Journal of Diabetes Science and Technology最新文献

Introduction: Insulin pump therapy can be adversely affected by interruption of insulin flow, leading to a rise in blood glucose (BG) and subsequently of blood beta-hydroxybutyrate (BHB) ketone levels.

Methods: We performed a PubMed search for English language reports (January 1982 to July 2024) estimating the rate of rise in BG and/or BHB after ≥ 60 minutes of interruption of continuous subcutaneous insulin infusion (CSII) in persons with type 1 diabetes (PwT1D). We also simulated the rise in BG in a virtual population of 100 adults with T1D following suspension of continuous subcutaneous insulin infusion.

Results: We identified eight relevant studies where BG and BHB (seven of these eight studies) were measured following suspension of CSII as a model for occlusion. After 60 minutes post-suspension, the mean extracted rates of rise averaged 0.62 mg/dL/min (37 mg/dL/h) for BG and 0.0038 mmol/L/min (0.20 mmol/L/h) for BHB. Mean estimated time to moderately/severely elevated BG (300/400 mg/dL) or BHB (1.6/3.0 mmol/L) was, respectively, 5.8/8.5 and 8.0/14.2 hours. The simulation model predicted moderately/severely elevated BG (300/400 mg/dL) after 9.25/12, 6.75/8.75, and 4.75/5.75 hours in the virtual subjects post-interruption with small (5th percentile), medium (50th percentile), and large (95th percentile) hyperglycemic changes.

Discussion: Clinical studies and a simulation model similarly predicted that, following CSII interruption, moderate/severe hyperglycemia can occur within 5-9/6-14 hours, and clinical studies predicted that moderate/severe ketonemia can occur within 7-12/13-21 hours. Patients and clinicians should be aware of this timing when considering the risks of developing metabolic complications after insulin pump occlusion.

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.

Gestational diabetes mellitus (GDM) is a common metabolic disease of pregnancy that threatens the health of several million women and their offspring. The highest prevalence of GDM is seen in women of low socioeconomic status. Women with GDM are at increased risk of adverse maternal outcomes, including increased rates of Cesarean section delivery, preeclampsia, perineal tears, and postpartum hemorrhage. However, of even greater concern is the increased risk to the fetus and long-term health of the child due to elevated glycemia during pregnancy. Although the use of continuous glucose monitoring (CGM) has been shown to reduce the incidence of maternal and fetal complications in pregnant women with type 1 diabetes and type 2 diabetes, most state Medicaid programs do not cover CGM for women with GDM. This article reviews current statistics relevant to the incidence and costs of GDM among Medicaid beneficiaries, summarizes key findings from pregnancy studies using CGM, and presents a rationale for expanding and standardizing CGM coverage for GDM within state Medicaid populations.

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: 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: 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.