traditional cotton gauze and medical sponges, etc. Moreover, the electrospun nanofibers are commonly harvested in the structure of nonwoven-like mats, which possess small pore sizes but high porosity, resulting in great microbial barrier performance as well as excellent moisture and air permeable properties. They also serve as good carriers to load various bioactive agents and/or even living cells, which further impart the electrospinning-based dressings with predetermined biological functions and even multiple functions to significantly improve the healing outcomes of different chronic skin wounds while dramatically shortening the treatment procedure. All these outstanding characteristics have made electrospun nanofibrous dressings one of the most promising dressing candidates for the treatment of chronic diabetic ulcers. This review starts with a brief introduction to diabetic ulcer and the electrospinning process, and then provides a detailed introduction to recent advances in electrospinning-based strategies for the treatment of diabetic wounds. Importantly, the synergetic application of combining electrospinning with bioactive ingredients and/or cell therapy was highlighted. The review also discussed the advantages of hydrogel dressings by using electrospun nanofibers. At the end of the review, the challenge and prospects of electrospinning-based strategies for the treatment of diabetic wounds are discussed in depth.

Peer Support Self-Management Intervention for Individuals With Type 2 Diabetes in Rural Primary Care Settings: Protocol for a Mixed Methods Study

BACKGROUND

The increasing prevalence of diabetes is placing important demands on the Chinese health care system. Providing self-management programs to the fast-growing number of people with diabetes presents an urgent need in rural primary care settings in China. Peer support has demonstrated effectiveness in improving self-management for individuals with diabetes in urban communities in China. A priority then becomes developing and evaluating a peer support program in primary care settings in rural communities of China and determining whether it is feasible and acceptable.

OBJECTIVE

The aims of this study are (1) to evaluate the feasibility and acceptability of a peer support approach to type 2 diabetes self-management in rural primary care settings; (2) to identify enabler and facilitator factors likely to influence the peer support implementation; (3) to provide primary data and evidence for developing a version of the program suitable for a randomized controlled trial in rural primary care settings.

METHODS

Three townships will be sampled from 3 different counties of Anhui province as the study setting. Participants will be recruited based on these counties' local primary care health record system. The peer supporters will be recruited from among the participants. The peer support program will be led by peer supporters who have completed 12 hours of training. It will be guided by primary care providers. The program will include biweekly meetings over 3 months with varied peer support contacts between meetings to encourage the implementation of diabetes self-management. Mixed methods will be used for evaluation. Qualitative methods will be used to collect information from health care system professionals, individuals with diabetes, and peer supporters. Quantitative methods will be used to collect baseline data and data at the end of the 3-month intervention regarding psychosocial factors and self-management practices.

RESULTS

The results will include (1) quantitative baseline data that will characterize type 2 diabetes self-management practices of individuals with diabetes; (2) qualitative data that will identify enablers of and barriers to self-management practices for individuals with type 2 diabetes in rural communities; (3) both qualitative and quantitative evaluation data, after the 3-month intervention, to demonstrate the feasibility and acceptability of the peer support approach for individuals with type 2 diabetes.

CONCLUSIONS

Our findings will inform the design of a tailored intervention program to improve self-management among individuals with type 2 diabetes in rural primary care settings. If we find that the peer support approach is feasible and acceptable, we will develop a larger randomized controlled trial to evaluate effectiveness in multiple rural settings in the province.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/47822.

Modulation of Altered Immune Parameters IL-2 and TNF-α in Diabetic Animal Models: A Therapeutic Insinuation of Metformin Beyond Diabetes

BACKGROUND

Immunomodulatory drugs target the overall immune system, hence producing numerous toxic effects on the other organs with serious health manifestations. Due to these safety concerns, there is a need to introduce or repurpose a new drug with immunomodulatory effects with good safety, efficacy, and better tolerance. Metformin, a standard antidiabetic drug, was evaluated for its immunomodulatory effects in diabetic models in the current study.

METHODOLOGY

The diabetic model was developed by intraperitoneal (IP) administration of streptozotocin (60 mg/kg). The experimental rats were divided into six groups (three diabetic and three non-diabetic) with six rats in each group. Metformin (50 mg/kg and 80 mg/kg) was given orally to both diabetic and non-diabetic groups, once a day, for 42 days. Immunomodulatory cytokines interleukin (IL)-2, IL-4, IL-5, tumor necrosis factor (TNF)-α, and interferon gamma (INF-ɣ) were analyzed from blood samples by BD FCAP flow cytometer.

RESULTS

The results revealed a significant (p=0.002) decrease in IL-2 and TNF-α in diabetic groups in comparison to control rats. However, no significant changes were observed in IL-4, IL-5, and INF-ɣ levels. Importantly, the treatment of metformin at both doses, i.e., 50 and 80 mg/kg, significantly reduced the elevated levels of IL-2 and TNF-α when compared to untreated diabetic groups.

CONCLUSION

Metformin may be considered as an optimum drug candidate to reduce pro-inflammatory cytokines, IL-2 and TNF-α, that can lead to the reduction of long-term diabetic complications.

Severe and fatal COVID-19 is characterised by increased circulating glucagon like peptide 1 and procalcitonin modulated by type 2 diabetes

AIMS

Endotoxemia commonly occurs in severe and fatal COVID-19, suggesting that concomitant bacterial stimuli may amplify the innate immune response induced by SARS-CoV-2. We previously demonstrated that the endogenous glucagon like peptide 1 (GLP-1) system in conjunction with increased procalcitonin (PCT) is hyperactivated in patients with severe Gram-negative sepsis and modulated by type 2 diabetes (T2D). We aimed to determine the association of COVID-19 severity with endogenous GLP-1 activation upregulated by increased specific pro-inflammatory innate immune response in patients with and without T2D.

MATERIALS AND METHODS

Plasma levels of total GLP-1, IL-6, and PCT were estimated on admission and during hospitalisation in 61 patients (17 with T2D) with non-severe and severe COVID-19.

RESULTS

COVID-19 patients demonstrated ten-fold increase of IL-6 levels regardless of disease severity. Increased admission GLP-1 levels (p = 0.03) accompanied by two-fold increased PCT were found in severe as compared with non-severe patients. Moreover, GLP-1 and PCT levels were significantly increased in non-survived as compared with survived patients at admission (p = 0.01 and p = 0.001, respectively) and at 5 to 6 days of hospitalisation (p = 0.05). Both non-diabetic and T2D patients demonstrated a positive correlation between GLP-1 and PCT response (r = 0.33, p = 0.03, and r = 0.54, p = 0.03, respectively), but the intensity of this joint pro-inflammatory/GLP-1 response was modulated by T2D. In addition, hypoxaemia down-regulated GLP-1 response only in T2D patients with bilateral lung damage.

CONCLUSIONS

The persistent joint increase of endogenous GLP-1 and PCT in severe and fatal COVID-19 suggests a role of concomitant bacterial infection in disease exacerbation. Early elevation of endogenous GLP-1 may serve as a new biomarker of COVID-19 severity and fatal outcome.

Adapting the Diabetes Prevention Program for Older Adults: Descriptive Study

BACKGROUND

Prediabetes affects 26.4 million people aged 65 years or older (48.8%) in the United States. Although older adults respond well to the evidence-based Diabetes Prevention Program, they are a heterogeneous group with differing physiological, biomedical, and psychosocial needs who can benefit from additional support to accommodate age-related changes in sensory and motor function.

OBJECTIVE

The purpose of this paper is to describe adaptations of the Centers for Disease Control and Prevention's Diabetes Prevention Program aimed at preventing diabetes among older adults (ages ≥65 years) and findings from a pilot of 2 virtual sessions of the adapted program that evaluated the acceptability of the content.

METHODS

The research team adapted the program by incorporating additional resources necessary for older adults. A certified lifestyle coach delivered 2 sessions of the adapted content via videoconference to 189 older adults.

RESULTS

The first session had a 34.9% (38/109) response rate to the survey, and the second had a 34% (30/88) response rate. Over three-quarters (50/59, 85%) of respondents agreed that they liked the virtual program, with 82% (45/55) agreeing that they would recommend it to a family member or a friend.

CONCLUSIONS

This data will be used to inform intervention delivery in a randomized controlled trial comparing in-person versus virtual delivery of the adapted program.

Social Determinants of Health Documentation in Structured and Unstructured Clinical Data of Patients With Diabetes: Comparative Analysis

Background

Electronic health records (EHRs) have yet to fully capture social determinants of health (SDOH) due to challenges such as nonexistent or inconsistent data capture tools across clinics, lack of time, and the burden of extra steps for the clinician. However, patient clinical notes (unstructured data) may be a better source of patient-related SDOH information.

Objective

It is unclear how accurately EHR data reflect patients' lived experience of SDOH. The manual process of retrieving SDOH information from clinical notes is time-consuming and not feasible. We leveraged two high-throughput tools to identify SDOH mappings to structured and unstructured patient data: PatientExploreR and Electronic Medical Record Search Engine (EMERSE).

Methods

We included adult patients (≥18 years of age) receiving primary care for their diabetes at the University of California, San Francisco (UCSF), from January 1, 2018, to December 31, 2019. We used expert raters to develop a corpus using SDOH in the compendium as a knowledge base as targets for the natural language processing (NLP) text string mapping to find string stems, roots, and syntactic similarities in the clinical notes of patients with diabetes. We applied advanced built-in EMERSE NLP query parsers implemented with JavaCC.

Results

We included 4283 adult patients receiving primary care for diabetes at UCSF. Our study revealed that SDOH may be more significant in the lives of patients with diabetes than is evident from structured data recorded on EHRs. With the application of EMERSE NLP rules, we uncovered additional information from patient clinical notes on problems related to social connectionsisolation, employment, financial insecurity, housing insecurity, food insecurity, education, and stress.

Conclusions

We discovered more patient information related to SDOH in unstructured data than in structured data. The application of this technique and further investment in similar user-friendly tools and infrastructure to extract SDOH information from unstructured data may help to identify the range of social conditions that influence patients' disease experiences and inform clinical decision-making.

Internet-Based Recruitment and Retention of Young Adults With Type 1 Diabetes: Cross-Sectional Study

BACKGROUND

Multiple research strategies are required to recruit and engage a representative cohort of young adults in diabetes research. In this report, we describe an approach for internet-based recruitment for a repeated-measures descriptive study.

OBJECTIVE

The objective of this cross-sectional study was to determine whether internet-based recruitment through multiple social media platforms, a clinical research platform, and cooperation with community partnerships-College Diabetes Network and Beyond Type 1-would serve as an effective way to recruit a representative sample of young adults aged 18-25 years with type 1 diabetes (T1D).

METHODS

We conducted a repeated-measures descriptive study. We captured enrollment rates and participant characteristics acquired from each social media platform through survey data and Facebook analytics. This study was advertised via paid postings across a combination of different social media platforms (eg, Facebook, Instagram, Twitter, and Reddit). We used quarterly application postings, quarterly newsletters, and participation in the ResearchMatch registry to identify potentially eligible participants from February 3, 2021, to June 6, 2022.

RESULTS

ResearchMatch proved to be the most cost-effective strategy overall, yielding the highest gender and racial diversity compared to other internet platforms (eg, Facebook, Instagram, Twitter, and Reddit), application postings (eg, Beyond Type 1), and newsletters (eg, College Diabetes Network and a local area college). However, we propose that the combination of these approaches yielded a larger, more diverse sample compared to any individual strategy. Our recruitment cost was US $16.69 per eligible participant, with a 1.27% conversion rate and a 30% eligibility rate.

CONCLUSIONS

Recruiting young adults with T1D across multiple internet-based platforms was an effective strategy to yield a moderately diverse sample. Leveraging various recruitment strategies is necessary to produce a representative sample of young adults with T1D. As the internet becomes a larger forum for study recruitment, participants from underrepresented backgrounds may continue engaging in research through advertisements on the internet and other internet-based recruitment platforms.

Exploring the Impact of Dawn Phenomenon on Glucose-Guided Eating Thresholds in Individuals With Type 2 Diabetes Using Continuous Glucose Monitoring: Observational Study

BACKGROUND

Glucose-guided eating (GGE) improves metabolic markers of chronic disease risk, including insulin resistance, in adults without diabetes. GGE is a timed eating paradigm that relies on experiencing feelings of hunger and having a preprandial glucose level below a personalized threshold computed from 2 consecutive morning fasting glucose levels. The dawn phenomenon (DP), which results in elevated morning preprandial glucose levels, could cause typically derived GGE thresholds to be unacceptable or ineffective among people with type 2 diabetes (T2DM).

OBJECTIVE

The aim of this study is to quantify the incidence and day-to-day variability in the magnitude of DP and examine its effect on morning preprandial glucose levels as a preliminary test of the feasibility of GGE in adults with T2DM.

METHODS

Study participants wore a single-blinded Dexcom G6 Pro continuous glucose monitoring (CGM) system for up to 10 days. First and last eating times and any overnight eating were reported using daily surveys over the study duration. DP was expressed as a dichotomous variable at the day level (DP day vs non-DP day) and as a continuous variable reflecting the percent of days DP was experienced on a valid day. A valid day was defined as having no reported overnight eating (between midnight and 6 AM). ∂ Glucose was computed as the difference in nocturnal glucose nadir (between midnight and 6 AM) to morning preprandial glucose levels. ∂ Glucose ≥20 mg/dL constituted a DP day. Using multilevel modeling, we examined the between- and within-person effects of DP on morning preprandial glucose and the effect of evening eating times on DP.

RESULTS

In total, 21 adults (59% female; 13/21, 62%) with non-insulin-treated T2DM wore a CGM for an average of 10.5 (SD 1.1) days. Twenty out of 21 participants (95%) experienced DP for at least 1 day, with an average of 51% of days (SD 27.2; range 0%-100%). The mean ∂ glucose was 23.7 (SD 13.2) mg/dL. People who experience DP more frequently had a morning preprandial glucose level that was 54.1 (95% CI 17.0-83.9; P<.001) mg/dL higher than those who experienced DP less frequently. For within-person effect, morning preprandial glucose levels were 12.1 (95% CI 6.3-17.8; P=.008) mg/dL higher on a DP day than on a non-DP day. The association between ∂ glucose and preprandial glucose levels was 0.50 (95% CI 0.37-0.60; P<.001). There was no effect of the last eating time on DP.

CONCLUSIONS

DP was experienced by most study participants regardless of last eating times. The magnitude of the within-person effect of DP on morning preprandial glucose levels was meaningful in the context of GGE. Alternative approaches for determining acceptable and effective GGE thresholds for people with T2DM should be explored and evaluated.

Use of a Smartphone-Based Medication Adherence Platform to Improve Outcomes in Uncontrolled Type 2 Diabetes Among Veterans: Prospective Case-Crossover Study

BACKGROUND

Medication nonadherence is a problem that impacts both the patient and the health system.

OBJECTIVE

The objective of this study was to evaluate the impact of a novel smartphone app with patient-response-directed clinical intervention on medication adherence and blood glucose control in noninsulin-dependent patients with type 2 diabetes mellitus (T2DM).

METHODS

We enrolled 50 participants with T2DM not on insulin with smartphones from a rural health care center in Northern Nevada for participation in this case-crossover study. Participants underwent a standard of care arm and an intervention arm. Each study arm was 3 months long, for a total of 6 months of follow-up. Participants had a hemoglobin A1c (HbA1c) lab draw at enrollment, 3 months, and 6 months. Participants had monthly "medication adherence scores" (MAS) and "Self-Efficacy for Appropriate Medication Use Scale" (SEAMS) questionnaires completed at baseline and monthly for the duration of the study. Our primary outcomes of interest were the changes in HbA1c between study arms. Secondary outcomes included the evaluation of the difference in the proportion of participants achieving a clinically meaningful reduction in HbA1c and the difference in the number of participants requiring diabetes therapy escalation between study arms. Exploratory outcomes included the analysis of the variation in medication possession ratio (MPR), MAS, and SEAMS during each study arm.

RESULTS

A total of 30 participants completed both study arms and were included in the analysis. Dropouts were higher in participants enrolled in the standard of care arm first (9/25, 36% vs 4/25, 16%). Participants had a median HbA1c of 9.1%, had been living with T2DM for 6 years, had a median age of 66 years, and had a median of 8.5 medications. HbA1c reduction was 0.69% in the intervention arm versus 0.35% in the standard of care arm (P=.30). A total of 70% (21/30) of participants achieved a clinically meaningful reduction in HbA1c of 0.5% in the app intervention arm versus 40% (12/30) in the standard of care arm (odds ratio 2.29, 95% CI 0.94-5.6; P=.09). Participants had higher odds of a therapy escalation while in the standard of care arm (18/30, 60% vs 5/30, 16.7%, odds ratio 4.3, 95% CI 1.2-15.2; P=.02). The median MPR prior to enrollment was 109%, 112% during the study's intervention arm, and 102% during the standard of care arm. The median real-time MAS was 93.2%. The change in MAS (1 vs -0.1; P=.02) and SEAMS (1.9 vs -0.2; P<.001) from baseline to month 3 was higher in the intervention arm compared to standard of care.

CONCLUSIONS

A novel smartphone app with patient-response-directed provider intervention holds promise in the ability to improve blood glucose control in complex non-insulin-dependent T2DM and is worthy of additional study.

Using Continuous Glucose Monitoring and Data Sharing to Encourage Collaboration Among Older Adults With Type 1 Diabetes and Their Care Partners: Qualitative Descriptive Study

BACKGROUND

Persons with diabetes use continuous glucose monitoring (CGM) to self-manage their diabetes. Care partners (CPs) frequently become involved in supporting persons with diabetes in the management of their diabetes. However, persons with diabetes and CP dyads may require more communication and problem-solving skills regarding how to share and respond to CGM data.

OBJECTIVE

The purpose of this study was to describe the experiences of persons with diabetes and CPs who participated in the Share "plus" intervention, which addresses dyadic communication strategies, problem-solving, and action planning to promote sharing of CGM data among the dyad.

METHODS

Ten dyads participated in the Share "plus" telehealth intervention. Participants were interviewed during and after the Share "plus" intervention. Thematic analysis was used to analyze interview data.

RESULTS

During postsession interviews, dyads described feeling a sense of shared responsibility yet viewed the persons with diabetes as ultimately responsible for the disease. Additionally, dyads shared that communication patterns improved and were able to recognize the negative aspects of previously established communication patterns. Dyads reported communication focused on hypoglycemia episodes while also differing in the frequency they reviewed CGM data and set alerts. Overall, dyads expressed positive reactions to the Share "plus" intervention.

CONCLUSIONS

Share "plus" was helpful in promoting positive CGM-related communication among dyads and encouraged more CP support. CPs play an important role in supporting older adults with type 1 diabetes. Communication strategies help support dyad involvement in CGM data sharing and self-management among persons with diabetes.

Designing a Collaborative Patient-Centered Digital Health Platform for Pediatric Diabetes Care in British Columbia: Formative Needs Assessment by Caregivers of Children and Youths Living With Type 1 Diabetes and Health Care Providers

BACKGROUND

Digital health apps are becoming increasingly available for people living with diabetes, yet data silos continue to exist. This requires health care providers (HCPs) and patients to use multiple digital platforms to access health data.

OBJECTIVE

In this study, we gathered the perspectives of caregivers of children and youths living with type 1 diabetes (T1D) and pediatric diabetes HCPs in the user-centered design of TrustSphere, a secure, single-point-of-access, integrative digital health platform.

METHODS

We distributed web-based surveys to caregivers of children and youths living with T1D and pediatric diabetes HCPs in British Columbia, Canada. Surveys were designed using ordinal scales and had free-text questions. Survey items assessed key challenges, perceptions about digital trust and security, and potential desirable features for a digital diabetes platform.

RESULTS

Similar challenges were identified between caregivers of children and youths living with T1D (n=99) and HCPs (n=49), including access to mental health support, integration of diabetes technology and device data, and the ability to collaborate on care plans with their diabetes team. Caregivers and HCPs identified potential features that directly addressed their challenges, such as more accessible diabetes data and diabetes care plans. Caregivers had more trust in sharing their child's data digitally than HCPs. Most caregivers and HCPs stated that an integrative platform for T1D would support collaborative patient care.

CONCLUSIONS

Caregiver and HCP perspectives gathered in this study will inform the early prototype of an integrative digital health platform. This prototype will be presented and iterated upon through a series of usability testing sessions with caregivers and HCPs to ensure the platform meets end users' needs.