Diabetes technology & therapeutics最新文献

{"title":"Accuracy of a Continuous Glucose Monitor in the Intensive Care Unit: A Proposed Accuracy Standard and Calibration Protocol for Inpatient Use.","authors":"Sewon A Bann, Jess C Hercus, Paul Atkins, Areej Alkhairy, Jackson P Loyal, Mypinder Sekhon, David J Thompson","doi":"10.1089/dia.2024.0074","DOIUrl":"https://doi.org/10.1089/dia.2024.0074","url":null,"abstract":"<p><p><b><i>Background and</i> <i>Aims:</i></b> Guidelines now recommend inpatient continuous glucose monitor (CGM) use with confirmatory blood glucose measurements. However, the Food and Drug Administration has not yet officially approved CGM for inpatient use in large part because its accuracy has not been established in this setting. We tested the accuracy of the Dexcom G6 (G6) in 28 adults on an insulin infusion in a medical-surgical intensive care unit with 1064 matched CGM and arterial point-of-care pairs. <b><i>Methods:</i></b> The participants were on average 57.29 (SD 2.39) years, of whom 13 had a prior diagnosis of diabetes and 14 were admitted for a surgical diagnosis. The first 19 participants received the G6 without calibration and had a mean absolute relative difference (MARD) of 13.19% (IQR 5.11, 19.03) across 659 matched pairs, which just meets the critical care expert recommendation of MARD <14%. We then aimed to improve accuracy for the subsequent 9 participants using a calibration protocol. <b><i>Results:</i></b> The MARD for calibrated participants was 9.65% (3.03, 13.33), significantly lower than for uncalibrated participants (<i>P</i> < 0.001). Calibration also demonstrated excellent safety with 100% of values within the Clarke Error Grid zones A and B compared with 99.07% without calibration. Our protocol achieved the lowest MARD and safest CEG profile in the critical care setting and well exceeds the critical care expert recommendations. Our large sample of heterogenous critically ill patients also reached comparable accuracy to the MARD of 9% for G6 in outpatients. We believe our calibration protocol will allow G6 to be used with sufficient accuracy in inpatients.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141442295","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":"Long-Term Improvements in Glycemic Control with Dexcom CGM Use in Adults with Noninsulin-Treated Type 2 Diabetes.","authors":"Jennifer E Layne, Lauren H Jepson, Alexander M Carite, Christopher G Parkin, Richard M Bergenstal","doi":"10.1089/dia.2024.0197","DOIUrl":"https://doi.org/10.1089/dia.2024.0197","url":null,"abstract":"<p><p><b><i>Aims:</i></b> The objective of this real-world, observational study was to evaluate change in continuing glucose monitoring (CGM) metrics for 1 year after CGM initiation in adults with noninsulin-treated type 2 diabetes (T2D). <b><i>Methods:</i></b> Data were analyzed from Dexcom G6 and G7 users who self-reported: T2D, ≥18 years, gender, no insulin use, and had a baseline percent time in range (TIR) 70-180 mg/dL of ≤70%. Outcomes were change in CGM metrics from baseline to 6 and 12 months overall and for younger (<65 years) and older (≥65 years) cohorts. Additional analyses explored the relationship between use of the high alert feature and change in TIR and time in tight range (TITR) 70-140 mg/dL. <b><i>Results:</i></b> CGM users (<i>n</i> = 3,840) were mean (SD) 52.5 (11.2) years, 47.9% female, mean TIR was 41.7% (21.4%), and 12.4% of participants were ≥65 years. Significant improvement in all CGM metrics not meeting target values at baseline was observed at 6 months, with continued improvement at 12 months. Mean baseline TIR increased by 17.3% (32.1%) from 41.7% (21.4%) to 59.0% (28.9%), and mean glucose management indicator decreased by 0.5% (1.2%) from 8.1% (0.9%) to 7.6% (1.1%) (both <i>P</i> < 0.001). Participants who maintained or customized the high alert default setting of 250 mg/dL had a greater increase in TIR and TITR compared with participants who disabled the alert. Days of CGM use over 12 months were high in 84.7% (15.9%). <b><i>Conclusion:</i></b> In this large, real-world study of adults with suboptimally controlled T2D not using insulin, Dexcom CGM use was associated with meaningful improvements in glycemic control over 12 months. Use of the high alert system feature was positively associated with glycemic outcomes. High use of CGM over 12 months suggests benefits related to consistent CGM use in this population.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.7,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141431655","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":"Continuous Glucose Monitoring Metrics and Hemoglobin A1c Relationship in Patients with Type 2 Diabetes Treated by Hemodialysis.","authors":"Rodolfo J Galindo, Bobak Moazzami, Katherine R Tuttle, Richard M Bergenstal, Limin Peng, Guillermo E Umpierrez","doi":"10.1089/dia.2024.0145","DOIUrl":"10.1089/dia.2024.0145","url":null,"abstract":"<p><p><b><i>Background:</i></b>There is a need for accurate glycemic control metrics in patients with diabetes and end-stage kidney disease (ESKD). Hence, we assessed the relationship of continuous glucose monitoring (CGM) metrics and laboratory-measured hemoglobin A1c (HbA1c) in patients with type 2 diabetes (T2D) treated by hemodialysis. <b><i>Methods:</i></b> This prospective observational study included adults (age 18-80 years) with T2D (HbA1c 5%-12%), treated by hemodialysis (for at least 90 days). Participants used a Dexcom G6 Pro CGM for 10 days. Correlation analyses between CGM metrics [mean glucose, glucose management indicator (GMI), and time-in-range (TIR 70-180 mg/dL)] and HbA1c were performed. <b><i>Results:</i></b> Among 59 participants (mean age was 57.7 ± 9.3 years, 58% were female, 86% were non-Hispanic blacks), the CGM mean glucose level was 188.9 ± 45 mg/dL (95% CI: 177.2, 200.7), the mean HbA1c and GMI were 7.1% ± 1.3% and 7.8% ± 1.1%, respectively (difference 0.74% ± 0.95). GMI had a strong negative correlation with TIR 70-180 mg/dL (r = -0.96). The correlation between GMI and HbA1c (r = 0.68) was moderate. Up to 29% of participants had a discordance between HbA1c and GMI of <0.5%, with 22% having a discordance between 0.5% and 1%, and 49% having a discordance of >1%. <b><i>Conclusions:</i></b> In patients with diabetes and ESKD treated by hemodialysis, the GMI has a strong correlation with TIR, while HbA1c underestimated the average glucose and GMI. Given the limitations of HbA1c in this population, GMI or mean glucose and TIR may be considered as more appropriate glucose control markers.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141161181","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":"Continuous Glucose Monitoring and Recreational Scuba Diving in Type 1 Diabetes: Head-to-Head Comparison Between Free Style Libre 3 and Dexcom G7 Performance.","authors":"Elena Gamarra, Giovanni Careddu, Andrea Fazi, Valentina Turra, Ambra Morelli, Chiara Camponovo, Pierpaolo Trimboli","doi":"10.1089/dia.2024.0126","DOIUrl":"10.1089/dia.2024.0126","url":null,"abstract":"<p><p><b><i>Background:</i></b> Scuba diving was previously excluded because of hypoglycemic risks for patients with type 1 diabetes mellitus(T1DM). Specific eligibility criteria and a safety protocol have been defined, whereas continuous glucose monitoring (CGM) systems have enhanced diabetes management. This study aims to assess the feasibility and accuracy of CGM Dexcom G7 and Free Style Libre 3 in a setting of repetitive scuba diving in T1DM, exploring the possibility of nonadjunctive use. <b><i>Material and Methods:</i></b> The study was conducted during an event of <i>Diabete Sommerso^®</i> association in 2023. Participants followed a safety protocol, with capillary glucose as reference standard (Beurer GL50Evo). Sensors' accuracy was evaluated through median and mean absolute relative difference (MeARD, MARD) and surveillance error grid (SEG). Data distribution and correlation were estimated by Spearman test and Bland-Altman plots. The ability of sensors to identify hypoglycemia was assessed by contingency tables. <b><i>Results:</i></b> Data from 202 dives of 13 patients were collected. The overall MARD was 31% (Dexcom G7) and 14.2% (Free Style Libre 3) and MeARD was 19.7% and 11.6%, respectively. Free Style Libre 3 exhibited better accuracy in normoglycemic and hyperglycemic ranges. SEG analysis showed 82.1% (Dexcom G7) and 97.4% (Free Style Libre 3) data on no-risk zone. Free Style Libre 3 better performed on hypoglycemia identification (diagnostic odds ratio of 254.10 vs. 58.95). Neither of the sensors reached the MARD for nonadjunctive use. <b><i>Conclusions:</i></b> The study reveals Free Style Libre 3 superior accuracy compared with Dexcom G7 in a setting of repetitive scuba diving in T1DM, except for hypoglycemic range. Both sensors fail to achieve accuracy for nonadjunctive use. Capillary tests remain crucial for safe dive planning, and sensor data should be interpreted cautiously. We suggest exploring additional factors potentially influencing sensor performance.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141070356","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":"Assessing Patterns of Continuous Glucose Monitoring Use and Metrics of Glycemic Control in Type 1 Diabetes and Type 2 Diabetes Patients in the Veterans Health Care System: Integrating Continuous Glucose Monitoring Device Data with Electronic Health Records Data.","authors":"Tomoki Okuno, Sharon A Macwan, Donald Miller, Gregory J Norman, Peter Reaven, Jin J Zhou","doi":"10.1089/dia.2024.0083","DOIUrl":"10.1089/dia.2024.0083","url":null,"abstract":"<p><p><b><i>Objective:</i></b> To integrate long-term daily continuous glucose monitoring (CGM) device data with electronic health records (EHR) for patients with type 1 and type 2 diabetes (T1D and T2D) in the national Veterans Affairs Healthcare System to assess real-world patterns of CGM use and the reliability of EHR-based CGM information. <b><i>Research Design and Methods:</i></b> This observational study used Dexcom CGM device data linked with EHR (from 2015 to 2020) for a large national cohort of patients with diabetes. We tracked the initiation and consistency of CGM use, assessed concordance of CGM use and measures of glucose control between CGM device data and EHR records, and examined results by age, ethnicity, and diabetes type. <b><i>Results:</i></b> The time from pharmacy release of CGM to patients to initiation of uploading CGM data to Dexcom servers averaged 3 weeks but demonstrated wide variation among individuals; importantly, this delay decreased markedly over the later years. The average daily wear time of CGM exceeded 22 h over nearly 3 years of follow-up. Patterns of CGM use were generally consistent across age, race/ethnicity groups, and diabetes type. There was strong concordance between EHR-based estimates of CGM use and Dexcom CGM wear time and between estimates of glucose control from both sources. <b><i>Conclusions:</i></b> The study demonstrates our ability to reliably integrate CGM devices and EHR data to provide valuable insights into CGM use patterns. The results indicate in the real-world environment that CGM is worn consistently over many years for both patients with T1D and T2D within the Veterans Affairs Healthcare System and is similar across major race/ethnic groups and age-groups.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141070354","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":"Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.","authors":"Gregg D Simonson, Amy B Criego, Tadej Battelino, Anders L Carlson, Pratik Choudhary, Sylvia Franc, Dana Gershenoff, George Grunberger, Irl B Hirsch, Diana Isaacs, Mary L Johnson, David Kerr, Davida F Kruger, Chantal Mathieu, Thomas W Martens, Revital Nimri, Sean M Oser, Anne L Peters, Ruth S Weinstock, Eugene E Wright, Carol H Wysham, Richard M Bergenstal","doi":"10.1089/dia.2024.0107","DOIUrl":"10.1089/dia.2024.0107","url":null,"abstract":"<p><p><b><i>Background</i></b>: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. <b><i>Methods</i></b>: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. <b><i>Results</i></b>: The <i>Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen</i> brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. <b><i>Conclusion</i></b>: The <i>AGP Report: Connected Insulin Pen</i> is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140956737","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":"The Type of Patient Training Does Not Impact Outcomes in the First 90 Days of Automated Insulin Delivery Use.","authors":"Seema Meighan, Julia L Douvas, Andrew Rearson, Robert Squaresky, Andrea Kelly, Brynn E Marks","doi":"10.1089/dia.2024.0096","DOIUrl":"10.1089/dia.2024.0096","url":null,"abstract":"<p><p><b><i>Background:</i></b> Youth starting Omnipod 5 (OP5) can onboard with a diabetes educator or self-start with support from online, industry-provided educational modules. We compared glycemic control and pump interaction by training type among youth initiating OP5. <b><i>Methods:</i></b> This retrospective review included 297 youth with type 1 diabetes (T1D) aged <22 years initiating OP5. We analyzed baseline continuous glucose monitor (CGM) data and pump and CGM data from the first 90 days of OP5 use. Multilevel mixed-effects regression assessed for changes in time in range (TIR) from baseline to 90 days by training type. <b><i>Results:</i></b> Of youth initiating OP5, 42.4% trained with a diabetes educator and 57.6% self-started. At baseline, self-starters had a longer T1D duration (5.0 (2.6,7.9) vs. 2.5 (1.3, 5.5) years, <i>P</i> = 0.001), more time <54 mg/dL (0.3% (0.1,1) vs. 0.15% (0,1), <i>P</i> = 0.01), and a higher coefficient of variation (40.2% (37, 44.4) vs. 38.7% (34.4, 42.4), <i>P</i> = 0.004). After 90 days of OP5 use, groups did not differ in time in automated mode or boluses per day. In a longitudinal model, after adjusting for baseline TIR and T1D duration, 90-day TIR was 10.5%-points higher (CI: 9.2-11.8, <i>P</i> < 0.0001), positively associated with baseline TIR (β = 0.82, CI: 0.78-0.85, <i>P</i> < 0.0001), and 1.1%-points greater among self-starters (CI: 0.06-2.2; <i>P</i> = 0.04). <b><i>Conclusions:</i></b> After 90 days of OP5 use, glycemic control and pump interactions were minimally different between youth who self-started and those who trained with a diabetes educator. For youth at a tertiary care center previously using an Omnipod system, online educational modules offered by industry provide sufficient training for use.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141161189","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":"12-Month Real-Life Efficacy of the MiniMed 780G Advanced Closed-Loop System in Patients Living with Type 1 Diabetes: A French Observational, Retrospective, Multicentric Study.","authors":"Sandrine Lablanche, Johanna Delagenière, Manon Jalbert, Emmanuel Sonnet, Muriel Benichou, Nathalie Arnold, Anne Spiteri, Jean-Philippe Le Berre, Eric Renard, Nicolas Chevalier, Sophie Borot, Elisabeth Bonnemaison, Christine Coffin, Marie-Pierre Teissier, Pierre Yves Benhamou, Jean-Christian Borel, Alfred Penfornis, Michael Joubert, Laurence Kessler","doi":"10.1089/dia.2023.0414","DOIUrl":"10.1089/dia.2023.0414","url":null,"abstract":"<p><p><b><i>Aim:</i></b> To evaluate the evolution of glycemic outcomes in patients living with type 1 diabetes (T1D) after 1 year of use of the MiniMed 780G advanced hybrid closed-loop (AHCL) system. <b><i>Methods:</i></b> We conducted an observational, retrospective, multicentric study in 20 centers in France. The primary objective was to evaluate the improvement in glycemic control after 1-year use of AHCL. The primary endpoint was the variation of time in range (TIR) between pre-AHCL and after 1-year use of AHCL. Secondary objectives were to analyze the glycemic outcomes after 3, 6, and 12 months of AHCL use, the safety, and the long-term observance of AHCL. <b><i>Results:</i></b> Two hundred twenty patients were included, and 200 were analyzed for the primary endpoint. 92.7% of patients continued to use AHCL. After 1 year of use of AHCL, TIR was 72.5% ± 10.6% (+9.1%; 95% confidence interval [CI] [7.6-10.5] compared to pre-AHCL initiation, <i>P</i> < 0.001), HbA1c 7.1% ± 0.7% (-0.5%; 95% CI [-0.6 to -0.4]; <i>P</i> < 0.001), time below range 2.0% [1.0; 3.0] (0.0% [-2.0; 0.0], <i>P</i> < 0.001), and time above range 24.8% ± 10.9% (-7.3%; 95% CI [-8.8 to -5.7]; <i>P</i> < 0.001). More patients achieved the glycemic treatment goals of HbA1c <7.0% (45.1% vs. 18.1%, <i>P</i> < 0.001) and TIR >70% (59.0% vs. 29.5% <i>P</i> < 0.001) when compared with pre-AHCL. Five patients experienced severe hypoglycemia events and two patients experienced ketoacidosis. <b><i>Conclusion:</i></b> After 1 year of use of AHCL, people living with T1D safely improved their glucose control and a higher proportion of them achieved optimal glycemic control.</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":"139490235","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":"Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm.","authors":"Boris Kovatchev, Alberto Castillo, Elliott Pryor, Laura L Kollar, Charlotte L Barnett, Mark D DeBoer, Sue A Brown","doi":"10.1089/dia.2023.0469","DOIUrl":"10.1089/dia.2023.0469","url":null,"abstract":"<p><p><b><i>Background:</i></b> Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. <b><i>Methods:</i></b> The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. <b><i>Results:</i></b> The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. <b><i>Conclusion:</i></b> In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.</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":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11305265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139563014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and Safety of Tirzepatide in Overweight and Obese Adult Patients with Type 1 Diabetes.","authors":"Satish K Garg, Halis K Akturk, Gurleen Kaur, Christie Beatson, Janet Snell-Bergeon","doi":"10.1089/dia.2024.0050","DOIUrl":"10.1089/dia.2024.0050","url":null,"abstract":"<p><p><b><i>Introduction and Objective:</i></b> Most patients with type 1 diabetes (T1D) in the United States are overweight (OW) or obese (OB), contributing to insulin resistance and suboptimal glucose control. The primary Food and Drug Administration-approved treatment for T1D is insulin, which may adversely affect weight. Tirzepatide is approved for managing type 2 diabetes, improves glucose control, facilitates weight loss, and improves cardiovascular disease outcomes. We assessed the use of tirzepatide in OW/OB subjects with T1D. <b><i>Methods:</i></b> This was a retrospective single-center real-world study in 62 OW/OB adult patients with T1D who were prescribed tirzepatide (treated group) and followed for 1 year. At least 3 months of use of tirzepatide was one of the inclusion criteria. Based on the inclusion criteria, this study represents 62 patients out of 184 prescribed tirzepatide. The control group included 37 OW/OB patients with T1D (computer frequency matched by age, duration of diabetes, gender, body mass index (BMI), and glucose control) who were not using any other weight-loss medications during the same period. The mean (±standard deviation [SD]) dose of weekly tirzepatide at 3 months was 5.6 ± 1.9 mg that increased to 9.7 ± 3.3 mg at 1 year. <b><i>Results:</i></b> The gender, mean baseline age, duration of diabetes, and glycosylated hemoglobin (HbA1c) were similar in the two groups, whereas BMI and weight were higher in the treated group. There were significantly larger declines in BMI and weight in the treated group than in controls across all time points among those in whom data were available. HbA1c decreased in the treated group as early as 3 months and was sustained through a 1-year follow-up (-0.67% at 1 year). As expected, insulin dose decreased at 3 months and throughout the study period. There were no reported hospitalizations from severe hypoglycemia or diabetic ketoacidosis. The mean glucose, time-in-range, time-above-range, SD, and coefficient of variation (continuous glucose monitoring metrics) significantly improved in the treated group. <b><i>Conclusions:</i></b> In this pilot (off label) study, we conclude that tirzepatide facilitated an average 18.5% weight loss (>46 pounds) and improved glucose control in OW/OB patients with T1D at 1 year. For safe use of tirzepatide in patients with T1D, we strongly recommend a large prospective randomized control trial in OW/OB patients with T1D.</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":"140184015","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}