Remote Glucose Monitoring in Camp Setting Reduces the Risk of Prolonged Nocturnal Hypoglycemia.
ABSTRACT Abstract Objective: This study tested the feasibility and effectiveness of remote continuous glucose monitoring (CGM) in a diabetes camp setting. Subjects and Methods: Twenty campers (7-21 years old) with type 1 diabetes were enrolled at each of three camp sessions lasting 5-6 days. On alternating nights, 10 campers were randomized to usual wear of a Dexcom (San Diego, CA) G4™ PLATINUM CGM system, and 10 were randomized to remote monitoring with the Dexcom G4 PLATINUM communicating with the Diabetes Assistant, a cell phone platform, to allow wireless transmission of CGM values. Up to 15 individual graphs and sensor values could be displayed on a single remote monitor or portable tablet. An alarm was triggered for values <70 mg/dL, and treatment was given for meter-confirmed hypoglycemia. The primary end point was to decrease the duration of hypoglycemic episodes <50 mg/dL. Results: There were 320 nights of CGM data and 197 hypoglycemic events. Of the remote monitoring alarms, 79% were true (meter reading of <70 mg/dL). With remote monitoring, 100% of alarms were responded to, whereas without remote monitoring only 54% of alarms were responded to. The median duration of hypoglycemic events <70 mg/dL was 35 min without remote monitoring and 30 min with remote monitoring (P=0.078). Remote monitoring significantly decreased prolonged hypoglycemic events, eliminating all events <50 mg/dL lasting longer than 30 min as well as all events <70 mg/dL lasting more than 2 h. Conclusions: Remote monitoring is feasible at diabetes camps and effective in reducing the risk of prolonged nocturnal hypoglycemia. This technology will facilitate forthcoming studies to evaluate the efficacy of automated closed-loop systems in the camp setting.
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ABSTRACT: It is assumed that MQ are central to glucose sensor bio-fouling and therefore have a major negative impact on continuous glucose monitoring (CGM) performance in vivo. However to our knowledge there is no data in the literature to directly support or refute this assumption. Since glucose and oxygen (O2) are key to glucose sensor function in vivo, understanding and controlling glucose and O2 metabolic activity of MQ is likely key to successful glucose sensor performance. We hypothesized that the accumulation of MQ at the glucose sensor-tissue interface will act as "Cell Based Metabolic Barriers" (CBMB) to glucose diffusing from the interstitial tissue compartment to the implanted glucose sensor and as such creating an artificially low sensor output, thereby compromising sensor function and CGM. Our studies demonstrated that 1) direct injections of MQ at in vivo sensor implantation sites dramatically decreased sensor output (measured in nA), 2) addition of MQ to glucose sensors in vitro resulted in a rapid and dramatic fall in sensor output and 3) lymphocytes did not affect sensor function in vitro or in vivo. These data support our hypothesis that MQ can act as metabolic barriers to glucose and O2 diffusion in vivo and in vitro.Biomaterials 01/2014; 35(10). DOI:10.1016/j.biomaterials.2014.01.001 · 8.31 Impact Factor
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ABSTRACT: To determine the safety and efficacy of an automated unified safety system (USS) in providing overnight closed-loop (OCL) control in children and adolescents with type 1 diabetes attending diabetes summer camps.RESEARCH DESIGN AND METHODS: The Diabetes Assistant (DIAS) USS used the Dexcom G4P glucose sensor (Dexcom) and t:slim insulin pump (Tandem Diabetes Care). An initial inpatient study was completed for 12 participants to evaluate safety. For the main camp study, 20 participants with type 1 diabetes were randomized to either OCL or sensor-augmented therapy (control conditions) per night over the course of a 5- to 6-day diabetes camp.RESULTS: Subjects completed 54 OCL nights and 52 control nights. On an intention-to-treat basis, with glucose data analyzed regardless of system status, the median percent time in range, from 70-150 mg/dL, was 62% (29, 87) for OCL nights versus 55% (25, 80) for sensor-augmented pump therapy (P = 0.233). A per-protocol analysis allowed for assessment of algorithm performance. The median percent time in range, from 70-150 mg/dL, was 73% (50, 89) for OCL nights (n = 41) versus 52% (24, 83) for control conditions (n = 39) (P = 0.037). There was less time spent in the hypoglycemic range <50, <60, and <70 mg/dL during OCL compared with the control period (P = 0.019, P = 0.009, and P = 0.023, respectively).CONCLUSIONS: The DIAS USS algorithm is effective in improving time spent in range as well as reducing nocturnal hypoglycemia during the overnight period in children and adolescents with type 1 diabetes in a diabetes camp setting.Diabetes Care 05/2014; 37(8). DOI:10.2337/dc14-0147 · 8.57 Impact Factor
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ABSTRACT: Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management. We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers. We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users. In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%). There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.Journal of Medical Internet Research 02/2015; 17(2):e52. DOI:10.2196/jmir.3951 · 4.67 Impact Factor