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Roos T, Hermanns N, Groß C, Kulzer B, Haak T, Ehrmann D. Effect of automated insulin delivery systems on person-reported outcomes in people with diabetes: a systematic review and meta-analysis. EClinicalMedicine 2024; 76:102852. [PMID: 39364272 PMCID: PMC11447321 DOI: 10.1016/j.eclinm.2024.102852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 09/05/2024] [Accepted: 09/10/2024] [Indexed: 10/05/2024] Open
Abstract
Background Conclusive evidence on the benefits of automated insulin delivery (AID) systems on person-reported outcomes (PROs) is missing. Methods In this systematic review and meta-analysis, four databases (PubMed, PsycINFO, Cochrane, and GoogleScholar) were searched from inception up to August 7th, 2024. All types of studies were included if studies reported on PROs in people with diabetes using an AID system. All types of control groups in randomised controlled trials (RCT) were included. Summary data were extracted by three reviewers. Main outcomes focused on diabetes distress, fear of hypoglycaemia and quality of life. Meta-analyses were conducted for RCTs and observational studies separately. When five or more studies could be pooled, random-effects meta-analysis was used, otherwise common-effects meta-analysis was used. Risk of bias was evaluated with Cochrane tools. This study was registered with PROSPERO, CRD42022352502. Findings A total of 62 studies (n = 9253) were included reporting on 45 different questionnaires. Twenty-seven studies were RCTs and 25 were observational studies. RCT meta-analyses showed reduced diabetes distress (standardised mean difference [95% CI]: -0.159 [-0.309, -0.010], I2 = 23.0%), reduced fear of hypoglycaemia (-0.339 [-0.566, -0.111], I2 = 42.6%), and improved hypoglycaemia unawareness (-0.231 [-0.424, -0.037], I2 = 0.0%), quality of life in adults (0.347 [0.134, 0.560], I2 = 0.0%) and children/adolescents (0.249 [0.050, 0.448], I2 = 0.0%). Observational meta-analyses corroborated improvements in diabetes distress (-0.217 [-0.403, -0.031], I2 = 68.5%), fear of hypoglycaemia (-0.445 [-0.540, -0.349], I2 = 0.0%), hypoglycaemia unawareness (-0.212 [-0.419, -0.004], I2 = 0.0%), and showed improved sleep quality (-0.158 [-0.255, -0.061], I2 = 0.0%). Interpretation We found low to moderate effect sizes indicating that AID therapy is associated with reduced burden and improved well-being in people with diabetes. Evidence comes from both RCTs and observational studies. However, for some PROs only a limited number of studies could be pooled with a large heterogeneity in questionnaires used. More research is needed with a more uniformed assessment of PROs to demonstrate the added value of AID therapy on psychosocial outcomes. Funding None.
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Affiliation(s)
- Timm Roos
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, 97980, Bad Mergentheim, Germany
| | - Norbert Hermanns
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, 97980, Bad Mergentheim, Germany
- Department of Clinical Psychology and Psychotherapy, Otto-Friedrich-University of Bamberg, Markusplatz 3, 96047, Bamberg, Germany
| | - Christopher Groß
- Department of Clinical Psychology and Psychotherapy, Otto-Friedrich-University of Bamberg, Markusplatz 3, 96047, Bamberg, Germany
| | - Bernhard Kulzer
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, 97980, Bad Mergentheim, Germany
- Department of Clinical Psychology and Psychotherapy, Otto-Friedrich-University of Bamberg, Markusplatz 3, 96047, Bamberg, Germany
| | - Thomas Haak
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, 97980, Bad Mergentheim, Germany
- Diabetes Centre Mergentheim, Diabetes Clinic, Theodor-Klotzbuecher-Str. 12, 97980, Bad Mergentheim, Germany
| | - Dominic Ehrmann
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, 97980, Bad Mergentheim, Germany
- Department of Clinical Psychology and Psychotherapy, Otto-Friedrich-University of Bamberg, Markusplatz 3, 96047, Bamberg, Germany
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Forlenza GP, Tabatabai I, Lewis DM. Point-Counterpoint: The Need for Do-It-Yourself (DIY) Open Source (OS) AID Systems in Type 1 Diabetes Management. Diabetes Technol Ther 2024; 26:689-699. [PMID: 38669472 DOI: 10.1089/dia.2024.0073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
In the last decade, technology developed by people with diabetes and their loved ones has added to the options for diabetes management. One such example is that of automated insulin delivery (AID) algorithms, which were created and shared as open source by people living with type 1 diabetes (T1D) years before commercial systems were first available. Now, numerous options for commercial systems exist in some countries, yet tens of thousands of people with diabetes are still choosing Open-Source AID (OS-AID), previously called "do-it-yourself" (DIY) systems, which are noncommercial versions of these open-source AID systems. In this article, we provide point and counterpoint perspectives regarding (1) safety and efficacy, (2) regulation and support, (3) user choice and flexibility, (4) access and affordability, and (5) patient and provider education, for open source and commercial AID systems. The perspectives reflected here include that of a person living with T1D who uses and has developed OS-AID systems, a physician-researcher based in the United States who conducts clinical trials to support development of commercial AID systems and supports people with diabetes using all types of AID, and an endocrinologist with T1D who uses both systems and treats people with diabetes using all types of AID.
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Affiliation(s)
- Gregory P Forlenza
- Barbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Ideen Tabatabai
- Barbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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Ferguson AM, Lin AC. Themes, Rates, and Risk of Adverse Events of the Artificial Pancreas in the United States Using MAUDE. Ann Biomed Eng 2024; 52:2282-2286. [PMID: 38740730 PMCID: PMC11247049 DOI: 10.1007/s10439-024-03529-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024]
Abstract
Three manufacturers sell artificial pancreas systems in the United States for management of Type 1 Diabetes. Given the life-saving task required of an artificial pancreas there needs to be a high level of trust and safety in the devices. This evaluation sought to find the adjusted safety event reporting rate and themes along with device-associated risk in events reported utilizing the MAUDE database. We searched device names in the MAUDE database over the period from 2016 until August 2023 (the date of retrieval). Thematic analysis was performed using dual-reviewer examination with a 96% concurrence. Relative risk (RR) was calculated for injury, malfunction, and overall, for each manufacturer, as well as adjusted event rate per manufacturer. Most events reported related to defects in the manufacturing of the casing materials which resulted in non-delivery of therapy. Tandem Diabetes Care, Inc. had an adjusted event rate of 50 per 100,000 units and RR of 0.0225. Insulet had an adjusted event rate of 300 per 100,000 units and RR of 0.1684. Medtronic has an adjusted event rate of 2771.43 per 100,000 units and RR of 20.7857. The newer Medtronic devices show improvements in likely event rate. While the artificial pancreas is still in its infancy, these event rates are not at an acceptable level for a device which can precipitate death from malfunctions. Further exploration into safety events and much more research and development is needed for devices to reduce the event rates. Improved manufacturing practices, especially the casing materials, are highly recommended. The artificial pancreas holds promise for millions but must be improved before it becomes a true life-saving device that it has the potential to become.
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Affiliation(s)
- Andrew M Ferguson
- University of Cincinnati College of Medicine, Cincinnati, USA.
- University of Cincinnati College of Pharmacy, Cincinnati, USA.
| | - Alex C Lin
- University of Cincinnati College of Pharmacy, Cincinnati, USA
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McClure RD, Talbo MK, Bonhoure A, Molveau J, South CA, Lebbar M, Wu Z. Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review. Curr Diab Rep 2024; 24:61-73. [PMID: 38294726 DOI: 10.1007/s11892-024-01534-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/17/2024] [Indexed: 02/01/2024]
Abstract
PURPOSE OF REVIEW Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions. RECENT FINDINGS Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.
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Affiliation(s)
- Reid D McClure
- Faculty of Kinesiology, Sport and Recreation, University of Alberta, 3-100 University Hall, Edmonton, AB, T6G 2H9, Canada
- Alberta Diabetes Institute, Li Ka Shing Centre, University of Alberta, Edmonton, AB, T6G 2T9, Canada
| | - Meryem K Talbo
- School of Human Nutrition, McGill University, 21111 Lakeshore Dr, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Anne Bonhoure
- Montreal Clinical Research Institute, 110 Pine Ave W, Montreal, QC, H2W 1R7, Canada
- Department of Nutrition, Faculty of Medicine, Universite de Montréal, 2405, Chemin de La Côte-Sainte-Catherine, Montreal, QC, H3T 1A8, Canada
| | - Joséphine Molveau
- Montreal Clinical Research Institute, 110 Pine Ave W, Montreal, QC, H2W 1R7, Canada
- Department of Nutrition, Faculty of Medicine, Universite de Montréal, 2405, Chemin de La Côte-Sainte-Catherine, Montreal, QC, H3T 1A8, Canada
- Univ. Lille, Univ. Artois, Univ. Littoral Côte d'Opale, ULR 7369 - URePSSS - Unité de Recherche Pluridisciplinaire Sport Santé Société, Lille, France
| | - Courtney A South
- School of Human Nutrition, McGill University, 21111 Lakeshore Dr, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Maha Lebbar
- Montreal Clinical Research Institute, 110 Pine Ave W, Montreal, QC, H2W 1R7, Canada
- Department of Nutrition, Faculty of Medicine, Universite de Montréal, 2405, Chemin de La Côte-Sainte-Catherine, Montreal, QC, H3T 1A8, Canada
| | - Zekai Wu
- Montreal Clinical Research Institute, 110 Pine Ave W, Montreal, QC, H2W 1R7, Canada.
- Department of Medicine, Division of Experimental Medicine, McGill University, 1001 Décarie Boulevard, Montreal, QC, H4A 3J1, Canada.
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Schipp J, Hendrieckx C, Braune K, Knoll C, O'Donnell S, Ballhausen H, Cleal B, Wäldchen M, Lewis DM, Gajewska KA, Skinner TC, Speight J. Psychosocial Outcomes Among Users and Nonusers of Open-Source Automated Insulin Delivery Systems: Multinational Survey of Adults With Type 1 Diabetes. J Med Internet Res 2023; 25:e44002. [PMID: 38096018 PMCID: PMC10755653 DOI: 10.2196/44002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 06/10/2023] [Accepted: 10/23/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Emerging research suggests that open-source automated insulin delivery (AID) may reduce diabetes burden and improve sleep quality and quality of life (QoL). However, the evidence is mostly qualitative or uses unvalidated, study-specific, single items. Validated person-reported outcome measures (PROMs) have demonstrated the benefits of other diabetes technologies. The relative lack of research investigating open-source AID using PROMs has been considered a missed opportunity. OBJECTIVE This study aimed to examine the psychosocial outcomes of adults with type 1 diabetes using and not using open-source AID systems using a comprehensive set of validated PROMs in a real-world, multinational, cross-sectional study. METHODS Adults with type 1 diabetes completed 8 validated measures of general emotional well-being (5-item World Health Organization Well-Being Index), sleep quality (Pittsburgh Sleep Quality Index), diabetes-specific QoL (modified DAWN Impact of Diabetes Profile), diabetes-specific positive well-being (4-item subscale of the 28-item Well-Being Questionnaire), diabetes treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire), diabetes distress (20-item Problem Areas in Diabetes scale), fear of hypoglycemia (short form of the Hypoglycemia Fear Survey II), and a measure of the impact of COVID-19 on QoL. Independent groups 2-tailed t tests and Mann-Whitney U tests compared PROM scores between adults with type 1 diabetes using and not using open-source AID. An analysis of covariance was used to adjust for potentially confounding variables, including all sociodemographic and clinical characteristics that differed by use of open-source AID. RESULTS In total, 592 participants were eligible (attempting at least 1 questionnaire), including 451 using open-source AID (mean age 43, SD 13 years; n=189, 41.9% women) and 141 nonusers (mean age 40, SD 13 years; n=90, 63.8% women). Adults using open-source AID reported significantly better general emotional well-being and subjective sleep quality, as well as better diabetes-specific QoL, positive well-being, and treatment satisfaction. They also reported significantly less diabetes distress, fear of hypoglycemia, and perceived less impact of the COVID-19 pandemic on their QoL. All were medium-to-large effects (Cohen d=0.5-1.5). The differences between groups remained significant after adjusting for sociodemographic and clinical characteristics. CONCLUSIONS Adults with type 1 diabetes using open-source AID report significantly better psychosocial outcomes than those not using these systems, after adjusting for sociodemographic and clinical characteristics. Using validated, quantitative measures, this real-world study corroborates the beneficial psychosocial outcomes described previously in qualitative studies or using unvalidated study-specific items.
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Affiliation(s)
- Jasmine Schipp
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- Section for Health Services Research, Institute of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Christel Hendrieckx
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- School of Psychology, Deakin University, Burwood, Australia
| | - Katarina Braune
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- Dedoc Labs GmbH, Berlin, Germany
| | - Christine Knoll
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Shane O'Donnell
- School of Sociology & School of Medicine, University College Dublin, Dublin, Ireland
| | - Hanne Ballhausen
- Department of Paediatric Endocrinology and Diabetes, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- Dedoc Labs GmbH, Berlin, Germany
| | - Bryan Cleal
- Diabetes Management Research, Steno Diabetes Center Copenhagen, Copenhagen, Denmark
| | - Mandy Wäldchen
- School of Sociology & School of Medicine, University College Dublin, Dublin, Ireland
| | | | - Katarzyna A Gajewska
- Diabetes Ireland, Dublin, Ireland
- School of Public Health, University College Cork, Cork, Ireland
| | - Timothy C Skinner
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
| | - Jane Speight
- The Australian Centre for Behavioural Research in Diabetes, Carlton, Australia
- School of Psychology, Deakin University, Burwood, Australia
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Huhndt A, Chen Y, O’Donnell S, Cooper D, Ballhausen H, Gajewska KA, Froment T, Wäldchen M, Lewis DM, Raile K, Skinner TC, Braune K. Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey. FRONTIERS IN CLINICAL DIABETES AND HEALTHCARE 2022; 3:876511. [PMID: 36992765 PMCID: PMC10012142 DOI: 10.3389/fcdhc.2022.876511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 05/04/2022] [Indexed: 01/15/2023]
Abstract
BackgroundAs a treatment option for people living with diabetes, automated insulin delivery (AID) systems are becoming increasingly popular. The #WeAreNotWaiting community plays a crucial role in the provision and distribution of open-source AID technology. However, while a large percentage of children were early adopters of open-source AID, there are regional differences in adoption, which has prompted an investigation into the barriers perceived by caregivers of children with diabetes to creating open-source systems.MethodsThis is a retrospective, cross-sectional and multinational study conducted with caregivers of children and adolescents with diabetes, distributed across the online #WeAreNotWaiting online peer-support groups. Participants—specifically caregivers of children not using AID—responded to a web-based questionnaire concerning their perceived barriers to building and maintaining an open-source AID system.Results56 caregivers of children with diabetes, who were not using open-source AID at the time of data collection responded to the questionnaire. Respondents indicated that their major perceived barriers to building an open-source AID system were their limited technical skills (50%), a lack of support by medical professionals (39%), and therefore the concern with not being able to maintain an AID system (43%). However, barriers relating to confidence in open-source technologies/unapproved products and fear of digital technology taking control of diabetes were not perceived as significant enough to prevent non-users from initiating the use of an open-source AID system.ConclusionsThe results of this study elucidate some of the perceived barriers to uptake of open-source AID experienced by caregivers of children with diabetes. Reducing these barriers may improve the uptake of open-source AID technology for children and adolescents with diabetes. With the continuous development and wider dissemination of educational resources and guidance—for both aspiring users and their healthcare professionals—the adoption of open-source AID systems could be improved.
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Affiliation(s)
- Antonia Huhndt
- Department of Paediatric Endocrinology and Diabetes, Charité—Universitätsmedizin Berlin, Berlin, Germany
| | - Yanbing Chen
- School of Public Health, Physiotherapy & Sports Science, University College Dublin, Belfield, Ireland
| | - Shane O’Donnell
- School of Sociology, University College Dublin, Belfield, Ireland
| | - Drew Cooper
- Department of Paediatric Endocrinology and Diabetes, Charité—Universitätsmedizin Berlin, Berlin, Germany
| | - Hanne Ballhausen
- Department of Paediatric Endocrinology and Diabetes, Charité—Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- #dedoc° Diabetes Online Community, Dedoc Labs GmbH, Berlin, Germany
| | - Katarzyna A. Gajewska
- #dedoc° Diabetes Online Community, Dedoc Labs GmbH, Berlin, Germany
- Population Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Timothée Froment
- #dedoc° Diabetes Online Community, Dedoc Labs GmbH, Berlin, Germany
| | - Mandy Wäldchen
- School of Sociology, University College Dublin, Belfield, Ireland
| | | | - Klemens Raile
- Department of Paediatric Endocrinology and Diabetes, Charité—Universitätsmedizin Berlin, Berlin, Germany
| | - Timothy C. Skinner
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
- Australian Centre for Behavioural Research in Diabetes, Melbourne, Australia
- La Trobe University, Bendigo, Australia
| | - Katarina Braune
- Department of Paediatric Endocrinology and Diabetes, Charité—Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
- Institute of Medical Informatics, Charité—Universitätsmedizin Berlin, Berlin, Germany
- *Correspondence: Katarina Braune,
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Shahid A, Lewis DM. Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems. Nutrients 2022; 14:nu14091906. [PMID: 35565875 PMCID: PMC9101219 DOI: 10.3390/nu14091906] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/19/2022] [Accepted: 04/28/2022] [Indexed: 02/06/2023] Open
Abstract
Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucose-related outcomes of such user-driven innovation. Initial OpenAPS studies include retrospective studies assessing high-level outcomes of average glucose levels and HbA1c, without in-depth analysis of glucose variability (GV). The OpenAPS Data Commons dataset, donated to by open-source AID users with insulin-requiring diabetes, is the largest freely available diabetes-related dataset with over 46,070 days’ worth of data and over 10 million CGM data points, alongside insulin dosing and algorithmic decision data. This paper first reviews the development toward the latest open-source AID and the performance of clinically approved GV metrics. We evaluate the GV outcomes using large-scale data analytics for the n = 122 version of the OpenAPS Data Commons. We describe the data cleaning processes, methods for measuring GV, and the results of data analysis based on individual self-reported demographics. Furthermore, we highlight the lessons learned from the GV outcomes and the analysis of a rich and complex diabetes dataset and additional research questions that emerged from this work to guide future research. This paper affirms previous studies’ findings of the efficacy of open-source AID.
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Affiliation(s)
- Arsalan Shahid
- CeADAR—Ireland’s Centre for Applied AI, University College Dublin, D04 V2N9 Dublin, Ireland
- Correspondence:
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