Diabetes technology & therapeutics最新文献

{"title":"MiniMed 780G System Outperforms Other Automated Insulin Systems Due to Algorithm Design, Not Bias: Response to Inaccurate Allegations.","authors":"Tim van den Heuvel, Javier Castaneda, Isabeau Thijs, Arcelia Arrieta, Lou Lintereur, John Shin, Ohad Cohen","doi":"10.1089/dia.2024.0121","DOIUrl":"10.1089/dia.2024.0121","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"783-784"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140335123","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":"Causes and Consequences of Continuous Glucose Monitor \"Breaks\": Perspectives from Adolescents with Type 1 Diabetes.","authors":"Karishma Datye, Kemberlee Bonnet, Angelee Parmar, David Schlundt, Sarah Jaser","doi":"10.1089/dia.2024.0210","DOIUrl":"10.1089/dia.2024.0210","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"780-782"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535451/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141418274","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":"Predicting Hypoglycemia and Hyperglycemia Risk During and After Activity for Adolescents with Type 1 Diabetes.","authors":"Simon Bergford, Michael C Riddell, Robin L Gal, Susana R Patton, Mark A Clements, Jennifer L Sherr, Peter Calhoun","doi":"10.1089/dia.2024.0061","DOIUrl":"10.1089/dia.2024.0061","url":null,"abstract":"<p><p><b><i>Objective:</i></b> To predict hypoglycemia and hyperglycemia risk during and after activity for adolescents with type 1 diabetes (T1D) using real-world data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study. <b><i>Methods:</i></b> Adolescents with T1D (<i>n</i> = 225; [mean ± SD] age = 14 ± 2 years; HbA1c = 7.1 ± 1.3%; T1D duration = 5 ± 4 years; 56% using hybrid closed loop), wearing continuous glucose monitors (CGMs), logged 3738 total activities over 10 days. Repeated Measures Random Forest (RMRF) and Repeated Measures Logistic Regression (RMLR) models were used to predict a composite risk of hypoglycemia (<70 mg/dL) and hyperglycemia (>250 mg/dL) within 2 h after starting exercise. <b><i>Results:</i></b> RMRF achieved high precision predicting composite risk and was more accurate than RMLR Area under the receiver operating characteristic curve (AUROC 0.737 vs. 0.661; <i>P</i> < 0.001). Activities with minimal composite risk had a starting glucose between 132 and 160 mg/dL and a glucose rate of change at activity start between -0.4 and -1.9 mg/dL/min. Time <70 mg/dL and time >250 mg/dL during the prior 24 h, HbA1c level, and insulin on board at activity start were also predictive. Separate models explored factors at the end of activity; activities with glucose between 128 and 133 mg/dL and glucose rate of change between 0.4 and -0.6 mg/dL/min had minimal composite risk. <b><i>Conclusions:</i></b> Physically active adolescents with T1D should aim to start exercise with an interstitial glucose between 130 and 160 mg/dL with a flat or slightly decreasing CGM trend to minimize risk for developing dysglycemia. Incorporating factors such as historical glucose and insulin can improve prediction modeling for the acute glucose responses to exercise.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"728-738"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140848072","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":"Response to: MiniMed 780G System Outperforms Other Automated Insulin Systems Due to Algorithm Design, Not Bias-Response to Inaccurate Allegations.","authors":"Gregory P Forlenza, Jennifer L Sherr","doi":"10.1089/dia.2024.0125","DOIUrl":"10.1089/dia.2024.0125","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"785-786"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140184016","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":" ","pages":"773-779"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","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":"The Potential Impact of Continuous Glucose Monitoring Use on Diabetes-Related Attitudes and Behaviors in Adults with Type 2 Diabetes: A Qualitative Investigation of the Patient Experience.","authors":"Taylor L Clark, William H Polonsky, Emily C Soriano","doi":"10.1089/dia.2023.0612","DOIUrl":"10.1089/dia.2023.0612","url":null,"abstract":"<p><p><b><i>Background:</i></b> Despite the known glycemic benefits of continuous glucose monitoring (CGM) for adults with type 2 diabetes (T2D), the attitudinal and behavioral changes underlying these glycemic improvements remain understudied. This study aimed to qualitatively explore these changes among a sample of adults with T2D. <b><i>Methods:</i></b> In-depth, semistructured interviews were conducted with adults with T2D who had been using CGM for 3-6 months as part of a larger community project in Ohio. Thematic analysis was used to identify themes across participants' experiences. <b><i>Results:</i></b> A total of 34 participants provided insights into their experiences with CGM. Six primary themes emerged: (1) Making the Invisible Visible, highlighting the newfound awareness of T2D in daily life. (2) Effective Decision-Making, emphasizing the use of real-time glucose data for immediate and long-term choices. (3) Enhanced Self-Efficacy, describing a renewed sense of control and motivation. (4) Diabetes-Related Diet Modifications. (5) Changes in Physical Activity. (6) Changes in Medication Taking. <b><i>Conclusions:</i></b> Participants reported a far-reaching impact of CGM on their daily lives, with many stating that CGM fostered a greater understanding of diabetes and prompted positive behavior changes. The observed attitudinal and behavioral shifts likely contributed synergistically to the significant glycemic benefits observed over the study period. This study highlights the technology's potential to bring about meaningful attitudinal and behavioral changes.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"700-708"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140206476","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":"Online Classification of Unstructured Free-Living Exercise Sessions in People with Type 1 Diabetes.","authors":"Emilia Fushimi, Eleonora M Aiello, Sunghyun Cho, Michael C Riddell, Robin L Gal, Corby K Martin, Susana R Patton, Michael R Rickels, Francis J Doyle","doi":"10.1089/dia.2023.0528","DOIUrl":"10.1089/dia.2023.0528","url":null,"abstract":"<p><p><b><i>Background:</i></b> Managing exercise in type 1 diabetes is challenging, in part, because different types of exercises can have diverging effects on glycemia. The aim of this work was to develop a classification model that can classify an exercise event (structured or unstructured) as aerobic, interval, or resistance for the purpose of incorporation into an automated insulin delivery (AID) system. <b><i>Methods:</i></b> A long short-term memory network model was developed with real-world data from 30-min structured sessions of at-home exercise (aerobic, resistance, or mixed) using triaxial accelerometer, heart rate, and activity duration information. The detection algorithm was used to classify 15 common free-living and unstructured activities and relate each to exercise-associated change in glucose. <b><i>Results:</i></b> A total of 1610 structured exercise sessions were used to train, validate, and test the model. The accuracy for the structured exercise sessions in the testing set was 72% for <i>aerobic</i>, 65% for <i>interval</i>, and 77% for <i>resistance</i>. In addition, we tested the classifier on 3328 unstructured sessions. We validated the session-associated change in glucose against the expected change during exercise for each type. Mean and standard deviation of the change in glucose of -20.8 (40.3) mg/dL were achieved for sessions classified as <i>aerobic</i>, -16.2 (39.0) mg/dL for sessions classified as <i>interval</i>, and -11.6 (38.8) mg/dL for sessions classified as <i>resistance</i>. <b><i>Conclusions:</i></b> The proposed algorithm reliably identified physical activity associated with expected change in glucose, which could be integrated into an AID system to manage the exercise disturbance in glycemia according to the predicted class.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"709-719"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139989517","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":" ","pages":"763-772"},"PeriodicalIF":5.7,"publicationDate":"2024-10-01","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":"An Automated Insulin Delivery System with Automatic Meal Bolus Based on a Hand-Gesturing Algorithm.","authors":"Anirban Roy, Benyamin Grosman, Andrea Benedetti, Bahman Engheta, Diana Miller, Maya Laron-Hirsh, Yael Cohen, Roseline Ré, Shannon N Edd, Robert Vigersky, Ohad Cohen, Amir Tirosh","doi":"10.1089/dia.2023.0529","DOIUrl":"10.1089/dia.2023.0529","url":null,"abstract":"<p><p><b><i>Background:</i></b> Carbohydrate counting (CC) and meal announcements, before eating, introduce a significant burden for individuals managing type 1 diabetes (T1D). An automated insulin delivery system with automatic bolusing that eliminates the need for CC and premeal bolusing (i.e., a hands-free closed-loop [HFCL] system) was assessed in a feasibility trial of adults with T1D. <b><i>Methods:</i></b> The system included the MiniMed™ 780G pump and a smartphone-paired smartwatch with the Klue application (Klue, Inc.) that detects eating and drinking gestures. A smartphone algorithm converted gestures into carb amounts that were transmitted to the pump for automatic bolusing. For 5 days, participants (<i>N</i> = 17, 18-75 years of age) used the system at home with meal announcements based on traditional CC, with the Klue application disabled (Home-stay phase). Thereafter, participants moved to a supervised hotel setting, where the Klue application was enabled for 5 days and meals were not announced (Hotel-stay phase). Participants consumed the same eight test meals (six solid and two liquid) of varying caloric and carb size at the same time and day of the week for both phases, and glycemic metrics were compared. Otherwise, there were no other meal restrictions. <b><i>Results:</i></b> The overall time in range (70-180 mg/dL) was 83.4% ± 7.0% and 80.6% ± 6.7% for the Home-stay and Hotel-stay, respectively (<i>P</i> = 0.08). The average time at <70 mg/dL was 3.1% and 3.0% (<i>P</i> = 0.9144), respectively, and the average time at >180 mg/dL was 13.5% and 16.3% (<i>P</i> = 0.1046), respectively. Postprandial glycemia following low-carb test meals was similar between the two phases. The system's ability to accommodate high-carb meals was somewhat limited. There were no episodes of severe hypoglycemia or diabetic ketoacidosis. <b><i>Conclusion:</i></b> Preliminary findings show that a HFCL system was safe and maintained overall glycemic control, similar to that observed with traditional CC and manual meal bolusing. By eliminating these daily T1D burdens, a HFCL system may improve quality of life for individuals with T1D. ClinicalTrials.gov number: NCT04964128.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"633-643"},"PeriodicalIF":5.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139989575","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":"Contemporary Management of Obesity: A Comparison of Bariatric Metabolic Surgery and Novel Incretin Mimetic Drugs.","authors":"Abhayjit Singh, Steven E Nissen","doi":"10.1089/dia.2024.0122","DOIUrl":"10.1089/dia.2024.0122","url":null,"abstract":"<p><p>The global prevalence of obesity has risen sharply during the past half-century, reaching pandemic proportions and creating a public health crisis. Obesity is a recognized risk factor for the development of diabetes, atherosclerosis, hypertension, hepatic steatosis, and many other cardiometabolic disorders with significant resultant morbidity and mortality. Though treatment of obesity can prevent or slow the progression of the aforementioned illnesses, efforts to help patients achieve reliable and sustainable weight loss have had limited success. Improving nutrition and increasing physical activity results in a host of health benefits; however, the weight loss achieved with lifestyle interventions alone is modest and difficult to sustain. Early attempts at medical and surgical treatment of obesity were plagued with adverse effects and complications. Moreover, these approaches failed to demonstrate long-term health benefits, even when weight loss was achieved. Recently, novel incretin-based therapies targeting glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptors have gained popularity because of their effectiveness in achieving substantial weight loss in patients both with and without diabetes. Following many successful clinical trials, there are now multiple GLP-1 receptor agonists and one dual GLP-1-GIP receptor agonist approved by the Food and Drug Administration for chronic weight management. Advancements in laparoscopic surgical technique and refinements in procedure selection have similarly improved the safety and efficacy of bariatric metabolic surgery for patients with obesity. In this review, we discuss the advantages and disadvantages of contemporary pharmacologic and surgical weight management strategies. We review the data regarding expected weight loss, glycemic control, cardiometabolic benefits, and potential adverse effects of various treatment approaches. As obesity rates continue to rise worldwide, it is imperative that clinicians keep these considerations in mind in order to better care for patients.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"673-685"},"PeriodicalIF":5.7,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140849911","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}