The use of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems has gained wide acceptance in diabetes care. These devices have been demonstrated to be ...clinically valuable, improving glycemic control and reducing risks of hypoglycemia in ambulatory patients with type 1 diabetes and type 2 diabetes. Approximately 30-40% of patients with type 1 diabetes and an increasing number of insulin-requiring patients with type 2 diabetes are using pump and sensor technology. As the popularity of these devices increases, it becomes very likely that hospital health care providers will face the need to manage the inpatient care of patients under insulin pump therapy and CGM. The American Diabetes Association advocates allowing patients who are physically and mentally able to continue to use their pumps when hospitalized. Health care institutions must have clear policies and procedures to allow the patient to continue to receive CSII treatment to maximize safety and to comply with existing regulations related to self-management of medication. Randomized controlled trials are needed to determine whether CSII therapy and CGM systems in the hospital are associated with improved clinical outcomes compared with intermittent monitoring and conventional insulin treatment or with a favorable cost-benefit ratio.
•RCTs have shown that CGM can reduce A1c and time spent in hypoglycemia.•CGM can help clarify A1c readings that do not match corresponding SMBG records. •CGM provides trend data about the direction ...and rate of changing glucose levels.•Patient education and increased sensor wear time increase the effectiveness of CGM. •Data confidentiality and integrity necessitate sound cybersecurity practices.
Continuous glucose monitoring (CGM) is an increasingly adopted technology for insulin-requiring patients that provides insights into glycemic fluctuations. CGM can assist patients in managing their diabetes with lifestyle and medication adjustments. This article provides an overview of the technical and clinical features of CGM based on a review of articles in PubMed on CGM from 1999 through January 31, 2017. A detailed description is presented of three professional (retrospective), three personal (real-time) continuous glucose monitors, and three sensor integrated pumps (consisting of a sensor and pump that communicate with each other to determine an optimal insulin dose and adjust the delivery of insulin) that are currently available in United States. We have reviewed outpatient CGM outcomes, focusing on hemoglobin A1c (A1C), hypoglycemia, and quality of life. Issues affecting accuracy, detection of glycemic variability, strategies for optimal use, as well as cybersecurity and future directions for sensor design and use are discussed. In conclusion, CGM is an important tool for monitoring diabetes that has been shown to improve outcomes in patients with type 1 diabetes mellitus. Given currently available data and technological developments, we believe that with appropriate patient education, CGM can also be considered for other patient populations.
Introduction:
Diabetes has emerged as an important risk factor for severe illness and death from COVID-19. There is a paucity of information on glycemic control among hospitalized COVID-19 patients ...with diabetes and acute hyperglycemia.
Methods:
This retrospective observational study of laboratory-confirmed COVID-19 adults evaluated glycemic and clinical outcomes in patients with and without diabetes and/or acutely uncontrolled hyperglycemia hospitalized March 1 to April 6, 2020. Diabetes was defined as A1C ≥6.5%. Uncontrolled hyperglycemia was defined as ≥2 blood glucoses (BGs) > 180 mg/dL within any 24-hour period. Data were abstracted from Glytec’s data warehouse.
Results:
Among 1122 patients in 88 U.S. hospitals, 451 patients with diabetes and/or uncontrolled hyperglycemia spent 37.8% of patient days having a mean BG > 180 mg/dL. Among 570 patients who died or were discharged, the mortality rate was 28.8% in 184 diabetes and/or uncontrolled hyperglycemia patients, compared with 6.2% of 386 patients without diabetes or hyperglycemia (P < .001). Among the 184 patients with diabetes and/or hyperglycemia who died or were discharged, 40 of 96 uncontrolled hyperglycemia patients (41.7%) died compared with 13 of 88 patients with diabetes (14.8%, P < .001). Among 493 discharged survivors, median length of stay (LOS) was longer in 184 patients with diabetes and/or uncontrolled hyperglycemia compared with 386 patients without diabetes or hyperglycemia (5.7 vs 4.3 days, P < .001).
Conclusion:
Among hospitalized patients with COVID-19, diabetes and/or uncontrolled hyperglycemia occurred frequently. These COVID-19 patients with diabetes and/or uncontrolled hyperglycemia had a longer LOS and markedly higher mortality than patients without diabetes or uncontrolled hyperglycemia. Patients with uncontrolled hyperglycemia had a particularly high mortality rate. We recommend health systems which ensure that inpatient hyperglycemia is safely and effectively treated.
An assessment of the medical literature on continuous glucose monitoring available through the end of 2004 is presented. It discusses continuous glucose monitoring in terms of its purposes, ...technologies, target populations, accuracy, clinical indications, outcomes, and problems. In conclusion, continuous glucose monitoring offers advantages over intermittent glucose monitoring when glycemic patterns are poorly understood.
FDA has launched a Real World Evidence (RWE) Program for using real-world evidence (RWE) to help support new indications for already approved drugs or biologics and postapproval studies. The plan ...also includes stakeholder engagement efforts, demonstration projects, leadership activities, and development of guidance documents to assist developers interested in using real-world data (RWD) to develop RWE to support FDA regulatory decisions. This plan was mandated by the Cures Act passed in 2016. Over the 24-month period from passage of the law until FDA officially announced their program, FDA has gone to considerable efforts to educate the public about the benefits of RWE and encourage researchers to consider situations where RWE trials can generate useful information. Through a variety of stakeholder engagement projects, including publication of articles in medical journals, participation in public meetings, and development of initiatives, FDA has put more effort into preparing the medical community for its new emphasis on RWE than any other new policy that I can recall.
Real-world evidence (RWE) is the clinical evidence about benefits or risks of medical products derived from analyzing real world data (RWD), which are data collected through routine clinical ...practice. This article discusses the advantages and disadvantages of RWE studies, how these studies differ from randomized controlled trials (RCTs), how to overcome barriers to current skepticism about RWE, how FDA is using RWE, how to improve the quality of RWE, and finally the future of RWE trials.
The Internet of Things (IoT) is generating an immense volume of data. With cloud computing, medical sensor and actuator data can be stored and analyzed remotely by distributed servers. The results ...can then be delivered via the Internet. The number of devices in IoT includes such wireless diabetes devices as blood glucose monitors, continuous glucose monitors, insulin pens, insulin pumps, and closed-loop systems. The cloud model for data storage and analysis is increasingly unable to process the data avalanche, and processing is being pushed out to the edge of the network closer to where the data-generating devices are. Fog computing and edge computing are two architectures for data handling that can offload data from the cloud, process it nearby the patient, and transmit information machine-to-machine or machine-to-human in milliseconds or seconds. Sensor data can be processed near the sensing and actuating devices with fog computing (with local nodes) and with edge computing (within the sensing devices). Compared to cloud computing, fog computing and edge computing offer five advantages: (1) greater data transmission speed, (2) less dependence on limited bandwidths, (3) greater privacy and security, (4) greater control over data generated in foreign countries where laws may limit use or permit unwanted governmental access, and (5) lower costs because more sensor-derived data are used locally and less data are transmitted remotely. Connected diabetes devices almost all use fog computing or edge computing because diabetes patients require a very rapid response to sensor input and cannot tolerate delays for cloud computing.
Behavioral theory is an important factor for designing digital health tools for diabetes to increase adherence to treatment. Many digital health products have not incorporated this method for ...achieving behavior change. This oversight might explain the disappointing outcomes of many products in this class. Four theories reported to be capable of enhancing the performance of digital health tools for diabetes include (1) Integrate, Design, Assess, and Share (IDEAS); (2) the Behaviour Change Wheel; (3) the Information-Motivation-Behavioral skills (IMB) model; and (4) gamification. Well-designed digital health tools are most likely to be effective if they are deployed in a patient-centered care setting established upon principles of sound behavioral theory. Behavioral theory can increase the effectiveness of digital tools and promote a receptive environment for their use.
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