Diabetes Program Research Articles

Effects of a Salutogenic Healthy Eating Program in Type 2 Diabetes (the SALUD Study): Protocol for a Randomized Controlled Trial.

Healthy eating can improve the course of type 2 diabetes mellitus (T2DM) considerably. As changing eating behaviors in everyday is challenging, there is a need for a nutritional strategy with an eye for everyday life of people with T2DM. A theory centered around the everyday life context is salutogenesis. Salutogenic principles have been operationalized in a new nutritional program for T2DM on food literacy and well-being: the Salutogenic Intervention for Type 2 Diabetes (SALUD) program. This study aims to describe the protocol of the invention study that will examine the quantitative and qualitative effects of the SALUD program. A semiblinded randomized controlled trial will be performed in the Netherlands. A sample size of 56 (including a 30% dropout rate) people with T2DM has been calculated, of whom half (n=28, 50%) will follow the SALUD program (intervention) and half (n=28, 50%) will receive usual care (control). Recruitment strategies consist of advertisement via local health care professionals, posters, social media, and local newspapers. The SALUD program consists of 12 weekly web-based group sessions under the supervision of a certified lifestyle coach. Fidelity of the delivery is guaranteed by selecting a salutogenic coach, use of an intervention manual, training of the coach, weekly evaluation forms, and recording several sessions. The theoretical salutogenic principle of the intervention is mobilizing 2 important psychosocial resources required for organizing healthy eating in everyday life: self-identity and social support. Measurements will be performed at 3 times: at baseline (T0), after 12 weeks (postintervention; T1), and after 24 weeks (follow-up; T2). The primary outcome is food literacy, measured with the self-perceived food literacy scale questionnaire (expected effect size=0.9). Secondary outcomes are self-efficacy, quality of life, sense of coherence, diet quality, body weight, BMI, and waist-hip ratio. All outcomes will be tested with linear mixed models, following an intention-to-treat approach and standard principles of randomized controlled trials. In addition, a qualitative analysis will be performed. The proposed study will provide useful information on the effects of a salutogenic program on healthy eating and well-being in people with T2DM in everyday life. Recruitment started on October 1, 2021. The intervention participants followed the SALUD program between January and August, 2022. The acquisition of the data was completed on August 1, 2022; publications are expected in 2023. This study will be one of the first salutogenic interventions for T2DM, which will provide valuable information on what salutogenic intervention entail. The SALUD program may serve as a concrete, web-based tool. The combination of quantitative and qualitative measures allows a comprehensive evaluation of effects. These insights can be used for further optimalization of T2DM interventions. Netherlands Trial Registry, NL8963; https://trialsearch.who.int/Trial2.aspx?TrialID=NL8963. DERR1-10.2196/40490.

Association between stress hyperglycemia and outcomes in patients with acute ischemic stroke due to large vessel occlusion.

This study aimed to evaluate the association between stress hyperglycemia ratio (SHR) and clinical outcomes at 90 days in acute ischemic stroke due to large vessel occlusion receiving endovascular treatment. The RESCUE BT trial was a multicenter, randomized, double-blind, placebo-controlled clinical trial, consisting of 948 stroke patients from 55 centers in China. A total of 542 patients with glucose and glycated hemoglobin (HbA1C) values at admission were included in this analysis. SHR, measured by glucose/HbA1C, was evaluated as both a tri-categorical variable (≤1.07 vs. 1.08-1.29 vs. ≥1.30) and a continuous variable. The primary outcome was a favorable functional outcome (modified Rankin Scale [mRS] score ≤2) at 90 days. The secondary outcome included excellent functional outcome (mRS score ≤1) and safety outcomes, such as 90-day mortality and intracranial hemorrhage. The study was registered with Chictr.org.cn (ChiCTR-INR-17014167). Compared with patients in the lowest tertile of SHR, the highest tertile group had significantly lower odds of achieving favorable functional outcome of mRS score of 0-2 (adjusted odds ratio, 0.44; 95% confidence interval, 0.28-0.69; p < 0.001) and excellent clinical outcome of mRS score of 0-1 (adjusted odds ratio, 0.48; 95% confidence interval, 0.29-0.79; p=0.004) at 90 days after adjusting for potential covariates. Similar results were observed after further adjustment for preexisting diabetes and Alberta Stroke Program Early Computed Tomography Score (ASPECTS). Stress hyperglycemia ratio, as measured by the glucose/HbA1C, was associated with a decreased odds of achieving a favorable functional outcome in patients with acute large vessel occlusion stroke at 90 days.

Performance of an artificial intelligence automated system for diabetic eye screening in a large English population.

A diabetic eye screening programme has huge value in reducing avoidable sight loss by identifying diabetic retinopathy at a stage when it can be treated. Artificial intelligence automated systems can be used for diabetic eye screening but are not employed in the national English Diabetic Eye Screening Programme. The aim was to report the performance of a commercially available deep-learning artificial intelligence software in a large English population. 9817 anonymised image sets from 10,000 consecutive diabetic eye screening episodes were presented to an artificial intelligence software. The sensitivity and specificity of the artificial intelligence system for detecting diabetic retinopathy were determined using the diabetic eye screening programme manual grade according to national protocols as the reference standard. For no diabetic retinopathy versus any diabetic retinopathy, the sensitivity of the artificial intelligence grading system was 69.7% and specificity 92.2%. The performance of the artificial intelligence system was superior for no or mild diabetic retinopathy versus significant or referrable diabetic retinopathy with a sensitivity of 95.4% and specificity of 92.0%. No cases were identified in which the artificial intelligence grade had missed significant diabetic retinopathy. The performance of a commercially available deep-learning artificial intelligence system for identifying diabetic retinopathy in an English national Diabetic Eye Screening Programme is presented. Using the pre-defined settings artificial intelligence performance was highest when identifying diabetic retinopathy which requires an action by the screening programme.

Convolutional Neural Networks Accurately Identify Ungradable Images in a Diabetic Retinopathy Telemedicine Screening Program.

Purpose: Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM). Standard of care for patients with DM is an annual eye examination or retinal imaging to assess for DR, the latter of which may be completed through telemedicine approaches. One significant issue is poor-quality images that prevent adequate screening and are thus ungradable. We used artificial intelligence to enable point-of-care (at time of imaging) identification of ungradable images in a DR screening program. Methods: Nonmydriatic retinal images were gathered from patients with DM imaged during a primary care or endocrinology visit from September 1, 2017, to June 1, 2021. The Topcon TRC-NW400 retinal camera (Topcon Corp., Tokyo, Japan) was used. Images were interpreted by 5 ophthalmologists for gradeability, presence and stage of DR, and presence of non-DR pathologies. A convolutional neural network with Inception V3 network architecture was trained to assess image gradeability. Images were divided into training and test sets, and 10-fold cross-validation was performed. Results: A total of 1,377 images from 537 patients (56.1% female, median age 58) were analyzed. Ophthalmologists classified 25.9% of images as ungradable. Of gradable images, 18.6% had DR of varying degrees and 26.5% had non-DR pathology. 10 fold cross-validation produced an average area under receiver operating characteristic curve (AUC) of 0.922 (standard deviation: 0.027, range: 0.882 to 0.961). The final model exhibited similar test set performance with an AUC of 0.924. Conclusions: This model accurately assesses gradeability of nonmydriatic retinal images. It could be used for increasing the efficiency of DR screening programs by enabling point-of-care identification of poor-quality images.

Effectiveness of a diabetes program based on digital health on capacity building and quality of care in type 2 diabetes: a pragmatic quasi-experimental study

Health systems in Latin America face many challenges in controlling the increasing burden of diabetes. Digital health interventions are a promise for the provision of care, especially in developing countries where mobile technology has a high penetration. This study evaluated the effectiveness of the implementation of a Diabetes Program (DP) that included digital health interventions to improve the quality of care of persons with type 2 Diabetes (T2DM) in a vulnerable population attending the public primary care network.Materials and methodsA quasi-experimental pre-post uncontrolled study was conducted in 19 primary care centers and hospitals in the province of Corrientes, Argentina. We included persons with T2DM, age > = 18 years with access to a mobile phone. The multicomponent intervention included a mobile app with a diabetes registry, a clinical decision support tool for providers and a text messaging intervention for patients.Results and discussionOne thousand sixty-five participants were included, 72.8% had less than 12 years of formal education and 53.5% lacked health coverage. Comorbidities were hypertension (60.8%) and overweight/obesity (88.2%). During follow-up there was a significant increase in the proportion of participants who underwent laboratory check-ups (HbA1c 20.3%-64.4%; p < 0.01) and foot exams (62.1%-87.2%; p < 0.01). No changes were observed at 12 and 24 months in the proportion of participants with poor metabolic control. The proportion of participants with uncontrolled blood pressure (≥ 140/90 mmHg) decreased from 47.2% at baseline to 30.8% at 24 months in those with a follow-up visit.ConclusionThe DP was innovative by integrating digital health interventions in the public primary care level. The study showed improvements in quality indicators related with diabetes care processes and in blood pressure control.

Uptake and effectiveness of online diabetes continuing education: The perspectives of Thai general practitioner trainees

BackgroundDespite continuing medical education (CME) programmes on evidence-based diabetes care, evidence-based best practice and actual GP practice remain scant. Online CME offers numerous benefits to general practitioners (GPs), particularly during the coronavirus disease 2019 (COVID-19) pandemic. In Thailand, CME is a voluntary process and is yet to be established as a mandatory requirement. This study examined GP uptake of online diabetes CME and the changes in GPs’ attitudes to and knowledge of Type 2 diabetes management. MethodsA cross-sectional study and a before-and-after study were employed with 279 GP trainees who voluntarily undertook a newly-developed online diabetes programme. A follow-up survey was conducted six months after the GP trainees completed their training. ResultsOne hundred and twelve out of 279 GP trainees (40.1%) participated in the study, of whom 37 (13.3%) enrolled in the online diabetes programme, and 20 (7.2%) completed the programme. Before enrolling in the programme, the participants' mean diabetes knowledge score was 61.5%. The participants’ confidence in effective insulin treatment increased significantly after the programme (95% Confidence interval [CI], −0.51-0.00; P = 0.05), but their knowledge scores before and after the programme were not statistically different (95% CI, −3.93-0.59; P = 0.14). ConclusionUptake of the online diabetes CME was poor, although appropriate recruitment strategies were employed, and the online educational option was attractive and accessible during the COVID-19 pandemic. This study emphasises the gap between evidence-based practice and actual GP practice and the need for mandatory CME.

Identifying the necessary capacities for the adaptation of a diabetes phenotyping algorithm in countries of differing economic development status

ABSTRACT Background In 2019, the World Health Organization recognised diabetes as a clinically and pathophysiologically heterogeneous set of related diseases. Little is currently known about the diabetes phenotypes in the population of low- and middle-income countries (LMICs), yet identifying their different risks and aetiology has great potential to guide the development of more effective, tailored prevention and treatment. Objectives This study reviewed the scope of diabetes datasets, health information ecosystems, and human resource capacity in four countries to assess whether a diabetes phenotyping algorithm (developed under a companion study) could be successfully applied. Methods The capacity assessment was undertaken with four countries: Trinidad, Malaysia, Kenya, and Rwanda. Diabetes programme staff completed a checklist of available diabetes data variables and then participated in semi-structured interviews about Health Information System (HIS) ecosystem conditions, diabetes programme context, and human resource needs. Descriptive analysis was undertaken. Results Only Malaysia collected the full set of the required diabetes data for the diabetes algorithm, although all countries did collect the required diabetes complication data. An HIS ecosystem existed in all settings, with variations in data hosting and sharing. All countries had access to HIS or ICT support, and epidemiologists or biostatisticians to support dataset preparation and algorithm application. Conclusions Malaysia was found to be most ready to apply the phenotyping algorithm. A fundamental impediment in the other settings was the absence of several core diabetes data variables. Additionally, if countries digitise diabetes data collection and centralise diabetes data hosting, this will simplify dataset preparation for algorithm application. These issues reflect common LMIC health systems’ weaknesses in relation to diabetes care, and specifically highlight the importance of investment in improving diabetes data, which can guide population-tailored prevention and management approaches.

AI telemedicine screening in ophthalmology: health economic considerations

AI telemedicine screening in ophthalmology: health economic considerations

Project ECHO Diabetes Cost Modeling to Support the Replication and Expansion of Tele-mentoring Programs in Non-research Settings.

Project ECHO Diabetes is a tele-education learning model for primary care providers (PCPs) seeking to improve care for patients with diabetes from marginalized communities. Project ECHO Diabetes utilized expert "hub" teams comprising endocrinologists, dieticians, nurses, psychologists, and social workers and "spokes" consisting of PCPs and their patients with diabetes. This Project ECHO Diabetes model provided diabetes support coaches to provide additional support to patients. We sought to estimate the costs of operating a Project ECHO Diabetes hub, inclusive of diabetes support coach costs. Data from Project ECHO Diabetes from June 2021 to June 2022 and wages from national databases were used to estimate hub and diabetes support coach costs to operate a 6-month, 24-session Project ECHO Diabetes program at hubs (University of Florida and StanfordUniversity) and spokes (PCP clinic sites in Florida and California). Hub costs for delivering a 6-month Project ECHO Diabetes program to five spoke clinics were $96,873. Personnel costs were the principal driver. Mean cost was $19,673 per spoke clinic and $11.37 per spoke clinic patient. Diabetes support coach costs were estimated per spoke clinic and considered scalable in that they would increase proportionately with the number of spoke clinics in a Project ECHO Diabetes cohort. Mean diabetes support coach costs were $6,506 per spoke clinic and $3.72 per patient. Total program costs per hub were $129,404. Mean cost per clinic was $25,881. Mean cost per patient was $15.03. Herein, we document real-world costs to operate a Project ECHO Diabetes hub and diabetes support coaches. Future analysis of Project ECHO Diabetes will include estimates of spoke participation costs andchanges in health care costs and savings. As state agencies, insurers, and philanthropies consider the replication of Project ECHO Diabetes, this analysis provides important initial information regarding primary operating costs.

Assessing the Effectiveness of Culturally Specific Diabetic Management Programs within Primary Health Care Settings: A Review of the Literature

Introduction: Diabetic management programs play an important role in supporting people who live with diabetes and preventing diabetes related complications. These programs need to be culturally relevant to be successful. Aim: To explore culturally specific diabetic management programs within primary health care settings that can be adapted to the context of Qatar. Method: This literature review was guided by Cronin et al.’s (2008) framework and included 17 scholarly articles published between 2011 and 2021. The Mixed Method Appraisal Tool was used to critically appraise the quality of these articles. Results: The main components of culturally specific diabetic management programs are information and understanding, cultural norms, cultural interventions, and personal motivation. Discussion: In order to ameliorate diabetes management for clients, culture needs to be considered when providing education. Key terms: Diabetes, cultural, self-management

The Impact of Family Medicine on Diabetic Eye Care, Screening Programs, Referral Patterns, and Outcomes

Diabetes mellitus is a long-lasting metabolic disease with a complex etiology. It is characterized by elevated blood sugar levels, which are marked by anomalies in insulin secretion, action, or both. Long-term hyperglycemia causes diverse microvascular and macrovascular diabetic complications, which are primarily responsible for the high morbidity and mortality associated with diabetes. Diabetes leads to significant ophthalmological complications among which diabetic retinopathy is thought to be the most frequent cause of blindness in people of working age, with diabetic macular oedema being the most frequent cause of impaired visual acuity among diabetics. The findings of several research studies suggest that the best way to prevent diabetic retinopathy from leading to blindness is through regular assessment and screening so any complications can be addressed as soon as possible. Furthermore, since early diabetic eye disease stages are asymptomatic, screening people with diabetes is essential. As a result, the primary care physician's involvement is essential for enabling an early diagnosis of this condition. Family physicians play an essential role in the early identification and prevention of diabetic retinopathy. They serve as the initial line of contact for managing diabetes and as referral sources when complications arise. The purpose of this research is to review the impact of family medicine on diabetic eye care, screening programs, referral patterns, and outcomes.

Availability of Evidence-Based Diabetes Programs in U.S. Children's Hospitals.

Diabetes affects Americans across the lifespan requiring individual and community-level interventions for prevention and management. Nonprofit hospitals are required to address community health needs under current tax law. The study objective was to assess what strategies children's hospitals implemented in prevention and care of diabetes and determine how many hospitals used evidence-based strategies. We identified the most recent Children's Hospital Needs Assessments and implementation strategies for each hospital. Data were thematically coded. Twenty-nine of the 233 U.S. children's hospitals addressed diabetes in their community benefit investments. Of the 130 hospital programs, 48 (37%) aligned with the DSMES framework. Programs focused on prevention (32%), healthy eating (18%), education (15%), physical activity (12%), quality improvement (11%), and self-management (5%). Most children's hospital interventions (85%) did not state a focus on reducing health disparities and none addressed problem solving or diabetes technology. Minimal hospitals are using evidence-based programming for diabetes management and are not targeting health disparities which undercuts their efforts. Hospitals are not adopting structural evidence-based approaches, missing key opportunities to implement strategies shown to reduce diabetes prevalence and lower A1c. This study suggests that children's hospitals need improvement in their diabetes programming to better serve their communities.

Evaluation of the surface temperature distribution in the feet of patients with type 2 diabetes using the thermovision method

IntroductionDiabetic foot syndrome (DFS) is one of the most common complications of diabetes. The purpose of the study was to evaluate the distribution of superficial temperature and microcirculation in the feet of patients with type 2 diabetes.Methods52 patients (the study group) with type 2 diabetes participated in the study, diagnosed by a physician while treated at “Centrum Medyczne” Provincial Specialist Healthcare Centre as part of the Diabetic Foot Syndrome Prevention Programme. The control group included 33 patients without diabetes. Superficial dorsal and plantar temperature of both feet was measured in all participants. The measurements were taken using a ThermoVision FLIR SYSTEM T335.ResultsIn both study groups, the temperature of the dorsal side of the foot was higher than the temperature of the plantar side. The observed difference in the control group was clearly larger than in the group of diabetic patients, and amounted to 1.7°C and 1.0°C. In the patients with diabetes the plantar temperature was higher by an average of 2.2°C, and the dorsal temperature was higher by an average of 1.5°C compared to the control group.ConclusionsThermal imaging can be used as a supplement to DFS diagnostics. Recommending daily self-monitoring of surface temperature with thermography for diabetic patients can help reduce the risk of neurotrophic changes in the foot.

Investigating the effects of digital foot self-management program on enhancing self-efficacy and self-care behavior among community-dwelling older adults with type 2 diabetes: A randomized controlled trial.

Diabetic foot self-management intervention programs have been proven to positively influence individuals' behaviors in preventing diabetic foot ulcers. Using digital technologies to deliver programs can facilitate compliance with diabetes self-management programs. However, few studies have focused on the effects of such digital programs on improving the self-efficacy and behaviors of older adults with type 2 diabetes in the community. To evaluate the effects of a digital foot self-management program on self-efficacy, self-care behavior, and Hemoglobin A1c levels. A single-blinded, randomized controlled trial was conducted. The intervention program comprised a 4-week digital foot care program with one face-to-face education session, phone calls once weekly, and LINE messages (social media) three times per research nurse and a follow-up of three months. Patients in the control group received routine care. A total of 100 participants (n = 50 in the control and n = 50 in the intervention groups) completed the study with a mean age of 67.55 (SD = 11.17). The results showed significant improvements in self-efficacy (F = 2187.24, p < 0.01) and self-care behavior (F = 614.71, p < 0.01) in foot care between the groups. The Hemoglobin A1c levels showed a 0.41% reduction over time in the experimental group (t = -3.759; p < 0.01), whereas the control group showed a 0.06% reduction (t = -0.797, p > 0.05). The newly developed digital foot self-management program was effective in community-dwelling older adult patients with type 2 diabetes.

Comparative evaluation of diabetic retinopathy screening programs in regular ophthalmology clinics versus integrated diabetic clinics within rural health-care services.

Robust integration of diabetic retinopathy (DR) screening within health systems is essential to prevent DR-related blindness. This, however, remains a challenge in the developing world. The aim of this study was to evaluate two models of DR screening programs within rural general health-care services. This was a retrospective observational study from two rural health centers. Demographic and clinical data of patients completing DR screening were analyzed. Patients were screened in regular ophthalmology clinics (ROC) or integrated diabetic clinics (IDC). Referral and treatment completion data were retrieved from the clinical charts at the base hospital. A total of 2535 DR screenings were conducted for 2296 patients. The total population prevalence for any DR was 14.2% (95% confidence interval [CI]: 12.8%-15.6%) and vision-threatening DR (VTDR) was 4.7% (95% CI: 3.8%-5.6%). In the ROC and IDC groups, respectively, the prevalence of any DR was 20.4% and 8.2%, VTDR, 7.8% and 1.7%, and blindness, 1.4% and 0.4% (all P < 0.001). Referral completion rates were higher in the ROC group (44.8% vs. 25.2%, P < 0.001), while treatment completion in both was similar (69.6% vs. 70.6%). Referral and treatment completion rates for referable DR were 61.2% and 48.2%, and for VTDR, 62% and 38.8%, respectively. Only 11.45% of patients completed the repeat screening follow-up. Patients attending IDCs had a significantly lower prevalence of any DR, VTDR, and blindness demonstrating the advantages of integrated diabetic care in a rural setting. However, referral uptake and DR treatment completion need strengthening.

Predicting Factors of Health-Related Quality of Life Among Adults With Type 2 Diabetes: A Systematic Review.

One of the most important outcomes of diabetes care and treatment is an improvement in patients' health-related quality of life (HRQoL). This study aimed to review the empirical evidence regarding the predictors of HRQoL among adults with type 2 diabetes mellitus (T2DM). To find all English-language articles published between 2012 and 2022, a comprehensive literature search was conducted using ProQuest, Scopus, PubMed, Science Direct, and CORE. Cross-sectional studies were the focus of this analysis. Search terms included "type 2 diabetes" OR "T2DM" AND "health-related quality of life" OR "HRQoL" AND ("predicting factors" OR "influencing factors" OR "associated factors"). The original search yielded a total of 1,089 studies, from which 35 met the review's inclusion criteria. The systematic review protocol was registered with PROSPERO CRD42023431229. The final analysis comprised 24,346 people with type 2 diabetes and used data from 35 cross-sectional studies conducted during the preceding decade. Socio-demographic factors (age, marital status, gender, monthly income, education, area of residence, and religiosity), patient-centered factors (diabetes knowledge and self-efficacy), disease characteristics (comorbidities, duration of diabetes, and insulin treatment), self-management behaviors (physical activity, medication adherence, and frequent glucose checks), and family support were found to be predictors of HRQoL. A diabetes program to enhance the HRQoL among people with T2DM is highly encouraged to address these factors, which can be focused on promoting self-management behaviors, diabetes distress management, and encourage family support.

Pharmacists' role in diabetes management for persons with lived experience of homelessness in Canada: A qualitative study.

Persons with lived experience of homelessness face many challenges in managing diabetes, including purchasing and storing medications, procuring healthy food and accessing healthcare services. Prior studies have found that pharmacy-led interventions for diabetes improved A1C, and lowered blood pressure and cholesterol in general populations. This study evaluated how select pharmacists in Canada have tailored their practices to serve persons with lived experiences of homelessness with diabetes. We conducted a qualitative descriptive study using open-ended interviews with inner-city pharmacists in select Canadian municipalities (Calgary, Edmonton, Vancouver, and Ottawa). We used NVivo qualitative data analysis software to facilitate thematic analysis of the data, focusing on how pharmacists contributed to diabetes care for persons with lived experience of homelessness. These pharmacists developed diabetes programs after discovering an unmet need in the population. Pharmacists have the unique ability to see patients frequently, allowing tailored education and hands-on assistance with diabetes management. These pharmacists provided extra-ordinary care like financial and housing resources and many of them were uniquely embedded within other services for persons with lived experience of homelessness (i.e. housing and social work supports). Pharmacists reported struggling with balancing optimal medical care for individuals with the financial constraints of running a business. Pharmacists are vital members of the diabetes care team for persons with lived experience of homelessness. Government policies should support and encourage unique models of care provided by pharmacists to improve diabetes management for this population.

Intermediate hyperglycaemia, diabetes and blood pressure in rural Bangladesh: five-year post-randomisation follow-up of the DMagic cluster-randomised controlled trial

The DMagic trial showed that participatory learning and action (PLA) community mobilisation delivered through facilitated community groups, and mHealth voice messaging interventions improved diabetes knowledge in Bangladesh and the PLA intervention reduced diabetes occurrence. We assess intervention effects three years after intervention activities stopped. Five years post-randomisation, we conducted a cross-sectional survey among a random sample of adults aged ≥30-years living in the 96 DMagic villages, and a cohort of individuals identified with intermediate hyperglycaemia at the start of the DMagic trial in 2016. Primary outcomes were: 1) the combined prevalence of intermediate hyperglycaemia and diabetes; 2) five-year cumulative incidence of diabetes among the 2016 cohort of individuals with intermediate hyperglycaemia. Secondary outcomes were: weight, BMI, waist and hip circumferences, blood pressure, knowledge and behaviours. Primary analysis compared outcomes at the cluster level between intervention arms relative to control. Data were gathered from 1623 (82%) of the randomly selected adults and 1817 (87%) of the intermediate hyperglycaemia cohort. 2018 improvements in diabetes knowledge in mHealth clusters were no longer observable in 2021. Knowledge remains significantly higher in PLA clusters relative to control but no difference in primary outcomes of intermediate hyperglycaemia and diabetes prevalence (OR (95%CI) 1.23 (0.89, 1.70)) or five-year incidence of diabetes were observed (1.04 (0.78, 1.40)). Hypertension (0.73 (0.54, 0.97)) and hypertension control (2.77 (1.34, 5.75)) were improved in PLA clusters relative to control. PLA intervention effect on intermediate hyperglycaemia and diabetes was not sustained at 3 years after intervention end, but benefits in terms of blood pressure reduction were observed. Medical Research Council UK: MR/M016501/1 (DMagic trial); MR/T023562/1 (DClare study), under the Global Alliance for Chronic Diseases (GACD) Diabetes and Scale-up Programmes, respectively.

Changes in Glycemic Control Following Use of a Spanish-Language, Culturally Adapted Diabetes Program: Retrospective Study

Several barriers to diabetes treatment and care exist, particularly in underserved medical communities. This study aimed to evaluate a novel, culturally adapted, Spanish-language mHealth diabetes program for glycemic control. Professional Spanish translators, linguists, and providers localized the entirety of the Vida Health Diabetes Management Program into a culturally relevant Spanish-language version. The Spanish-language Vida Health Diabetes Management Program was used by 182 (n=119 women) Spanish-speaking adults with diabetes. This app-based program provided access to culturally adapted educational content on diabetes self-management, one-on-one remote counseling and coaching sessions, and on-demand in-app messaging with bilingual (Spanish and English) certified health coaches, registered dietitian nutritionists, and certified diabetes care and education specialists. Hemoglobin A1c (HbA1c) was the primary outcome measure, and a 2-tailed, paired t test was used to evaluate changes in HbA1c before and after program use. To determine the relationship between program engagement and changes in glycemic control, a cluster-robust multiple regression analysis was employed. We observed a significant decrease in HbA1c of -1.23 points between baseline (mean 9.65%, SD 1.56%) and follow-up (mean 8.42%, SD 1.44%; P<.001). Additionally, we observed a greater decrease in HbA1c among participants with high program engagement (high engagement: -1.59%, SD 1.97%; low engagement: -0.84%, SD 1.64%; P<.001). This work highlights improvements in glycemic control that were clinically as well as statistically significant among Spanish-preferring adults enrolled in the Vida Health Spanish Diabetes Management Program. Greater improvements in glycemic control were observed among participants with higher program engagement. These results provide needed support for the use of digital health interventions to promote meaningful improvements in glycemic control in a medically underserved community.

Artificial intelligence for diabetic retinopathy screening

AbstractDiabetes constitutes a significant problem for global health and wellbeing. The number of people living with diabetes raised from 108 million in 1980 to 422 million in 2014. By 2035, 592 million people will have diabetes, with the largest rise in low‐ and middle‐income regions. Diabetic retinopathy (DR) is one of the major complications of diabetes, estimated to be the leading cause of blindness among working‐age adults globally. The increasing worldwide population, coupled with increasing prevalence of diabetes and increased incidence of diabetic retinopathy all lead to increasing number of patients with ocular complications of diabetes. Only a few countries were able to successfully establish and continue diabetic retinopathy screening on national level, most prominently – United Kingdom and Singapore. The NHS Diabetic Eye Screening Programme, a continuation of an English screening programme set up in 2006, reported in 2014 that DR is no longer the leading cause of certifiable blindness in England and Wales for the first time in 50 years. The advent of deep‐learning based DR detection revealed a significant improvement in the accuracy of the newly developed or improved systems. It requires a careful balance between sensitivity and specificity, imaging modality, gradeability of the images, all of which will need to be weighed against the potential cost. Deep learning DR detection has been found to be cost‐effective in developed countries, like Singapore and United Kingdom. However, the feasibility of implementing AI DR screening in countries without a robust teleophthalmology screening programme setup beforehand and other resource‐limited settings should still be evidenced. IDx‐DR is the first autonomous diagnostic software and one of the very first AI‐based software's in medicine to receive Federal Drug and Administration (FDA) approval. Eyeart was approved by FDA for the similar purpose in 2020. In European Union, there are more than 10 different AI‐based devices for DR screening registered, however in different classes, I and IIa. There are also significant shortcomings in current studies of AI in DR, including that great majority of them are sponsored or dependent on the respective algorithm's' company. Independent studies, particularly comparisons or studies establishing objective criteria through which the respective algorithms could be compared are rare.