Detection of structural lesions of the sacroiliac joints in patients with spondyloarthritis: A comparison of T1-weighted 3D spoiled gradient echo MRI and MRI-based synthetic CT versus T1-weighted turbo spin echo MRI.

OBJECTIVES: To investigate the detection of erosion, sclerosis and ankylosis using 1 mm 3D T1-weighted spoiled gradient echo (T1w-GRE) MRI and 1 mm MRI-based synthetic CT (sCT), compared with conventional 4 mm T1w-TSE. MATERIALS AND METHODS: Prospective, cross-sectional study. Semi-coronal 4 mm T1w-TSE and axial T1w-GRE with 1.6 mm slice thickness and 0.8 mm spacing between overlapping slices were performed. The T1w-GRE images were processed into sCT images using a commercial deep learning algorithm, BoneMRI. Both were reconstructed into 1 mm semi-coronal images. T1w-TSE, T1w-GRE and sCT images were assessed independently by 3 expert and 4 non-expert readers for erosion, sclerosis and ankylosis. Cohen's kappa for inter-reader agreement, exact McNemar test for lesion frequencies and Wilcoxon signed-rank test for confidence in lesion detection were used. RESULTS: Nineteen patients with axial spondyloarthritis were evaluated. T1w-GRE increased inter-reader agreement for detecting erosion (kappa 0.42 vs 0.21 in non-experts), increased detection of erosion (57 vs 43 of 152 joint quadrants) and sclerosis (26 vs 17 of 152 joint quadrants) among experts, and increased reader confidence for scoring erosion and sclerosis. sCT increased inter-reader agreement for detecting sclerosis (kappa 0.69 vs 0.37 in experts) and ankylosis (0.71 vs 0.52 in non-experts), increased detection of sclerosis (34 vs 17 of 152 joint quadrants) and ankylosis (20 vs 13 of 76 joint halves) among experts, and increased reader confidence for scoring erosion, sclerosis and ankylosis. CONCLUSION: T1w-GRE and sCT increase sensitivity and reader confidence for the detection of erosion, sclerosis and ankylosis, compared with T1w-TSE. CLINICAL RELEVANCE STATEMENT: These methods improve the detection of sacroiliac joint structural lesions and might be a useful addition to SIJ MRI protocols both in routine clinical care and as structural outcome measures in clinical trials.

Adherence to newer second-line oral antidiabetic drugs among people with type 2 diabetes-A systematic review.

The adherence to oral antidiabetic drugs (OADs) among people with type 2 diabetes (T2D) is suboptimal. However, new OADs have been marketed within the last 10 years. As these new drugs differ in mechanism of action, treatment complexity, and side effects, they may influence adherence. Thus, the aim of this study was to assess the adherence to newer second-line OADs, defined as drugs marketed in 2012-2022, among people with T2D. A systematic review was performed in CINAHL, Cochrane Trials, Embase, PubMed, PsycINFO, and Scopus. Articles were included if they were original research of adherence to newer second-line OADs and reported objective adherence quantification. The quality of the articles was assessed using JBI's critical appraisal tools. The overall findings were reported according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and summarized in a narrative synthesis. All seven included articles were European retrospective cohort studies investigating alogliptin, canagliflozin, dapagliflozin, empagliflozin, and unspecified types of SGLT2i. Treatment discontinuation and medication possession ratio (MPR) were the most frequently reported adherence quantification measures. Within the first 12 months of treatment, 29%-44% of subjects on SGLT2i discontinued the treatment. In terms of MPR, 61.7%-94.9% of subjects on either alogliptin, canagliflozin, dapagliflozin, empagliflozin or an unspecified SGLT2i were adherent. The two investigated adherence quantification measures, treatment discontinuation and MPR, suggest that adherence to the newer second-line OADs may be better than that of older OADs. However, a study directly comparing older and newer OADs should be done to verify this.

The Effectiveness of Digital Health Lifestyle Interventions on People With Prediabetes: Protocol for a Systematic Review, Meta-Analysis, and Meta-Regression.

BACKGROUND: There has been an increasing interest in the use of digital health lifestyle interventions for people with prediabetes, as these interventions may offer a scalable approach to preventing type 2 diabetes. Previous systematic reviews on digital health lifestyle interventions for people with prediabetes had limitations, such as a narrow focus on certain types of interventions, a lack of statistical pooling, and no broader subgroup analysis of intervention characteristics. The identified limitations observed in previous systematic reviews substantiate the necessity of conducting a comprehensive review to address these gaps within the field. This will enable a comprehensive understanding of the effectiveness of digital health lifestyle interventions for people with prediabetes. OBJECTIVE: The objective of this systematic review, meta-analysis, and meta-regression is to systematically investigate the effectiveness of digital health lifestyle interventions on prediabetes-related outcomes in comparison with any comparator without a digital component among adults with prediabetes. METHODS: This systematic review will include randomized controlled trials that investigate the effectiveness of digital health lifestyle interventions on adults (aged 18 years or older) with prediabetes and compare the digital interventions with nondigital interventions. The primary outcome will be change in body weight (kg). Secondary outcomes include, among others, change in glycemic status, markers of cardiometabolic health, feasibility outcomes, and incidence of type 2 diabetes. Embase, PubMed, CINAHL, and CENTRAL (Cochrane Central Register of Controlled Trials) will be systematically searched. The data items to be extracted include study characteristics, participant characteristics, intervention characteristics, and relevant outcomes. To estimate the overall effect size, a meta-analysis will be conducted using the mean difference. Additionally, if feasible, meta-regression on study, intervention, and participant characteristics will be performed. The Cochrane risk of bias tool will be applied to assess study quality, and the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach will be used to assess the certainty of evidence. RESULTS: The results are projected to yield an overall estimate of the effectiveness of digital health lifestyle interventions on adults with prediabetes and elucidate the characteristics that contribute to their effectiveness. CONCLUSIONS: The insights gained from this study may help clarify the potential of digital health lifestyle interventions for people with prediabetes and guide the decision-making regarding future intervention components. TRIAL REGISTRATION: PROSPERO CRD42023426919; http://tinyurl.com/d3enrw9j. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50340.

Diabetes Management Support in Preschool and Primary School: A Qualitative Ideation Study Presenting Recommendations for Improved Communicative Practice.

Diabetes care in institutional settings is a significant challenge that affects the whole family as well as care workers and teachers. The present study is the ideation part of a rigorous development process in the KIds with Diabetes in School (KIDS) project. We have previously conducted a thorough three-part needs assessment in which we explored the problem area from the viewpoints of (1) municipal administrative staff, (2) preschool and school staff and (3) families. Based on the identified needs and to a great extent on the contents and shortcomings of existing guidelines, the objective of the present study is to explore and develop possible solutions and recommendations for addressing the challenges and problems. To meet this objective, we held comprehensive multistakeholder participatory workshops in each of the five Danish regions. Five main themes with multiple subthemes were identified as areas to be addressed: (1) training and knowledge, (2) communication and collaboration, (3) the designated contact/support person, (4) national guidelines, and (5) the Diabetes Coordinator. Our findings demonstrate that communicative structures and dynamics are at the very heart of the identified problems and challenges and that the possible solutions should revolve around improving existing structures and highlighting the importance of constantly working on understanding and developing communication strategies. We propose a set of recommendations for practice based on these communicative needs.

A Three-Step Data-Driven Methodology to Assess Adherence to Basal Insulin Therapy in Patients With Insulin-Treated Type 2 Diabetes.

BACKGROUND: While health care providers (HCPs) are generally aware of the challenges concerning insulin adherence in adults with insulin-treated type 2 diabetes (T2D), data guiding identification of insulin nonadherence and understanding of injection patterns have been limited. Hence, the aim of this study was to examine detailed injection data and provide methods for assessing different aspects of basal insulin adherence. METHOD: Basal insulin data recorded by a connected insulin pen and prescribed doses were collected from 103 insulin-treated patients (aged ≥18 years) with T2D from an ongoing clinical trial (NCT04981808). We categorized the data and analyzed distributions of correct doses, increased doses, reduced doses, and missed doses to quantify adherence. We developed a three-step model evaluating three aspects of adherence (overall adherence, adherence distribution, and dose deviation) offering HCPs a comprehensive assessment approach. RESULTS: We used data from a connected insulin pen to exemplify the use of the three-step model to evaluate overall, adherence, adherence distribution, and dose deviation using patient cases. CONCLUSION: The methodology provides HCPs with detailed access to previously limited clinical data on insulin administration, making it possible to identify specific nonadherence behavior which will guide patient-HCP discussions and potentially provide valuable insights for tailoring the most appropriate forms of support.

Quantification of insulin adherence in adults with insulin-treated type 2 diabetes: A systematic review.

AIMS: This systematic review aims to identify current methods used for the assessment of insulin adherence in adults with insulin-treated type 2 diabetes. The primary goal is to offer recommendations for clinical practice to improve quantification of adherence. METHODS: The review was conducted in accordance with PRISMA 2020 and registered at PROSPERO (CRD42022334134). PubMed, Embase, CINAHL, and PsycINFO were searched on 15 November 2022 and included three blocks: Type 2 diabetes, insulin, and adherence. We considered primary full-text studies describing an assessment method and a threshold for assessment of insulin adherence in adults with insulin-treated type 2 diabetes. RESULTS: A final sample of 50 studies were included. Identified methods fell into four categories: self-report, pharmacy claims, inulin count, and data from an insulin pen device. Commonly reported methods included: The Morisky Medication Adherence Scale, the (adjusted) Medication Possession Ratio, and the Proportions of Days Covered. A threshold of <80% was used to define non-adherence in nearly half of the studies. Yet, several thresholds were reported. CONCLUSIONS: Most available methods for assessing insulin adherence in adults with insulin-treated type 2 diabetes are severely limited in providing in-depth insights into timing, dosing size, injection patterns, and adherence behavior. However, recognizing diverse types of non-adherence is crucial, as they denote unique behavioral entities requiring targeted intervention. Employing insulin injection data (e.g., from a smart insulin pen cap) to underlie an assessment method is a potential new approach to objectively assess insulin timing and dosing adherence in adults with insulin-treated type 2 diabetes.

A Study on Optimization and Evaluation of the Visualization of Complex Algorithm Results in Remote Monitoring of COPD.

BACKGROUND: Artificial intelligence (AI) can potentially increase the quality of telemonitoring in chronic obstructive pulmonary disease (COPD). However, the output from AI is often difficult for clinicians to understand due to the complexity. This challenge may be accommodated by visualizing the AI results, however it hasn't been studied how this could be done specifically, i.e., considering which visual elements to include. AIM: To investigate how complex results from a predictive algorithm for patients with COPD can be translated into easily understandable data for the clinicians. METHODS: Semi-structured interviews were conducted to explore clinicians' needs when visualizing the results of a predictive algorithm. This formed a basis for creating a prototype of an updated user interface. The user interface was evaluated using usability tests through the "Think aloud" method. RESULTS: The clinicians pointed out the need for visualization of exacerbation alerts and the development in patients' data. Furthermore, they wanted the system to provide more information about what caused exacerbation alerts. Elements such as color and icons were described as particularly useful. The usability of the prototype was primarily assessed as easily understandable and advantageous in connection to the functions of the predictive algorithm. CONCLUSION: Predictive algorithm use in telemonitoring of COPD can be optimized by clearly visualizing the algorithm's alerts, clarifying the reasons for algorithm output, and by providing a clear overview of the development in the patient's data. This can contribute to clarity when the clinicians should act and why they should act on alerts from predictive algorithms.

Personalized Prediction of Change in Fasting Blood Glucose Following Basal Insulin Adjustment in People With Type 2 Diabetes: A Proof-of-Concept Study.

AIMS: For people with type 2 diabetes treated with basal insulin, suboptimal glycemic control due to clinical inertia is a common issue. Determining the optimal basal insulin dose can be difficult, as it varies between individuals. Thus, insulin titration can be slow and cautious which may lead to treatment fatigue and non-adherence. A model that predicts changes in fasting blood glucose (FBG) after adjusting basal insulin dose may lead to more optimal titration, reducing some of these challenges. OBJECTIVE: To predict the change in FBG following adjustment of basal insulin in people with type 2 diabetes using a machine learning framework. METHODS: A multiple linear regression model was developed based on 786 adults with type 2 diabetes. Data were divided into training (80%) and testing (20%) sets using a ranking approach. Forward feature selection and fivefold cross-validation were used to select features. RESULTS: Participants had a mean age of approximately 59 years, a mean duration of diabetes of 12 years, and a mean HbA1c at screening of 65 mmol/mol (8.1%). Chosen features were FBG at week 2, basal insulin dose adjustment from week 2 to 7, trial site, hemoglobin level, and alkaline phosphatase level. The model achieved a relative absolute error of 0.67, a Pearson correlation coefficient of 0.74, and a coefficient of determination of 0.55. CONCLUSIONS: A model using FBG, insulin doses, and blood samples can predict a five-week change in FBG after adjusting the basal insulin dose in people with type 2 diabetes. Implementation of such a model can potentially help optimize titration and improve glycemic control.

Factors associated with adherence or nonadherence to insulin therapy among adults with type 2 diabetes mellitus: A scoping review.

BACKGROUND AND AIM: One of the greatest barriers to the treatment of T2DM is nonadherence which particularly applies to insulin therapy. There is a need for a comprehensive overview of all factors associated with nonadherence to insulin therapy. The aim of this study was to identify factors associated with adherence or nonadherence to insulin therapy among adults with T2DM. METHODS: A scoping review was conducted in accordance with the PRISMA 2020 statement. A systematic search was performed in PubMed, Cinahl, and Web of Science (January 2013 to March 2023). RESULTS: A final sample of 48 studies was included in the scoping review. The synthesis revealed 30 factors associated with adherence or nonadherence. The factors were grouped into 6 themes: demographics, attitude and perceptions, management of diabetes, impact on daily living, disease and medication, and healthcare system. CONCLUSION: The most prominent factors identified were age, cost of healthcare, personal beliefs towards insulin therapy, social stigma, patient education, complexity of diabetes treatment, impact of insulin therapy on daily life, and fear of side effects. The results indicate a need for further research to determine threshold values for the factors associated with adherence or nonadherence.

The multidisciplinary team in diagnosing and treatment of patients with diabetes and comorbidities: A scoping review.

Background: Multidisciplinary Teams (MDTs) has been suggested as an intervention to overcome some of the complexities experienced by people with diabetes and comorbidities in terms of diagnosis and treatment. However, evidence concerning MDTs within the diabetes field remains sparse. Objective: This review aims to identify and map available evidence on key characteristics of MDTs in the context of diagnosis and treatment in people with diabetes and comorbidities. Methods: This review followed the PRISMA-ScR guidelines. Databases PubMed, EMBASE, and CINAHL were systematically searched for studies assessing any type of MDT within the context of diagnosis and treatment in adult people (≥ 18 years) with diabetes and comorbidities/complications. Data extraction included details on study characteristics, MDT interventions, digital health solutions, and key findings. Results: Overall, 19 studies were included. Generally, the MDTs were characterized by high heterogeneity. Four overall components characterized the MDTs: Both medical specialists and healthcare professionals (HCPs) of different team sizes were represented; interventions spanned elements of medication, assessment, nutrition, education, self-monitoring, and treatment adjustment; digital health solutions were integrated in 58% of the studies; MDTs were carried out in both primary and secondary healthcare settings with varying frequencies. Generally, the effectiveness of the MDTs was positive across different outcomes. Conclusions: MDTs are characterized by high diversity in their outline yet seem to be effective and cost-effective in the context of diagnosis and treatment of people with diabetes and comorbidities. Future research should investigate the cross-sectorial collaboration to reduce care fragmentation and enhance care coordination.

Management of Diabetes during School Hours: A Cross-Sectional Questionnaire Study in Denmark.

Managing diabetes is complicated for many children. It often requires support from an adult during the school day. In Denmark, most children spend 30-35 h a week at school. Nevertheless, diabetes management in schools remains largely uninvestigated. This study aimed to examine the characteristics and organization of diabetes management in Danish primary schools from the personnel's perspective. All primary schools in Denmark were invited to participate in the study (n = 2129), and 525 schools were included. A questionnaire was constructed and sent by email. Questionnaire data are presented in the descriptive statistics and compared with the ISPAD guidelines. According to 77.2% of respondents, school personnel had received training in diabetes management, and 78.5% of the schools had at least one person available for diabetes support every day. Respondents felt prepared to help the students with counting carbohydrates (38.9%), dosing insulin (39.1%), and helping the students during high (52.1%) or low (60.3%) blood sugar levels, insulin chock (35.2%), or during activities (36.3%). Yet, diabetes management was a challenging task. Only 61.7% had an action plan for diabetes management, 37.4% had face-to-face information meetings with the parents, and 55.1% of respondents reported having sufficient time to cooperate with the parents.

The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression.

BACKGROUND: Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes. However, such reviews often have a narrow focus, which calls for a more comprehensive systematic review within the field. Hence, the objective of the present systematic review, meta-analysis, and meta-regression is to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with type 2 diabetes (T2D). METHODS: This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We considered telemedicine randomized controlled trials (RCT) including adults (≥18 years) diagnosed with T2D. Change in glycated hemoglobin (HbA1c, %) was the primary outcome. PubMed, EMBASE, and the Cochrane Library Central Register of Controlled Trials (CENTRAL) were searched on October 14, 2020. An overall treatment effect was estimated using a meta-analysis performed on the pool of included studies based on the mean difference (MD). The revised Cochrane risk-of-bias tool was applied and the certainty of evidence was graded using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. RESULTS: The final sample of papers included a total of 246, of which 168 had sufficient information to calculate the effect of HbA1c%. The results favored telemedicine, with an MD of -0.415% (95% confidence interval [CI] = -0.482% to -0.348%). The heterogeneity was great (I2 = 93.05%). A monitoring component gave rise to the higher effects of telemedicine. CONCLUSIONS: In conclusion, telemedicine may serve as a valuable supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine.

The Effectiveness of Telemedicine Solutions in Type 1 Diabetes Management: A Systematic Review and Meta-analysis.

BACKGROUND: Telemedicine holds a potential to strengthen self-management support outside health care settings in the everyday management of type 1 diabetes (T1D). However, existing effectiveness reviews are older or include a relatively narrow focus on specific definitions of telemedicine or included databases. OBJECTIVE: To conduct a systematic review of the effectiveness of telemedicine solutions versus any comparator on diabetes-related outcomes among people with T1D. METHODS: Studies including adults (≥18 years) with T1D published before October 14, 2020, were eligible. Primary outcome was glycated hemoglobin (HbA1c, %). The Cochrane Library, PubMed, EMBASE, and CINAHL were searched. Meta-analysis based on the mean difference in HbA1c% was used to pool effects. The Cochrane tool was applied to assess risk-of-bias, and the certainty of evidence was graded using the GRADE approach. RESULTS: A total of 22 studies were included (with 1615 participants). Treatment effect for HbA1c% favored telemedicine (mean difference of -0.26% [95% confidence interval:-0.37% to -0.15%]) with moderate effect certainty. Heterogeneity was moderate (I2 = 33.30%). Although not significant, secondary outcomes were all in favor of telemedicine except number of severe hypoglycemic events and diabetes knowledge, but the certainty of the evidence for those outcomes was all low or very low. DISCUSSION: Reducing average HbA1c% levels are important to combat the risk of diabetic complications and premature death. However, the evidence mostly consist of small studies with a relative short duration and the estimated pooled effect is smaller than could be expected from quality improvement strategies in general for diabetes management. PROSPERO NUMBER: CRD42020123565.

Effectiveness of Telemedicine in Managing Diabetes in Pregnancy: A Systematic Review and Meta-Analysis.

BACKGROUND: Strict monitoring of blood glucose during pregnancy is essential for ensuring optimal maternal and neonatal outcomes. Telemedicine could be a promising solution for supporting diabetes management; however, an updated meta-analysis is warranted. This study assesses the effects of telemedicine solutions for managing gestational and pregestational diabetes. METHODS: PubMed, EMBASE, Cochrane Library Central Register of Controlled Trials, and CINAHL were searched up to October 14, 2020. All randomized trials assessing the effects of telemedicine in managing diabetes in pregnancy relative to any comparator without the use of telemedicine were included. The primary outcome was infant birth weight. A meta-analysis comparing the mean difference (MD) in birth weight across studies was applied, and subgroup and sensitivity analyses were performed. The revised Cochrane tool was applied to assess the risk of bias, and the certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. RESULTS: From a total of 18 studies, ten (totaling 899 participants) were used to calculate the effect on infant birth weight. The results nonsignificantly favored the control (MD of 19.34 g; [95% confidence interval, CI -47.8; 86.47]), with moderate effect certainty. Heterogeneity was moderate (I2 = 37.39%). Statistically significant secondary outcomes included differences in two-hour glucose tolerance postpartum (gestational diabetes; two studies: standardized mean difference 9.62 mg/dL [95% CI: 1.95; 17.28]) that favored the control (GRADE level, very low) and risk of shoulder dystocia (four studies: log odds -1.34 [95% CI: -2.61; -0.08]) that favored telemedicine (GRADE, low). CONCLUSIONS: No evidence was found to support telemedicine as an alternative to usual care when considering maternal and fetal outcomes. However, further research is needed, including economic evaluations.

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical practice leading to suboptimal treatment. Thus, 60% of people with T2D treated with insulin do not reach glycemic targets. This emphasizes a need for methods supporting efficient and individualized basal insulin titration of people with T2D. However, no systematic review of basal insulin dose guidance for people with T2D has been found. OBJECTIVE: To provide an overview of basal insulin dose guidance methods that support titration of people with T2D and categorize these methods by characteristics, effect, and user experience. METHODS: The review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Studies about basal insulin dose guidance, including adults with T2D on basal insulin analogs published before September 7, 2022, were included. Joanna Briggs Institute critical appraisal checklists were applied to assess risk of bias. RESULTS: In total, 35 studies were included, and three categories of dose guidance were identified: paper-based titration algorithms, telehealth solutions, and mathematical models. Heterogeneous reporting of glycemic outcomes challenged comparison of effect between the three categories. Few studies assessed user experience. CONCLUSIONS: Studies mainly used titration algorithms to titrate basal insulin as telehealth or in paper format, except for studies using mathematical models. A numerically larger proportion of participants seemed to reach target using telehealth solutions compared to paper-based titration algorithms. Exploring capabilities of machine learning may provide insights that could pioneer future research while focusing on holistic development.

Bedtime Prediction of Nocturnal Hypoglycemia in Insulin-Treated Type 2 Diabetes Patients.

BACKGROUND AND AIMS: Hypoglycemia may lead to anxiety, poor adherence, and hypoglycemia unawareness and is especially a threat during the night in patients with insulin-treated type 2 diabetes (T2D). It would therefore be beneficial to warn patients at risk of hypoglycemia at bedtime so they can react accordingly and avoid the episode. Hence, the aim of the present study was to develop a model for predicting nocturnal hypoglycemia. METHODS: Continuous glucose monitoring (CGM), mealtime, and insulin data were collected from 67 insulin-treated patients with T2D (NCT01819129). Data were structured into 24-hour periods and labeled as nocturnal hypoglycemia or not depending on whether 15 consecutive minutes were spent below 3.0 mmol/L (54 mg/dL) during the following night. Each period was divided into "last night," "morning," "day," and "evening" for feature extraction purposes, and 72 potential features were extracted for every period. A five-fold cross-validation was used to select features by forward selection and for training and validating a model based on logistic regression. RESULTS: The prediction model was based on 30 patients with 60/496 periods resulting in nocturnal hypoglycemia. Forward selection revealed that the best features were based on CGM and involved the last value and mean value during the evening, as well as the relative difference in maximum value during the day between the present period and previous periods. The model obtained a mean area under the receiver operating characteristics curve (AUC) of 0.82 with an accuracy of 0.79. CONCLUSIONS: The model was able to predict nocturnal hypoglycemia with an acceptable accuracy and could therefore prevent such cases.

The Diabetes teleMonitoring of patients in insulin Therapy (DiaMonT) trial: study protocol for a randomized controlled trial.

BACKGROUND: The effect of telemedicine solutions in diabetes remains inconclusive. However, telemedicine studies have shown a positive trend in regards to glycemic control. The telemedicine interventions that facilitate adjustment of medication seems to improve glycemic control more effectively. Hence, it is recommended that future telemedicine studies for patients with diabetes include patient-specific suggestions for changes in medicine. Hence, the aim of the trial is to explore the effect of telemonitoring in patients with type 2 diabetes (T2D) on insulin therapy. METHODS: The trial is an open-label randomized controlled trial with a trial period of 3 months conducted in two sites in Denmark. Patients with T2D on insulin therapy will be randomized (1:1) to a telemonitoring group (intervention) or a usual care group (control). The telemonitoring group will use a continuous glucose monitor (CGM), an insulin pen, an activity tracker, and smartphone applications throughout the trial. Hospital staff will monitor the telemonitoring group and contact the subjects by telephone repeatedly throughout the trial period. The usual care group will use a blinded CGM the first and last 20 days of the trial and will use a blinded insulin pen for the entire period. The primary endpoint will be changed from baseline in CGM time in range (3.9-10.0 mmol/L) 3 months after randomization. Secondary endpoints include change from baseline in glycated hemoglobin (HbA1c), total daily dose, time above range, and time below range 3 months after randomization. Exploratory endpoints include health-related quality of life, diabetes-related quality of life, etc. DISCUSSION: The DiaMonT trial will test a telemonitoring setup including various devices. Such a setup may be criticized, because it is impossible to determine which element(s) add to the potential effect. However, it is not possible and counterproductive to test the elements individually, since it is the full telemedicine setup that is being evaluated. The DiaMonT trial is the first Danish trial to explore the effect of telemonitoring on patients on insulin therapy. Thus, the DiaMonT trial has the potential to form the basis for the implementation of telemedicine for patients with T2D in Denmark. TRIAL REGISTRATION: ClinicalTrials.gov NCT04981808. Registered on 8 June 2021.

Municipal Support of Diabetes Management in Daycare, Kindergarten and School: A Qualitative Study of Differences, Challenges and Potentials.

Diabetes care during institutional hours is a major challenge affecting the whole family. The aim of this study was to highlight challenges and potentials regarding municipal support in relation to diabetes care of children in school, kindergarten, and daycare. The dataset consists of 80 semi-structured online interviews with 121 municipal employees from 74 (of 98) municipalities in Denmark. Data were analysed using qualitative content analysis. The analysis produced four main themes: (1) Institutional staff initially feel insecure about diabetes care responsibilities, (2) There is a high degree of parental involvement and responsibilities during institutional hours, (3) The roles of health employees vary, and (4) Fluctuating allocation of special needs assistants (SNAs) creates challenges. The findings of this nationwide qualitative study show that, even though Denmark guarantees, by law, the child's right to support in diabetes self-care in school and childcare institutions, diabetes management in Denmark still needs to be improved, with a view to ensuring equal support for all children with diabetes.

Clinical implementation of an algorithm for predicting exacerbations in patients with COPD in telemonitoring: a study protocol for a single-blinded randomized controlled trial.

BACKGROUND: Acute exacerbations have a significant impact on patients with COPD by accelerating the decline in lung function leading to decreased health-related quality of life and survival time. In telehealth, health care professionals exercise clinical judgment over a physical distance. Telehealth has been implemented as a way to monitor patients more closely in daily life with an intention to intervene earlier when physical measurements indicate that health deteriorates. Several studies call for research investigating the ability of telehealth to automatically flag risk of exacerbations by applying the physical measurements that are collected as part of the monitoring routines to support health care professionals. However, more research is needed to further develop, test, and validate prediction algorithms to ensure that these algorithms improve outcomes before they are widely implemented in practice. METHOD: This trial tests a COPD prediction algorithm that is integrated into an existing telehealth system, which has been developed from the previous Danish large-scale trial, TeleCare North (NCT: 01984840). The COPD prediction algorithm aims to support clinical decisions by predicting the risk of exacerbations for patients with COPD based on selected physiological parameters. A prospective, parallel two-armed randomized controlled trial with approximately 200 participants with COPD will be conducted. The participants live in Aalborg municipality, which is located in the North Denmark Region. All participants are familiar with the telehealth system in advance. In addition to the participants' usual weekly monitored measurements, they are asked to measure their oxygen saturation two more times a week during the trial period. The primary outcome is the number of exacerbations defined as an acute hospitalization from baseline to follow-up. Secondary outcomes include changes in health-related quality of life measured by both the 12-Item Short Form Survey version 2 and EuroQol-5 Dimension Questionnaire as well as the incremental cost-effectiveness ratio. DISCUSSION: This trial seeks to explore whether the COPD prediction algorithm has the potential to support early detection of exacerbations in a telehealth setting. The COPD prediction algorithm may initiate timely treatment, which may decrease the number of hospitalizations. TRIAL REGISTRATION: NCT05218525 (pending at clinicaltrials.gov ) (date, month, year).

Using Distance Communication for the User-Centered Development of a Smartphone-Based Serious Game for Children With Type 1 Diabetes: Participatory Design Approach.

BACKGROUND: The complications of type 1 diabetes (T1D) can be delayed or prevented in children with T1D who receive proper self-management education. Smartphone-based serious games are increasingly being used as an effective tool for teaching self-management. When developing a serious game, it is important that the development process be user-centered. Traditionally, different face-to-face methods have been used when children participate in the development process. However, face-to-face data collection is not always feasible. In such situations, distance communication can be used when developing a serious game. OBJECTIVE: The objective of this study is to develop a user-centered smartphone-based serious game that teaches self-management focused on carbohydrate intake in children aged 8-14 years with T1D using distance communication in both the development and evaluation of the game. METHODS: The development and evaluation of a smartphone-based serious game prototype was inspired by the Lean principles, and a user-centered approach was applied. The development process included 1 expert interview and design workshops with children with T1D. On the basis of the interview and design workshop results, a serious game prototype was developed using Microsoft PowerPoint. The evaluation of the serious game prototype included an interview with a dietitian and a playtest with children with T1D. All data were collected using distance communication. RESULTS: A user-centered smartphone-based serious game prototype was developed and evaluated. The expert interview with the dietitian formed the basis for the learning outcomes in the game. Four children and their parents contributed to the preferences, needs, requirements, and ideas for selected parts of the game design. The dietitian evaluated the prototype positively and validated its content and accuracy. The serious game prototype was well-received by the children and their parents during the playtest. The serious game prototype was perceived as a useful and engaging way to learn. However, the difficulty level was not appropriate, and the information was too basic for participants who had been diagnosed over a year ago. The use of digital communication platforms did not cause any problems. CONCLUSIONS: The smartphone-based serious game prototype has the potential to be a useful and attractive tool for teaching disease self-management. The use of distance communication proved to be a useful approach in the development of a serious game.