ReviewDiabetes technology & therapeutics2016
Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects.
Review in Diabetes technology & therapeutics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed, 94 citations in OpenAlex.
- Optimizing Hybrid Closed-Loop Therapy in Adolescents and Emerging Adults Using the MiniMed 670G System.Diabetes care · 2018Trial
- Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial.Diabetes care · 2017Trial
- Trial
- Sensor Life and Overnight Closed Loop: A Randomized Clinical Trial.Journal of diabetes science and technology · 2017Trial
- Current Technologies for Managing Type 1 Diabetes Mellitus and Their Impact on Quality of Life-A Narrative Review.Life (Basel, Switzerland) · 2023Review
- Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes.Frontiers in endocrinology · 2022Article
- Intelligent automated drug administration and therapy: future of healthcare.Drug delivery and translational research · 2021Review
- The Closed-Loop System Improved the Control of a Pregnant Patient with Type 1 Diabetes Mellitus.Case reports in endocrinology · 2021Article
- Health Care Provider Knowledge and Perceptions of FDA-Approved and Do-It-Yourself Automated Insulin Delivery.Journal of diabetes science and technology · 2020Observational
- Novel algebraic meal disturbance estimation based adaptive robust control design for blood glucose regulation in type 1 diabetes patients.IET systems biology · 2020Article
- The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes.Journal of diabetes science and technology · 2020Article
- Severe Hypoglycemia: Is It Still a Threat for Children and Adolescents With Type 1 Diabetes?Frontiers in endocrinology · 2020Review
- A Clinical Guide to Advanced Diabetes Devices and Closed-Loop Systems Using the CARES Paradigm.Diabetes technology & therapeutics · 2019Article
- Impact of CGM on the Management of Hypoglycemia Problems: Overview and Secondary Analysis of the HypoDE Study.Journal of diabetes science and technology · 2019Review
- Article
- Article
- Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications.Journal of diabetes science and technology · 2018Article
- Measurement Performance of Two Continuous Tissue Glucose Monitoring Systems Intended for Replacement of Blood Glucose Monitoring.Diabetes technology & therapeutics · 2018Article
- Ongoing Debate About Models for Artificial Pancreas Systems and In Silico Studies.Diabetes technology & therapeutics · 2018Article
- Estimation of parameters for plasma glucose regulation in type-2 diabetics in presence of meal.IET systems biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of accurate and easy-to-use continuous glucose monitoring (CGM) improved diabetes treatment by providing additional temporal information on glycemia and glucose trends to patient and physician. Although CGM enables users to lower their average glucose level without an increased incidence of hypoglycemia, this comes at the price of additional patient effort. Automation of insulin administration, also known as closed-loop (CL) or artificial pancreas treatment, has the promise to reduce patient effort and improve glycemic control. CGM data serve as the conditional input for insulin automation devices. The first commercial product for partial automation of insulin administration used insulin delivery shutoff at a predefined glucose level. These systems showed a reduction in hypoglycemia. Insulin-only CL devices show increased time spent in euglycemia and a reduction of hypo- and hyperglycemia. Improved glycemic control, coinciding with a minor decrease in hemoglobin A1c level, was confirmed in recent long-term home studies investigating these devices, paving the way for pivotal studies for commercialization of the artificial pancreas. Although the first results from dual-hormone CL systems are promising, because of increased cost of consumables of these systems, long-term head-to-head studies will have to prove superiority over insulin-only approaches. Now CL glucose control for daily use might finally become reality. Improved continuous glucose sensing technology, miniaturization of electrical devices, and development of algorithms were key in making this possible. Clinical adoption challenges, including device usability and reimbursement, need to be addressed. Time will tell for which patient groups CL systems will be reimbursed and whether these devices can deliver the promise that they hold.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.