Diabetes technology & therapeutics最新文献

{"title":"Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis.","authors":"Ji Yoon Kim, Sang-Man Jin, Sarah B Andrade, Boyang Chen, Jae Hyeon Kim","doi":"10.1089/dia.2023.0513","DOIUrl":"10.1089/dia.2023.0513","url":null,"abstract":"<p><p><b><i>Background:</i></b> We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. <b><i>Methods:</i></b> Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). <b><i>Results:</i></b> A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (<i>P</i> < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, <i>P</i> = 0.001). <b><i>Conclusions:</i></b> In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139562958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Macronutrient Intake and Number of Meals on Glycemic Outcomes Over 1 Year in Youth with Type 1 Diabetes.","authors":"Rebecca Ortiz La Banca Barber, Lisa K Volkening, Sanjeev N Mehta, Eyal Dassau, Lori M Laffel","doi":"10.1089/dia.2023.0464","DOIUrl":"10.1089/dia.2023.0464","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Insulin bolus doses derive from glucose levels and planned carbohydrate intake, although fat and protein impact glycemic excursions. We examined the impact of macronutrients and number of daily meals/snacks on glycemic outcomes in youth with type 1 diabetes. <b><i>Methods:</i></b> Youth (<i>N</i> = 136, ages 8-17) with type 1 diabetes completed 3-day food records, wore 3-day masked continuous glucose monitoring, and had A1c measurements every 3 months for 1 year. Diet data were analyzed using Nutrition Data System for Research. Longitudinal mixed models assessed effects of macronutrient intake and number of meals/snacks on glycemic outcomes. <b><i>Results:</i></b> At baseline, youth (48% male) had mean age of 12.8 ± 2.5 years and diabetes duration of 5.9 ± 3.1 years; 73% used insulin pumps. Baseline A1c was 8.1% ± 1.0%, percent time in range 70-180 mg/dL (%TIR) was 49% ± 17%, % time below range <70 mg/dL (%TBR) was 6% ± 8%, % time above range >180 mg/dL (%TAR) was 44% ± 20%, and glycemic variability as coefficient of variation (CV) was 41% ± 8%; macronutrient intake included 48% ± 5% carbohydrate, 36% ± 5% fat, and 16% ± 2% protein. Most youth (56%) reported 3-4 meals/snacks daily (range 1-9). Over 1 year, greater carbohydrate intake was associated with lower A1c (<i>P</i> = 0.0003), more %TBR (<i>P</i> = 0.0006), less %TAR (<i>P</i> = 0.002), and higher CV (<i>P</i> = 0.03). Greater fat intake was associated with higher A1c (<i>P</i> = 0.006), less %TBR (<i>P</i> = 0.002), and more %TAR (<i>P</i> = 0.005). Greater protein intake was associated with higher A1c (<i>P</i> = 0.01). More daily meals/snacks were associated with lower A1c (<i>P</i> = 0.001), higher %TIR (<i>P</i> = 0.0006), and less %TAR (<i>P</i> = 0.0001). <b><i>Conclusions:</i></b> Both fat and protein impact glycemic outcomes. Future automated insulin delivery systems should consider all macronutrients for timely insulin provision. The present research study derived from secondary analysis of the study registered under NCT00999375.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139562859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of Two Continuous Glucose Monitoring Devices During Aerobic and High-Intensity Interval Training in Individuals with Type 1 Diabetes.","authors":"Alba Cuerda Del Pino, Rodrigo Martín-San Agustín, Alejandro José Laguna Sanz, José-Luis Díez, Ana Palanca, Paolo Rossetti, Maria Gumbau-Gimenez, F Javier Ampudia-Blasco, Jorge Bondia","doi":"10.1089/dia.2023.0535","DOIUrl":"10.1089/dia.2023.0535","url":null,"abstract":"<p><p><b><i>Background:</i></b> This study aimed to evaluate the accuracy of Dexcom G6 (DG6) and FreeStyle Libre-2 (FSL2) during aerobic training and high-intensity interval training (HIIT) in individuals with type 1 diabetes. <b><i>Methods:</i></b> Twenty-six males (mean age 29.3 ± 6.3 years and mean duration of diabetes 14.9 ± 6.1 years) participated in this study. Interstitial glucose levels were measured using DG6 and FSL2, while plasma glucose levels were measured every 10 min using YSI 2500 as the reference for glucose measurements in this study. The measurements began 20 min before the start of exercise and continued for 20 min after exercise. Seven measurements were taken for each subject and exercise. <b><i>Results:</i></b> Both DG6 and FSL2 devices showed significant differences compared to YSI glucose data for both aerobic and HIIT exercises. Continuous glucose monitoring (CGM) devices exhibited superior performance during HIIT than aerobic training, with DG6 showing a mean absolute relative difference of 14.03% versus 31.98%, respectively. In the comparison between the two devices, FSL2 demonstrated significantly higher effectiveness in aerobic training, yet its performance was inferior to DG6 during HIIT. According to the 40/40 criteria, both sensors performed similarly, with marks over 93% for all ranges and both exercises, and above 99% for HIIT and in the >180 mg/dL range, which is in accordance with FDA guidelines. <b><i>Conclusions:</i></b> The findings suggest that the accuracy of DG6 and FSL2 deteriorates during and immediately after exercise but remains acceptable for both devices during HIIT. However, accuracy is compromised with DG6 during aerobic exercise. This study is the first to compare the accuracy of two CGMs, DG6, and FSL2, during two exercise modalities, using plasma glucose YSI measurements as the gold standard for comparisons. It was registered at clinicaltrials.gov (NCT06080542).</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139431868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Glycemic Outcomes Persist for up to 2 Years in Very Young Children with the Omnipod^® 5 Automated Insulin Delivery System.","authors":"Daniel J DeSalvo, Bruce W Bode, Gregory P Forlenza, Lori M Laffel, Bruce A Buckingham, Amy B Criego, Melissa Schoelwer, Sarah A MacLeish, Jennifer L Sherr, David W Hansen, Trang T Ly","doi":"10.1089/dia.2023.0506","DOIUrl":"10.1089/dia.2023.0506","url":null,"abstract":"<p><p><b><i>Background:</i></b> To evaluate the long-term safety and effectiveness of the Omnipod^® 5 Automated Insulin Delivery (AID) System in very young children with type 1 diabetes with up to 2 years of use. <b><i>Methods:</i></b> Following a 13-week single-arm, multicenter, pivotal trial that took place after 14 days of standard therapy data collection, participating children (2-5.9 years of age at study enrollment) were provided the option to continue use of the AID system in an extension phase. HbA1c was measured every 3 months, up to 15 months of total use, and continuous glucose monitor metrics were collected through the completion of the extension study (for up to 2 years). <b><i>Results:</i></b> Participants (<i>N</i> = 80) completed 18.2 [17.4, 23.4] (median [interquartile range]) total months of AID, inclusive of the 3-month pivotal trial. During the pivotal trial, HbA1c decreased from 7.4% ± 1.0% (57 ± 10.9 mmol/mol) to 6.9% ± 0.7% (52 ± 7.7 mmol/mol, <i>P</i> < 0.0001) and was maintained at 7.0% ± 0.7% (53 ± 7.7 mmol/mol) after 15 months total use (<i>P</i> < 0.0001 from baseline). Time in target range (70-180 mg/dL) increased from 57.2% ± 15.3% during standard therapy to 68.1% ± 9.0% during the pivotal trial (<i>P</i> < 0.0001) and was maintained at 67.2% ± 9.3% during the extension phase (<i>P</i> < 0.0001 from standard therapy). Participants spent a median 97.1% of time in Automated Mode during the extension phase, with one episode of severe hypoglycemia and one episode of diabetic ketoacidosis. <b><i>Conclusion:</i></b> This evaluation of the Omnipod 5 AID System indicates that long-term use can safely maintain improvements in glycemic outcomes with up to 2 years of use in very young children with type 1 diabetes. <b>Clinical Trials Registration Number:</b> NCT04476472.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139562862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of Machine Learning Models for the Identification of Elevated Ketone Bodies During Hyperglycemia in Patients with Type 1 Diabetes.","authors":"Simon Lebech Cichosz, Clara Bender","doi":"10.1089/dia.2023.0531","DOIUrl":"10.1089/dia.2023.0531","url":null,"abstract":"<p><p><b><i>Aims:</i></b> Diabetic ketoacidosis (DKA) is a serious life-threatening condition caused by a lack of insulin, which leads to elevated plasma glucose and metabolic acidosis. Early identification of developing DKA is important to start treatment and minimize complications and risk of death. The aim of the present study is to develop and test prediction model(s) that gives an alarm about their risk of developing elevated ketone bodies during hyperglycemia. <b><i>Methods:</i></b> We analyzed data from 138 type 1 diabetes patients with measurements of ketone bodies and continuous glucose monitoring (CGM) data from over 30,000 days of wear time. We utilized a supervised binary classification machine learning approach to identify elevated levels of ketone bodies (≥0.6 mmol/L). Data material was randomly divided at patient level in 70%/30% (training/test) dataset. Logistic regression (LR) and random forest (RF) classifier were compared. <b><i>Results:</i></b> Among included patients, 913 ketone samples were eligible for modeling, including 273 event samples with ketone levels ≥0.6 mmol/L. An area under the receiver operating characteristic curve from the RF classifier was 0.836 (confidence interval [CI] 90%, 0.783-0.886) and 0.710 (CI 90%, 0.646-0.77) for the LR classifier. <b><i>Conclusions:</i></b> The novel approach for identifying elevated ketone levels in patients with type 1 diabetes utilized in this study indicates that CGM could be a valuable resource for the early prediction of patients at risk of developing DKA. Future studies are needed to validate the results.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140058911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges of GLP Analog Use for People with Type 1 Diabetes: <i>Issues with Prior Approvals and Tips for Safer Use</i>.","authors":"Satish K Garg, Janet Snell-Bergeon, Gurleen Kaur, Christie Beatson","doi":"10.1089/dia.2024.0023","DOIUrl":"10.1089/dia.2024.0023","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140184014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Initiating GLP-1 Therapy in Combination with FreeStyle Libre Provides Greater Benefit Compared with GLP-1 Therapy Alone.","authors":"Eugene E Wright, Gregory J Roberts, Joyce S Chuang, Yelena Nabutovsky, Naunihal Virdi, Eden Miller","doi":"10.1089/dia.2024.0015","DOIUrl":"10.1089/dia.2024.0015","url":null,"abstract":"<p><p><b><i>Background and Aim:</i></b> Glucagon-like peptide-1 receptor agonists (GLP-1 RA) therapy provides glycemic benefits to individuals with type 2 diabetes (T2D). However, the effects of GLP-1 RA therapy in combination with FreeStyle Libre systems (FSL) are unknown. This study aimed to compare changes in hemoglobin A1c (HbA1c) between people acquiring GLP-1 with FSL (GLP-1+FSL) versus GLP-1 without FSL (GLP-1). <b><i>Methods:</i></b> This real-world study used Optum's de-identified Market Clarity Data, a linked electronic health records (EHR)-claims database, and included adults with T2D and HbA1c ≥8% who acquired their first GLP-1 RA medication between 2018 and 2022. GLP-1+FSL subjects acquired their first FSL within ±30 days of their first GLP-1 acquisition. Cohorts were matched 1:5 on baseline insulin therapy, age, sex, baseline HbA1c, and GLP-1 type. Paired changes in HbA1c were compared between unmatched and matched groups at 6 months. <b><i>Results:</i></b> The study included 24,724 adults in the unmatched cohort (GLP-1+FSL, <i>n</i> = 478; GLP-1, <i>n</i> = 24,246). The matched cohort included 478 GLP-1+FSL users and 2,390 GLP-1 users: mean age 53.5 ± 11.8 and 53.5 ± 11.3 years, HbA1c 10.25 ± 1.68% and 10.22 ± 1.69%, respectively. HbA1c reduction was greater in the GLP-1+FSL group compared with the GLP-1 group in the unmatched cohort (-2.43% vs. -1.73%, difference 0.70%, <i>P</i> < 0.001, respectively) and in the matched cohort (-2.43% vs. -2.06%, difference 0.37%, <i>P</i> < 0.001). GLP-1+FSL vs. GLP-1 treatment was associated with greater HbA1c reduction in the intensive insulin (-2.32% vs. -1.50%), nonintensive insulin (-2.50% vs. -1.74%), and noninsulin group (-2.46% vs. -1.78%), as well as in patients using semaglutide (-2.73% vs. -1.92%) and dulaglutide (-2.45% vs. -1.71%) GLP-1 RA, all <i>P</i> < 0.001. <b><i>Conclusions:</i></b> Adults with suboptimally controlled T2D, initiating GLP-1 RA with FreeStyle Libre, had greater improvement in HbA1c compared with those treated with GLP-1 RA only. These results suggest an additional glycemic benefit of FSL when used with a GLP-1 RA in T2D treatment.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140848149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Life Achievements of MiniMed 780G Advanced Closed-Loop System in Youth with Type 1 Diabetes: AWeSoMe Study Group Multicenter Prospective Trial.","authors":"Noah Gruber, Avigail Wittenberg, Avivit Brener, Shirli Abiri, Kineret Mazor-Aronovitch, Michal Yackobovitch-Gavan, Shay Averbuch, Tal Ben Ari, Noah Levek, Neriya Levran, Zohar Landau, Marianna Rachmiel, Orit Pinhas-Hamiel, Yael Lebenthal","doi":"10.1089/dia.2024.0148","DOIUrl":"10.1089/dia.2024.0148","url":null,"abstract":"<p><p><b><i>Background:</i></b> We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. <b><i>Methods:</i></b> This prospective observational multicenter study collected demographic, clinical, and 2-week 780G system data at five time points. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. <b><i>Results:</i></b> The cohort included 93 children, 43% girls, with a median age of 15.1 years (interquartile range [IQR] 12.9,17.0). A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (<i>p</i>_time < 0.001) after the transition to 780G. The mean hemoglobin A1c (HbA1c) (SE) was 8.65% (0.12) at baseline and dropped by >1% after 1 year to 7.54% (0.14) (<i>p</i>_time < 0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (<i>P</i> < 0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (<i>P</i> = 0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (<i>P</i> < 0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to Advanced Hybrid Closed-Loop (AHCL) usage were predictors of achieving optimal glycemic control. <b><i>Conclusions:</i></b> The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of health care professionals, youth, and caregivers.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140956741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Subcutaneous Continuous Glucose Monitoring in Adult Critically Ill Patients Receiving Vasopressor Therapy.","authors":"Ola Friman, Navid Soltani, Marcus Lind, Pia Zetterqvist, Anca Balintescu, Anders Perner, Anders Oldner, Olav Rooyackers, Johan Mårtensson","doi":"10.1089/dia.2024.0035","DOIUrl":"10.1089/dia.2024.0035","url":null,"abstract":"<p><p><b><i>Background:</i></b> Subcutaneous continuous glucose monitoring (CGM) may facilitate glucose control in the ICU. We aimed to assess the accuracy of CGM (Dexcom G6) against arterial blood glucose (ABG) in adult critically ill patients receiving intravenous insulin infusion and vasopressor therapy. We also aimed to assess feasibility and tolerability of CGM in this setting. <b><i>Methods:</i></b> We included ICU patients receiving mechanical ventilation, insulin, and vasopressor therapy. Numerical accuracy was assessed by the mean absolute relative difference (MARD), overall, across arterial glucose strata, over different noradrenaline equivalent infusion rates, and over time since CGM start. MARD <14% was considered acceptable. Clinical accuracy was assessed using Clarke Error Grid (CEG) analysis. Feasibility outcome included number and duration of interrupted sensor readings due to signal loss. Tolerability outcome included skin reactions related to sensor insertion or sensor adhesives. <b><i>Results:</i></b> We obtained 2946 paired samples from 40 patients (18 with type 2 diabetes) receiving a median (IQR) maximum noradrenaline equivalent infusion rate of 0.18 (0.08-0.33) µg/kg/min during CGM. Overall, MARD was 12.7% (95% CI 10.7-15.3), and 99.8% of CGM readings were within CEG zones A and B. MARD values ≥14% were observed when ABG was outside target range (6-10 mmol/L [108-180 mg/dL]) and with noradrenaline equivalent infusion rates above 0.10 µg/kg/min. Accuracy improved with time after CGM start, reaching MARD values <14% after 36 h. We observed four episodes of interrupted sensor readings due to signal loss, ranging from 5 to 20 min. We observed no skin reaction related to sensor insertion or sensor adhesives. <b><i>Conclusions:</i></b> In our ICU cohort of patients receiving vasopressor infusion, subcutaneous CGM demonstrated acceptable overall numerical and clinical accuracy. However, suboptimal accuracy may occur outside glucose ranges of 6-10 mmol/L (108-180 mg/dL), during higher dose vasopressor infusion, and during the first 36 h after CGM start.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140956738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychometric Properties of the Automated Insulin Delivery: Benefits and Burdens Scale for Adults with Type 1 Diabetes.","authors":"Jenna B Shapiro, Anthony T Vesco, Michael S Carroll, Jill Weissberg-Benchell","doi":"10.1089/dia.2024.0117","DOIUrl":"10.1089/dia.2024.0117","url":null,"abstract":"<p><p><b><i>Objective:</i></b> To evaluate the psychometric properties of a patient-reported outcome measure, the Automated Insulin Delivery-Benefits and Burdens Scale (AID-BBS), which was designed to assess benefits and burdens of AID use in adults with type 1 diabetes (T1D). The measure was hypothesized to have validity, reliability, and clinical utility for predicting likelihood of continued use of an AID system. <b><i>Research Design and Methods:</i></b> A total of 217 adults with T1D (ages from 18 to 82 years) who were enrolled in an AID system research trial completed AID-BBS items at study midpoint (6 weeks) and at the end of the trial (13 weeks). Data were collected on pre-post glycemic outcomes. Participants completed other patient-reported psychosocial outcome measures (e.g., emotional well-being, diabetes distress, attitudes toward diabetes technology, diabetes treatment satisfaction) at Week 13. Likelihood of continued device use was assessed with three items at 13 weeks. <b><i>Results:</i></b> Exploratory factor analysis supported a one-factor structure for each subscale (15-item benefit and 9-item burden subscale) when evaluated separately. Convergent, discriminant, and predictive validity, internal consistency, and test-retest reliability were supported. Benefit and burden subscales at week 6 predicted usage intention above and beyond device impact on glycemic outcomes, also controlling for baseline glycemic outcomes. <b><i>Conclusion</i></b>: Findings support the AID-BBS as a psychometrically valid, reliable, and useful instrument for assessing burdens and benefits associated with AID system use in adults with T1D. The measure can be used to help health care providers set realistic expectations and proactively address modifiable burdens. Clinical Trial Registration Number: NCT04200313.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140956740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}