Journal of Diabetes Science and Technology最新文献

The recently CE-marked continuous real-time glucose monitoring (rtCGM) solution Accu-Chek® (AC) SmartGuide Solution was developed to enable people with diabetes mellitus (DM) to proactively control their glucose levels using predictive technologies. The comprehensive solution consists of three components that harmonize well with each other. The CGM device is composed of a sensor applicator and a glucose sensor patch whose data are transferred to the connected smartphone by Bluetooth® Low Energy. The user interface of the CGM solution is powered by the AC SmartGuide app delivering current and past glucose metrics, and the AC SmartGuide Predict app providing a glucose prediction suite enabled by artificial intelligence (AI). This article describes the innovative CGM solution.

Background: Despite the efficacy of diabetes prevention programs, only an estimated 5% of people with pre-diabetes actually participate. Mobile health (mHealth) holds promise to engage patients with pre-diabetes into lifestyle modification programs by decreasing the referral burden, centralizing remote enrollment, removing the physical requirement of a brick-and-mortar location, lowering operating costs through automation, and reducing time and transportation barriers.

Methods: Non-randomized implementation study enrolling patients with pre-diabetes from a large health care organization. Patients were exposed to a text message-based program combining live human coaching guidance and support with automated scheduled, interactive, data-driven, and on-demand messages. The primary analysis examined predicted weight outcomes at 6 and 12 months. Secondary outcomes included predicted changes in HbA1c and minutes of exercise at 6 and 12 months.

Results: Of the 163 participants included in the primary analysis, participants had a mean predicted weight loss of 5.5% at six months (P < .001) and of 4.3% at 12 months (P < .001). We observed a decrease in predicted HbA1c from 6.1 at baseline to 5.8 at 6 and 12 months (P < .001). Activity minutes were statistically similar from a baseline of 155.5 minutes to 146.0 minutes (P = .567) and 142.1 minutes (P = .522) at 6 and 12 months, respectively, for the overall cohort.

Conclusions: In this real-world implementation of the myAgileLife Diabetes Prevention Program among patients with pre-diabetes, we observed significant decreases in weight and HbA1c at 6 and 12 months. mHealth may represent an effective and easily scalable potential solution to deliver impactful diabetes prevention curricula to large numbers of patients.

Background: For diabetes mellitus treatment plans, the consistency and quality of insulin drug products are crucial for patient well-being. Because biologic drugs, such as insulin, are complex heterogeneous products, the methods for drug product evaluation should be carefully validated for use. As such, these criteria are rigorously evaluated and monitored by national authorities. Consequently, reports that describe significantly lower insulin content than their label claims are a concern. This issue was raised by a past publication analyzing insulin drug products available in Canada, and, as a result, consumers and major patient organizations have requested clarification.

Methods: To address these concerns, this study independently analyzed insulin drug products purchased from local Canadian pharmacies-including human insulin, insulin analogs, and porcine insulin-by compendial and noncompendial reversed-phase high-performance liquid chromatography (RP-HPLC) methods.

Results: We demonstrated the importance of using methods fit for purpose when assessing insulin quality. In a preliminary screen, the expected insulin peak was seen in all products except two insulin analogs-insulin detemir and insulin degludec. Further investigation showed that this was not caused by low insulin content but insufficient solvent conditions, which demonstrated the necessity for methods to be adequately validated for product-specific use. When drug products were appropriately assessed for content using the validated type-specific compendial RP-HPLC methods for insulin quantitation, values agreed with the label claim content.

Conclusions: Because insulin drug products are used daily by over a million Canadians, it is important that researchers and journals present data using methods fit for purpose and that readers evaluate such reports critically.

Background: To evaluate the glycemia risk index (GRI) as a new glucometry in pediatric and adult populations with type 1 diabetes (T1D) in clinical practice.

Methods: A cross-sectional study of 202 patients with T1D receiving intensive treatment with insulin (25.2% continuous subcutaneous insulin infusion [CSII]) and intermittent scanning (flash) glucose monitoring (isCGM). Clinical and glucometric isCGM data were collected, as well as the component of hypoglycemia (CHypo) and component of hyperglycemia (CHyper) of the GRI.

Results: A total of 202 patients (53% males and 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution were evaluated.Adult patients (>19 years) presented higher glycated hemoglobin (HbA1c) (7.4 ± 1.1 vs 6.7 ± 0.6%; P < .01) and lower time in range (TIR) (55.4 ± 17.5 vs 66.5 ± 13.1%; P < .01) values than the pediatric population, with lower coefficient of variation (CV) (38.6 ± 7.2 vs 42.4 ± 8.9%; P < .05). The GRI was significantly lower in pediatric patients (48.0 ± 22.2 vs 56.8 ± 23.4; P < .05) associated with higher CHypo (7.1 ± 5.1 vs 5.0 ± 4.5; P < .01) and lower CHyper (16.8 ± 9.8 vs 26.5 ± 15.1; P < .01) than in adults.When analyzing treatment with CSII compared with multiple doses of insulin (MDI), a nonsignificant trend to a lower GRI was observed in CSII (51.0 ± 15.3 vs 55.0 ± 25.4; P= .162), with higher levels of CHypo (6.5 ± 4.1 vs 5.4 ± 5.0; P < .01) and lower CHyper (19.6 ± 10.6 vs 24.6 ± 15.2; P < .05) compared with MDI.

Conclusions: In pediatric patients and in those with CSII treatment, despite a better control by classical and GRI parameters, higher overall CHypo was observed than in adults and MDI, respectively. The present study supports the usefulness of the GRI as a new glucometric parameter to evaluate the global risk of hypoglycemia-hyperglycemia in both pediatric and adult patients with T1D.

Background: The objective of this work is to develop a highly miniaturized, low-power, biosensing platform for continuous glucose monitoring (CGM). This platform is based on an application-specific integrated circuit (ASIC) chip that interfaces with an amperometric glucose-sensing element. To reduce both size and power requirements, this custom ASIC chip was implemented using 65-nm complementary metal oxide semiconductor (CMOS) technology node. Interfacing this chip to a frequency-counting microprocessor with storage capabilities, a miniaturized transcutaneous CGM system can be constructed for small laboratory animals, with long battery life.

Method: A 0.45 mm × 1.12 mm custom ASIC chip was first designed and implemented using the Taiwan Semiconductor Manufacturing Company (TSMC) 65-nm CMOS technology node. This ASIC chip was then interfaced with a multi-layer amperometric glucose-sensing element and a frequency-counting microprocessor with storage capabilities. Variation in glucose levels generates a linear increase in frequency response of this ASIC chip. In vivo experiments were conducted in healthy Sprague Dawley rats.

Results: This highly miniaturized, 65-nm custom ASIC chip has an overall power consumption of circa 36 µW. In vitro testing shows that this ASIC chip produces a linear (R² = 99.5) frequency response to varying glucose levels (from 2 to 25 mM), with a sensitivity of 1278 Hz/mM. In vivo testing in unrestrained healthy rats demonstrated long-term CGM (six days/per charge) with rapid glucose response to glycemic variations induced by isoflurane anesthesia and tail vein injection.

Conclusions: The miniature footprint of the biosensor platform, together with its low-power consumption, renders this CMOS ASIC chip a versatile platform for a variety of highly miniaturized devices, intended to improve the quality of life of patients with type 1 and type 2 diabetes.

Background and objectives: Incidence of type 1 diabetes mellitus (T1DM) is increasing, and these patients often have poor glycemic control. Electronic dashboards summating patient data have been shown to improve patient outcomes in other conditions. In addition, educating patients on T1DM has shown to improve glycated hemoglobin (A1C) levels. We hypothesized that using data from the electronic dashboard to monitor defined diabetes management activities to implement population-based interventions would improve patient outcomes.

Methods: Inclusion criteria included patients aged 0 to 18 years at Phoenix Children's Hospital with T1DM. Patient data were collected via the electronic dashboard, and both diabetes management activities (A1C, patient admissions, and visits to the emergency department) and patient outcomes (patient education, appointment compliance, follow-up after hospital admission) were analyzed.

Results: This study revealed that following implementation of the electronic dashboard, the percentage of patients receiving appropriate education increased from 48% to 80% (Z-score = 23.55, P < .0001), the percentage of patients attending the appropriate number of appointments increased from 50% to 68.2%, and the percentage of patients receiving follow-up care within 40 days after a hospital admission increased from 43% to 70%. The median A1C level decreased from 9.1% to 8.2% (Z-score = -6.74, P < .0001), and patient admissions and visits to the emergency department decreased by 20%.

Conclusions: This study shows, with the implementation of an electronic dashboard, we were able to improve outcomes for our pediatric patients with T1DM. This tool can be used at other institutions to improve care and outcomes for pediatric patients with T1DM and other chronic conditions.

Background: The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitoring (BGM). We explored heterogeneous treatment effects of CGM on hypoglycemia by formulating a data-driven decision rule that selects an intervention (ie, CGM vs BGM) to minimize percentage of time <70 mg/dL for each individual WISDM participant.

Method: The precision medicine analyses used data from participants with complete data (n = 194 older adults, including those who received CGM [n = 100] and BGM [n = 94] in the trial). Policy tree and decision list algorithms were fit with 14 baseline demographic, clinical, and laboratory measures. The primary outcome was CGM-measured percentage of time spent in hypoglycemic range (<70 mg/dL), and the decision rule assigned participants to a subgroup reflecting the treatment estimated to minimize this outcome across all follow-up visits.

Results: The optimal decision rule was found to be a decision list with 3 steps. The first step moved WISDM participants with baseline time-below range >1.35% and no detectable C-peptide levels to the CGM subgroup (n = 139), and the second step moved WISDM participants with a baseline time-below range of >6.45% to the CGM subgroup (n = 18). The remaining participants (n = 37) were left in the BGM subgroup. Compared with the BGM subgroup (n = 37; 19%), the group for whom CGM minimized hypoglycemia (n = 157; 81%) had more baseline hypoglycemia, a lower proportion of detectable C-peptide, higher glycemic variability, longer disease duration, and higher proportion of insulin pump use.

Conclusions: The decision rule underscores the benefits of CGM for older adults to reduce hypoglycemia. Diagnostic CGM and laboratory markers may inform decision-making surrounding therapeutic CGM and identify older adults for whom CGM may be a critical intervention to reduce hypoglycemia.