Journal of Diabetes Science and Technology最新文献

{"title":"Expert Clinical Interpretation of Continuous Glucose Monitor Reports From Individuals Without Diabetes.","authors":"Nicole L Spartano, Brenton Prescott, Maura E Walker, Eleanor Shi, Guhan Venkatesan, David Fei, Honghuang Lin, Joanne M Murabito, David Ahn, Tadej Battelino, Steven V Edelman, G Alexander Fleming, Guido Freckmann, Rodolfo J Galindo, Michael Joubert, M Cecilia Lansang, Julia K Mader, Boris Mankovsky, Nestoras N Mathioudakis, Viswanathan Mohan, Anne L Peters, Viral N Shah, Elias K Spanakis, Kayo Waki, Eugene E Wright, Mihail Zilbermint, Howard A Wolpert, Devin W Steenkamp","doi":"10.1177/19322968251315171","DOIUrl":"10.1177/19322968251315171","url":null,"abstract":"<p><strong>Background: </strong>Clinical interpretation of continuous glucose monitoring (CGM) data for people without diabetes has not been well established. This study aimed to investigate concordance among CGM experts in recommending clinical follow-up for individuals without diabetes, based upon their independent review of CGM data.</p><p><strong>Methods: </strong>We sent a survey out to expert clinicians (<i>n</i> = 18) and asked them to evaluate 20 potentially challenging Dexcom G6 Pro CGM reports (and hemoglobin A1c [HbA1c] and fasting venous blood glucose levels) from individuals without diabetes. Clinicians reported whether they would recommend follow-up and the reasoning for their decision. We performed Fleiss Kappa interrater reliability to determine agreement among clinicians.</p><p><strong>Results: </strong>More than half of expert clinicians (56-100%, but no clear consensus) recommended follow-up to individuals who spent >2% time above range (>180 mg/dL), even if HbA1c <5.7% and fasting glucose <100 mg/dL. There were no observed trends for recommending follow-up based on mean glucose or glucose management indicator. Overall, we observed poor agreement in recommendations for who should receive follow-up based on their CGM report (Fleiss Kappa = 0.36).</p><p><strong>Conclusions: </strong>High discordance among expert clinicians when interpreting potentially challenging CGM reports for people without diabetes highlights the need for more research in developing normative data for people without diabetes. Future work is required to develop CGM criteria for identifying potentially high-risk individuals who may progress to prediabetes or type 2 diabetes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251315171"},"PeriodicalIF":4.1,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11822776/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143399419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Utility of Smart Multiple Daily Injection Systems in Intensive Insulin-Treated People With Diabetes: An Italian Expert Consensus.","authors":"Francesco Giorgino, Riccardo Bonfanti, Filomena Castaldo, Concetta Irace, Andrea Laurenzi, Claudio Maffeis, Giovanni Pappagallo, Dario Pitocco, Ivana Rabbone, Emanuela Zarra, Andrea Enzo Scaramuzza","doi":"10.1177/19322968251316577","DOIUrl":"10.1177/19322968251316577","url":null,"abstract":"<p><strong>Background: </strong>Smart systems for multiple daily injections (Smart MDI) integrate continuous glucose monitoring, connected insulin pens, smartphone apps, and cloud-based data storage to provide bolus and corrective dose suggestions, reminders/alerts, automatic tracking and sharing of insulin therapy, and glycemic data to users, caregivers, and providers. This is an expert consensus on the clinical value of Smart MDI and critical points for implementation in adults and children/adolescents with diabetes.</p><p><strong>Methods: </strong>A nominal group technique combined with the estimate-talk-estimate approach was employed to achieve consensus among panel members from the Italian Intersociety Technology and Diabetes Study Group with expertise in pediatric and adult diabetes care.</p><p><strong>Results: </strong>The expert consensus indicated that glycemic profiles can be improved by using bolus dose suggestions based on glucose values, planned meals, the insulin-to-carbohydrate ratio, correction factors, and consideration of insulin-on-board. Automatic remote sharing of patient data on glycemia and insulin therapy allows clinicians to make more appropriate and timely therapeutic recommendations based on objective data. Dose tracking, bolus reminders/alerts, and reduced hypoglycemia and associated anxiety achieved through Smart MDI may improve adherence.</p><p><strong>Conclusions: </strong>Smart MDI can reduce treatment burden while improving the daily experiences and glycemic outcomes for adults and children/adolescents with type 1 or type 2 diabetes. However, high-quality clinical data are lacking, and more evidence is needed to compare the effects of Smart MDI and other advanced insulin delivery systems on glycemic and patient-reported outcomes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251316577"},"PeriodicalIF":4.1,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11811948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143382575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Performance-Based Adaptation Index for Automated Insulin Delivery Systems.","authors":"Jenny L Diaz C, Patricio Colmegna, Elliot Pryor, Marc D Breton","doi":"10.1177/19322968251315499","DOIUrl":"10.1177/19322968251315499","url":null,"abstract":"<p><strong>Background: </strong>Automated insulin delivery (AID) algorithms can benefit from tuning of their aggressiveness to meet individual needs, as insulin requirements vary among and within users. We introduce the Performance-Based Adaptation Index (PAI), a tool designed to enable automatic adjustment of an AID system aggressiveness based on continuous glucose monitoring (CGM) metrics.</p><p><strong>Methods: </strong>PAI integrates two CGM-based metrics-one for hypoglycemia and another for hyperglycemia exposure-over a previous time window into a single index (<math><mrow><msub><mi>α</mi><mi>θ</mi></msub></mrow></math>). We propose two methods to compute <math><mrow><msub><mi>α</mi><mi>θ</mi></msub></mrow></math>: one based on time in range (TIR, 70-180 mg/dL), and the other on glycemic risk indices. Using <math><mrow><msub><mi>α</mi><mi>θ</mi></msub></mrow></math>, we developed a multiplicative strategy to adjust the AID system's aggressiveness, accounting for situations where <math><mrow><msub><mi>α</mi><mi>θ</mi></msub></mrow></math> cannot be reliably calculated. The feasibility of this method was assessed in-silico using the UVA/Padova Type 1 Diabetes Simulator and our full closed-loop algorithm (UVA-model predictive control (MPC)) across five scenarios: optimal tuning (baseline), conservative and aggressive tunings, and temporary and permanent changes in insulin needs. Glycemic outcomes were evaluated from the simulated glucose traces.</p><p><strong>Results: </strong>Negligible performance variations were observed in the baseline scenario. For the conservative scenario, adjusting <math><mrow><msub><mi>α</mi><mi>θ</mi></msub></mrow></math> improved TIR (35.1% vs 71.8%) and increased total daily insulin (32.1 U vs 41.2 U). Conversely, for the aggressive scenario, it reduced hypoglycemia exposure (TBR: 2.6% vs 1.4%) and overall insulin usage (45.6 U vs 43.0 U).</p><p><strong>Conclusion: </strong>In-silico results demonstrated the safety and efficacy of using PAI to automatically tune the UVA-MPC controller, achieving TIR values above 70% under fully closed-loop conditions and across various physiological states. Clinical validation of these results is warranted.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251315499"},"PeriodicalIF":4.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11803600/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143254443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous Glucose Monitoring in Hospitalized Adults With Diabetic Ketoacidosis: A Prospective Open-Label Pilot Study.","authors":"Magdalena M Bogun, Chunhui Wang, Paul A Kurlansky, Nur Bedeir, Guillermo E Umpierrez","doi":"10.1177/19322968251316887","DOIUrl":"10.1177/19322968251316887","url":null,"abstract":"<p><strong>Background: </strong>Continuous glucose monitoring (CGM) devices are increasingly used in critical and non-critical care hospital units. The efficacy of CGM in assessing glucose control in adults with diabetic ketoacidosis (DKA) is unknown.</p><p><strong>Methods: </strong>This single-center pilot study compared glycemic control by real-time CGM (Dexcom G6), capillary point-of-care (POC), and basic metabolic panel (BMP) during intravenous (IV) insulin treatment and after the resolution of DKA. We compared the mean absolute relative difference (MARD), median absolute relative difference (ARD) glucose values, and Diabetes Technology Society (DTS) Error Grid analyses.</p><p><strong>Results: </strong>We recruited 52 patients (49 ± 19 years, admission glucose: 503 ± 239.4 mg/dL) with type 1 diabetes (n = 24) and type 2 diabetes (n = 28). Compared with POC testing, the MARD was 17.4% ± 13.2%, and the median ARD was 14.2% (interquartile range [IQR]: 6.4, 28) during the initial IV insulin period and 19.8% ± 18.7% and 14.3% (7, 26.2) after DKA resolution. The DTS Error Grid analysis showed that 100% of values during the IV insulin treatment and 95% after the DKA resolution were in zones A+B. Compared with BMP glucose values, the MARD and median ARD were 18.5% ± 19.1% and 12.2% (5.4, 23.8) during the IV insulin treatment and 22.5% ± 24.7% and 15.1% (6.6, 27.6) after DKA resolution.</p><p><strong>Conclusion: </strong>This is the first report on the use of real-time CGM in adults with DKA. Our study indicates that CGM technology is a reliable tool for hospital use during acute insulin treatment and after the resolution of DKA. Future multicentre randomized studies are needed to determine the benefits of real-time CGM in facilitating diabetes care in hospitalized patients with hyperglycemic crises.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251316887"},"PeriodicalIF":4.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11800229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143189373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demystifying Infusion Pumps: Design of a Cost-Effective Platform for Education and Innovation.","authors":"Israel Ulises Cayetano-Jiménez, Nubia Pamela López-Jiménez, Rogelio Bustamante-Bello","doi":"10.1177/19322968251316580","DOIUrl":"10.1177/19322968251316580","url":null,"abstract":"<p><strong>Introduction: </strong>This article presents a cost-effective, modular infusion platform to help diabetes specialists customize and understand infusion pump mechanics and control principles. Traditional insulin pumps are costly and inflexible, limiting accessibility, and particularly in low-resource settings. Inspired by open-source initiatives like OpenAPS, this platform engages specialists in device operation and customization, offering practical insights into infusion technology.</p><p><strong>Method: </strong>An initial survey assessed technological literacy, customization interests, and feature preferences among Mexican diabetes specialists, followed by a hands-on engagement session with the platform's hardware. Core components are described and chosen for reliability, affordability, and integration ease. A follow-up survey evaluated specialists' confidence and interest in device customization, gathering feedback on usability and design.</p><p><strong>Results: </strong>Survey data showed strong specialist interest in understanding device mechanics and high confidence in customization after hands-on engagement. Most specialists found the hardware layout conducive to experimentation, with significant interest in closed-loop capabilities. Key valued features included safety, affordability, ease of use, customization, and integration of diverse continuous glucose monitors, with added suggestions for potential clinical certification, cost-effective supplies, and artificial intelligence integration.</p><p><strong>Conclusion: </strong>This platform offers a promising educational and developmental tool in diabetes management, bridging clinical application, and customization. Its low-cost, modular design provides a feasible solution for low-resource settings, equipping specialists to tailor devices for specific patient needs. While the platform's educational potential is clear, further studies and validation are essential for a possible transition to a clinical-grade device. Continued development could democratize access to advanced diabetes technology, transforming specialist training, and patient care.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251316580"},"PeriodicalIF":4.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11795575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143189376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Three Continuous Glucose Monitoring Systems in Adults With Type 1 Diabetes.","authors":"Manuel Eichenlaub, Delia Waldenmaier, Stephanie Wehrstedt, Stefan Pleus, Manuela Link, Nina Jendrike, Sükrü Öter, Cornelia Haug, Maren Schinz, Vincent Braunack-Mayer, Regula Schneider, Derek Brandt, Guido Freckmann","doi":"10.1177/19322968251315459","DOIUrl":"10.1177/19322968251315459","url":null,"abstract":"<p><strong>Background: </strong>The performance of continuous glucose monitoring (CGM) systems is difficult to compare due to different study designs and a lack of head-to-head studies. This study evaluated the performance of FreeStyle Libre 3 (FL3), Dexcom G7 (DG7), and Medtronic Simplera (MSP) against different comparator methods and during clinically relevant glycemic scenarios.</p><p><strong>Method: </strong>Twenty-four adult participants with type 1 diabetes mellitus wore one sensor of each CGM system in parallel for up to 15 days. Sensors of DG7 and MSP were exchanged on days 5 and 8, respectively. Three 7-hour sessions with 15-minute comparator blood glucose-level measurements using YSI 2300 (YSI, venous), Cobas Integra (INT, venous), and Contour Next (CNX, capillary) were conducted on days 2, 5, and 15. Simultaneously, glucose-level excursions with transient hyperglycemia and hypoglycemia were induced according to a recently published testing procedure. The accuracy was evaluated using various metrics, including mean absolute relative differences (MARDs).</p><p><strong>Results: </strong>Compared with YSI data, the MARDs of FL3, DG7, and MSP were 11.6%, 12.0%, and 11.6%, respectively. Relative to the INT data, the corresponding MARDs were 9.5%, 9.9%, and 13.9%, respectively, and compared with CNX data, MARDs were 9.7%, 10.1%, and 16.6%, respectively. Both FL3 and DG7 showed better accuracy in the normoglycemic and hyperglycemic range, while MSP performed better in the hypoglycemic range.</p><p><strong>Conclusions: </strong>Performance results of all CGM systems varied depending on the comparator method. However, across comparators FL3 and DG7 tended to be more accurate compared with MSP. All CGM systems showed a lower accuracy compared with previous studies, emphasizing the need for comprehensive study design guidelines.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251315459"},"PeriodicalIF":4.1,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11795573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143189378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mobile Phone Usage and Willingness to Use Mobile Phones to Support Medication Adherence and Receive Text Message Appointment Reminders in Older Outpatients With Type 2 Diabetes.","authors":"Huyen Thi Thanh Vu, Thu Thi Hoai Nguyen, Minh Ngoc Luu, Thuy Phuong Nguyen, Huong Thi Thu Nguyen, Tam Ngoc Nguyen, Thanh Xuan Nguyen, Linh Vu Huyen Ha, Huong Thi Thanh Nguyen, Janani Thillainadesan, Vasi Naganathan, Toan Thi Thanh Do, Anh Trung Nguyen","doi":"10.1177/19322968241306438","DOIUrl":"10.1177/19322968241306438","url":null,"abstract":"<p><strong>Background: </strong>Information technology can be used to improve the management of non-communicable diseases, such as diabetes. This study aims to evaluate the willingness of older outpatients with type 2 diabetes to use mobile phones to support medication adherence and receive text message appointment reminders and investigated the factors associated with this willingness.</p><p><strong>Methods: </strong>This study was a cross-sectional study conducted at the outpatient department of Dong Da General Hospital. Participants aged 60 and over managed and treated for type 2 diabetes were asked about mobile phone usage. Data were also collected on sociodemographic information, diabetes characteristics, and medical history.</p><p><strong>Results: </strong>In the 584 study participants recruited, the mean age was 73.2 (SD: 8.3) years. Approximately 80% patients with diabetes had medium or high treatment adherence and 52.4% had hemoglobin A1c (HbA_lc) < 7.5%. In the multilevel logistic regression analysis, the following factors were significantly associated with willingness to using phones to support medication adherence: college, university, or higher level (odds ratio [OR] = 2.35, 95% confidence interval [CI] = 1.10, 4.99), current smoking (OR = 5.40, 95% CI = 1.01, 28.94), whether they had a mobile phone and type of phone (basic phone: OR = 2.47, 95% CI = 1.42, 4.30; smartphone: OR = 17.93, 95% CI = 8.81, 36.47) . The following factors were significantly associated with willingness to receive these appointment reminders via mobile phone: whether they had a mobile phone and type of phone (basic phone: OR = 2.79, 95% CI = 1.70, 4.59; smartphone: OR = 9.61, 95% CI = 4.61, 19.99) and HbA_1c < 7.5 (OR = 0.65, 95% CI = 0.43, 0.99).</p><p><strong>Conclusions: </strong>Our study would suggest that there is potential value in using mobile phone to improve the management of diabetes in community living older people but this alone cannot be relied upon.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241306438"},"PeriodicalIF":4.1,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11786259/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143074206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cost-Effective Quality of Life Improvement While Reducing Health Care Professional Burnout With an AI-Driven Intervention for Personalized Medicine.","authors":"Ryan Charles Kelly, Richard I G Holt, Hermione Price, Peter Phiri, Michael Cummings, Amar Ali, Mayank Patel, Ethan Barnard, Sharon Allard, Victoria Hunter, Jana Rojkova, Clare Bolger, Daniela Georgieva, Maren Schinz, Martina Rothenbühler, Aritz Lizoain, Katharine Barnard-Kelly","doi":"10.1177/19322968241310879","DOIUrl":"10.1177/19322968241310879","url":null,"abstract":"<p><strong>Background and aims: </strong>Burnout affects >50% of physicians and nurses. Spotlight-AQ is a personalized digital health platform designed to improve routine diabetes visits. We assessed cost-effectiveness, visit length, and association with health care professional (HCP) burnout.</p><p><strong>Materials and methods: </strong>Complete case within-trial cost-effectiveness analysis embedded within a multicenter, parallel-group randomized controlled trial. Adults with diabetes were recruited from primary and secondary care. Intervention group participants completed the Spotlight-AQ pre-clinic assessment before each routine visit. Health status was assessed with EQ-5D-5L to calculate quality-adjusted life years (QALYs). Client Service Receipt Inventory measured downstream resource use. Total costs and QALYs were calculated using baseline-controlled seemingly unrelated regression with bootstrapping. Haemoglobin (HbA_1c) data were collected. Health care professionals completed the Maslach Burnout Inventory at baseline and study end.</p><p><strong>Results: </strong>A total of 98 adults (49 intervention) and 18 HCPs participated. Total costs: £243 (US$310) intervention arm versus £230 (US$293) control arm; incremental cost: £13 (US$16). Total QALYs: 0.362 intervention arm and 0.358 control arm, with an incremental QALY: 0.004. Spotlight-AQ intervention dominated usual care with a 68% probability of cost-effectiveness at a threshold of £30 000 (US$38 294) per QALY gained. Health care professionals reported reduced burnout, emotional exhaustion, depersonalization, and a greater sense of personal achievement. Doctors are more so than nurses.</p><p><strong>Conclusion: </strong>Spotlight-AQ has demonstrated cost-effective while delivering improved care and reduced HCP burnout.</p><p><strong>Trial registration: </strong>ISRCTN15511689, registration date: November 1, 2021.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241310879"},"PeriodicalIF":4.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"How the Diabetes Research Hub Will Modernize and Enhance Diabetes Data Utilization\".","authors":"","doi":"10.1177/19322968251317190","DOIUrl":"10.1177/19322968251317190","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251317190"},"PeriodicalIF":4.1,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Personalized DiaBetes TEXT Messaging Combined with Peer Support Education on Patients With Type 2 Diabetes: A Randomized Controlled Trial.","authors":"Debby Syahru Romadlon, Hui-Chuan Huang, Yu-Chi Chen, Sophia H Hu, Rudy Kurniawan, Tri Juli Edi Tarigan, Safiruddin Al Baqi, Faizul Hasan, Hsiao-Yean Chiu","doi":"10.1177/19322968251314501","DOIUrl":"10.1177/19322968251314501","url":null,"abstract":"<p><strong>Background: </strong>To investigate the effects of personalized DiaBetes TEXT messaging combined with Peer Support Education (DB-TEXT+ PSE) on clinical outcomes in patients with type 2 diabetes.</p><p><strong>Methods: </strong>An assessor-blinded, three-arm randomized controlled trial recruited 84 participants between December 2022 and July 2023. Participants were randomly assigned to a DB-TEXT + PSE group, a DB-TEXT group, or a professional education program (PEP) group. Primary outcomes included glycated hemoglobin (HbA_1c), fasting blood glucose (FBG) levels, and clinical remission rates, whereas secondary outcomes measured lipid profiles, fatigue, sleep quality, depression, and quality of life (QoL). Outcomes were assessed at baseline (T0), three months (T1), and six months (T2) postintervention.</p><p><strong>Results: </strong>Relative to PEP, personalized DB-TEXT + PSE and DB-TEXT alone led to significantly reduced HbA_1c levels at T1 and decreased FBG levels at T1 and T2. Type 2 diabetes remission was achieved by 35.7% and 50% of the participants in the DB-TEXT + PSE group, by 17.9% and 25% in the DB-TEXT group, and by 3.7% and 3.7% in the PEP group at T1 and T2, respectively. Relative to the PEP, DB-TEXT + PSE led to significantly reduced TC levels, diastolic blood pressure (DBP), and systolic blood pressure (SBP) and improved sleep quality and QoL over time.</p><p><strong>Conclusions: </strong>Personalized DB-TEXT + PSE is more effective at enhancing clinical outcomes, reducing fatigue, improving sleep quality, and improving quality of life in patients with type 2 diabetes than DB-TEXT alone and PEPs are. Educators can incorporate personalized DB-TEXT + PSE as a component of diabetes education programs and thereby integrate digital interventions and supplementary programs.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251314501"},"PeriodicalIF":4.1,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780624/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143066196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}