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Zheng Z, Zhu R, Peng I, Xu Z, Jiang Y. Wearable and implantable biosensors: mechanisms and applications in closed-loop therapeutic systems. J Mater Chem B 2024; 12:8577-8604. [PMID: 39138981 DOI: 10.1039/d4tb00782d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
This review article examines the current state of wearable and implantable biosensors, offering an overview of their biosensing mechanisms and applications. We also delve into integrating these biosensors with therapeutic systems, discussing their operational principles and incorporation into closed-loop devices. Biosensing strategies are broadly categorized into chemical sensing for biomarker detection, physical sensing for monitoring physiological conditions such as pressure and temperature, and electrophysiological sensing for capturing bioelectrical activities. The discussion extends to recent developments in drug delivery and electrical stimulation devices to highlight their significant role in closed-loop therapy. By integrating with therapeutic devices, biosensors enable the modulation of treatment regimens based on real-time physiological data. This capability enhances the patient-specificity of medical interventions, an essential aspect of personalized healthcare. Recent innovations in integrating biosensors and therapeutic devices have led to the introduction of closed-loop wearable and implantable systems capable of achieving previously unattainable therapeutic outcomes. These technologies represent a significant leap towards dynamic, adaptive therapies that respond in real-time to patients' physiological states, offering a level of accuracy and effectiveness that is particularly beneficial for managing chronic conditions. This review also addresses the challenges associated with biosensor technologies. We also explore the prospects of these technologies to address their potential to transform disease management with more targeted and personalized treatment solutions.
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Affiliation(s)
- Zeyuan Zheng
- Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Runjin Zhu
- Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Ian Peng
- Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Zitong Xu
- Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - Yuanwen Jiang
- Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
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Landgraf R, Aberle J, Birkenfeld AL, Gallwitz B, Kellerer M, Klein HH, Müller-Wieland D, Nauck MA, Wiesner T, Siegel E. Therapy of Type 2 Diabetes. Exp Clin Endocrinol Diabetes 2024; 132:340-388. [PMID: 38599610 DOI: 10.1055/a-2166-6755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Affiliation(s)
| | - Jens Aberle
- Division of Endocrinology and Diabetology, University Obesity Centre Hamburg, University Hospital Hamburg-Eppendorf, Germany
| | | | - Baptist Gallwitz
- Department of Internal Medicine IV, Diabetology, Endocrinology, Nephrology, University Hospital Tübingen, Germany
| | - Monika Kellerer
- Department of Internal Medicine I, Marienhospital, Stuttgart, Germany
| | - Harald H Klein
- MVZ for Diagnostics and Therapy Bochum, Bergstraße 26, 44791 Bochum, Germany
| | - Dirk Müller-Wieland
- Department of Internal Medicine I, Aachen University Hospital RWTH, Aachen, Germany
| | - Michael A Nauck
- Diabetology, Endocrinology and Metabolism Section, Department of Internal Medicine I, St. Josef Hospital, Ruhr University, Bochum, Germany
| | | | - Erhard Siegel
- Department of Internal Medicine - Gastroenterology, Diabetology/Endocrinology and Nutritional Medicine, St. Josefkrankenhaus Heidelberg GmbH, Heidelberg, Germany
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Krnic N, Sesa V, Mrzljak A, Berkovic MC. Are treatment options used for adult-onset type 2 diabetes mellitus (equally) available and effective for children and adolescents? World J Diabetes 2024; 15:623-628. [PMID: 38680687 PMCID: PMC11045425 DOI: 10.4239/wjd.v15.i4.623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/29/2024] [Accepted: 03/06/2024] [Indexed: 04/11/2024] Open
Abstract
Youth-onset type 2 diabetes mellitus (T2DM), influenced by an increase in obesity, is a rising problem worldwide. Pathophysiological mechanisms of this early-onset T2DM include both peripheral and hepatic insulin resistance, along with increased hepatic fasting glucose production accompanied by inadequate first and second-phase insulin secretion. Moreover, the incretin effect is reduced. The initial presentation of type 2 diabetes can be dramatic and symptoms may overlap with those of type 1 diabetes mellitus. Therefore, immediate therapy should address hyperglycemia and associated metabolic derangements irrespective of ultimate diabetes type, while further therapy adjustments are prone to patients' phenotype. New agents with proven glycemic and beyond glycemia benefits, such as Glucagon-like polypeptide 1 receptor agonists and Sodium-glucose cotransporter-2 inhibitors, used in the adult population of T2DM patients, might become increasingly important in the treatment armamentarium. Moreover, metabolic surgery is an option for markedly obese (body mass index > 35 kg/m2) children and adolescents suffering from T2DM who have uncontrolled glycemia and/or serious comorbidities when lifestyle and pharmacologic interventions fail. In this mini-review, we will discuss the potential of treatment options considering new data available from randomized control trials, including individuals with adult-onset type diabetes mellitus.
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Affiliation(s)
- Nevena Krnic
- Clinics for Pediatrics, University Hospital Center Zagreb, Zagreb 10000, Croatia
| | - Vibor Sesa
- Department of Gastroenterology and Hepatology, University Hospital Centre Zagreb, Zagreb 10000, Croatia
| | - Anna Mrzljak
- Department of Gastroenterology and Hepatology, University Hospital Centre Zagreb, Zagreb 10000, Croatia
- University of Zagreb School of Medicine, Zagreb 10000, Croatia
| | - Maja Cigrovski Berkovic
- Department for Sport and Exercise Medicine, University of Zagreb Faculty of Kinesiology, Zagreb 10000, Croatia
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Nimri R, Phillip M, Clements MA, Kovatchev B. Closed-Loop Control, Artificial Intelligence-Based Decision-Support Systems, and Data Science. Diabetes Technol Ther 2024; 26:S68-S89. [PMID: 38441444 DOI: 10.1089/dia.2024.2505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Affiliation(s)
- Revital Nimri
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Moshe Phillip
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Mark A Clements
- Division of Pediatric Endocrinology, Children's Mercy Hospitals and Clinics, Kansas City, MO, USA
| | - Boris Kovatchev
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA, USA
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Amer BE, Yaqout YE, Abozaid AM, Afifi E, Aboelkhier MM. Does fully closed-loop automated insulin delivery improve glycaemic control in patients with type 2 diabetes? A meta-analysis of randomized controlled trials. Diabet Med 2024; 41:e15196. [PMID: 37567739 DOI: 10.1111/dme.15196] [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] [Received: 05/31/2023] [Revised: 07/22/2023] [Accepted: 08/09/2023] [Indexed: 08/13/2023]
Abstract
AIMS This meta-analysis investigated the efficacy and safety of fully closed-loop automated insulin delivery (AID) in patients with type 2 diabetes. MATERIALS AND METHODS We systemically searched PubMed, Scopus, Web of Science, and Cochrane Central from inception until April 26, 2023. We included randomized controlled trials (RCTs) comparing fully closed-loop AID versus conventional insulin therapy. The outcomes were pooled as the mean difference (MD) and risk ratio with 95% confidence interval (CI) in the random effect model. Our primary outcome was the proportion of time in the target glucose range (5.6-10 mmol/L, 3.9-10 mmol/L, or 3.9-8 mmol/L, depending on the study). Key secondary outcomes included the proportion of time spent in hyperglycaemia or hypoglycaemia. RESULTS We included seven RCTs (three crossover and four parallel design), compromising 390 patients. Our analysis showed that compared to the control group, fully closed-loop AID increased the proportion of time spent within the target glucose range by additional 337 min per 24 h (MD = 23.39%, 95% CI [16.64%, 30.14%], p < 0.01), additional 108 min overnight (MD = 22.40%, 95% CI [12.88%, 31.91%], p < 0.01), and additional 258 min during the daytime period (MD = 26.85%, 95% CI [21.06%, 32.63%], p < 0.01). Compared to the control group, the overall time in hyperglycaemia was shortened by 326 min per 24 h (MD = -22.67%, 95% CI [-30.87%, -14.46%], p < 0.01). There was no significant difference between the two groups in terms of overall, overnight, and daytime periods spent in hypoglycaemia. CONCLUSIONS Our meta-analysis suggests that fully closed-loop AID may improve glycaemic control in patients with type 2 diabetes, particularly for those with more challenging diabetes management. Further research is required to establish the feasibility of implementing these systems in clinical practice. [Correction added on 26 August 2023 after first online publication: Under Results, the first sentence "We included seven RCTs (three crossover and one parallel designs)" has been changed to "We included seven RCTs (three crossover and four parallel designs)".].
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Affiliation(s)
- Basma Ehab Amer
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Benha University, Benha, Egypt
| | - Yasmeen Essam Yaqout
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Ahmed Mohamed Abozaid
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Tanta University, Tanta, Egypt
| | - Eslam Afifi
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Benha University, Benha, Egypt
| | - Menna M Aboelkhier
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Science, Cairo University, Cairo, Egypt
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Hitt TA, Hannon TS, Magge SN. Approach to the Patient: Youth-Onset Type 2 Diabetes. J Clin Endocrinol Metab 2023; 109:245-255. [PMID: 37584397 DOI: 10.1210/clinem/dgad482] [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] [Received: 05/30/2023] [Revised: 08/10/2023] [Accepted: 08/11/2023] [Indexed: 08/17/2023]
Abstract
Youth-onset type 2 diabetes is a growing epidemic with a rising incidence worldwide. Although the pathogenesis and diagnosis of youth-onset type 2 diabetes are similar to adult-onset type 2 diabetes, youth-onset type 2 diabetes is unique, with greater insulin resistance, insulin hypersecretion, and faster progression of pancreatic beta cell function decline. Individuals with youth-onset type 2 diabetes also develop complications at higher rates within short periods of time compared to adults with type 2 diabetes or youth with type 1 diabetes. The highest prevalence and incidence of youth-onset type 2 diabetes in the United States is among youth from minoritized racial and ethnic groups. Risk factors include obesity, family history of type 2 diabetes, comorbid conditions and use of medications associated with insulin resistance and rapid weight gain, socioeconomic and environmental stressors, and birth history of small-for-gestational-age or pregnancy associated with gestational or pregestational diabetes. Patients with youth-onset type 2 diabetes should be treated using a multidisciplinary model with frequent clinic visits and emphasis on addressing of social and psychological barriers to care and glycemic control, as well as close monitoring for comorbidities and complications. Intensive health behavior therapy is an important component of treatment, in addition to medical management, both of which should be initiated at the diagnosis of type 2 diabetes. There are limited but growing pharmacologic treatment options, including metformin, insulin, glucagon-like peptide 1 receptor agonists, and sodium-glucose cotransporter 2 inhibitors. Although long-term outcomes are not fully known, metabolic/bariatric surgery in youth with type 2 diabetes has led to improved cardiometabolic outcomes.
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Affiliation(s)
- Talia A Hitt
- Division of Endocrinology and Diabetes, Department of Pediatrics, Johns Hopkins University School of Medicine, 200 N. Wolfe Street, Room 3114, Baltimore, MD 21287, USA
| | - Tamara S Hannon
- Division of Endocrinology and Diabetology, Department of Pediatrics, Indiana University School of Medicine, 705 Riley Hospital Drive, Indianapolis, IN 46202, USA
| | - Sheela N Magge
- Division of Endocrinology and Diabetes, Department of Pediatrics, Johns Hopkins University School of Medicine, 200 N. Wolfe Street, Room 3114, Baltimore, MD 21287, USA
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Hughes MS, Addala A, Buckingham B. Digital Technology for Diabetes. N Engl J Med 2023; 389:2076-2086. [PMID: 38048189 DOI: 10.1056/nejmra2215899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/06/2023]
Affiliation(s)
- Michael S Hughes
- From the Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine (M.S.H.), and the Division of Pediatric Endocrinology, Department of Pediatrics (A.A., B.B), Stanford University, Stanford, CA
| | - Ananta Addala
- From the Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine (M.S.H.), and the Division of Pediatric Endocrinology, Department of Pediatrics (A.A., B.B), Stanford University, Stanford, CA
| | - Bruce Buckingham
- From the Division of Endocrinology, Gerontology, and Metabolism, Department of Medicine (M.S.H.), and the Division of Pediatric Endocrinology, Department of Pediatrics (A.A., B.B), Stanford University, Stanford, CA
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Heinemann L. Automated Insulin Delivery System and People With Type 2 Diabetes: A Topic With Many Facets. J Diabetes Sci Technol 2023:19322968231204625. [PMID: 37807907 DOI: 10.1177/19322968231204625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Optimizing glucose control is of interest also for patients with type 2 diabetes (T2D). While systems for automated insulin delivery are widely used for patients with type 1 diabetes, as documented by many publications, this is not the case with T2D. Because of the number of such patients, this will change drastically in the next years. Manufacturers can transfer many learnings from type 1 to type 2; however, specific clinical aspects have to be considered. This commentary will discuss these aspects and some of the current activities. Future automated insulin delivery (AID) systems will take data from multisensor systems into account to individualize the AID algorithm, supported by artificial intelligence. There is a high need to document the benefits of AID systems in this patient group.
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Affiliation(s)
- Lutz Heinemann
- Science Consulting in Diabetes GmbH, Düsseldorf, Germany
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