Journal of Diabetes Science and Technology最新文献

Presented is a series of narrative reviews that summarize published information regarding the effect or potential effect of interfering substances on the accuracy of continuous glucose monitoring (CGM) devices. While drawing together what is currently known regarding this topic, the future direction in this field and clinical implications posed by polypharmacy on CGM performance are considered. This first in a series of four review articles classifies commercially available CGMs by glucose measurement principle before reviewing what is currently known regarding substance interference mechanisms and design approaches that may serve to reduce interfering effects. Points covered include the following: minimally invasive electrochemical CGMs, which may be classified by first-, second-, or third-generational design (these models are at risk of interference from electroactive substances, or substances that can interfere with the enzymatic biorecognition process); non-invasive fluid sampling CGMs, which draw glucose across the skin barrier but are similarly reliant on the electrochemical measurement of an enzymatic reaction product; and minimally invasive implantable CGMs, which exhibit different interfering substance behaviors to other CGM classes, using a non-enzyme-based glucose-recognition agent coupled to optical detection. An understanding of substance-interfering mechanisms allows consideration of the potential impact on clinical accuracy of substances that are routinely prescribed, can be purchased over the counter, or are new to market.

Background: Technosphere insulin (TI) is an ultra-rapid-acting inhaled insulin approved for glucose management in adults with diabetes mellitus. Using a higher modified initial conversion dose than in the current United States Prescribing Information, this study assessed supplementing or replacing automated insulin delivery (AID) systems with TI.

Methods: Adult participants with type 1 diabetes (glycated hemoglobin [HbA1c], 7%-11%) using an AID system were randomized into TI + AID (TI for meals and AID for basal and corrections), TI + insulin degludec (TI for meals and corrections and insulin degludec for basal), or control group (remaining on AID) and treated for 90 days. HbA1c, forced expiratory volume in 1 second (FEV₁), hypoglycemic events, and adverse events (AEs) were assessed.

Results: Of 33 enrolled participants, 24 completed the study. All groups demonstrated comparable declines in HbA1c from baseline to end of treatment (statistically significant decline for control group). No within- or between-group statistical differences were observed in FEV₁. Incidence and event rate of hypoglycemia <70 mg/dL and <54 mg/dL were similar between groups, and no severe hypoglycemic events were reported. No treatment-related serious AEs were reported, and 2 participants experienced AEs of special interest related to TI (clinically relevant decline in pulmonary function and wheezing).

Conclusions: This proof-of-concept study demonstrated the safety and efficacy of TI, at a higher modified dose conversion, when added for mealtime control to an AID system or was used for glycemic control with basal insulin.

Individuals with a family history of type 1 diabetes (T1D) are at significantly higher risk of developing T1D compared to the general population. Before its clinical onset, individuals with T1D can be identified through islet autoantibody (IAb) testing which, if multiple IAbs are detected, justifies the diagnosis of early-stage T1D. Amid rising global T1D incidence, we outline Germany's strategy for early detection and management focused on individuals with a family history and, where informative, implementation lessons are illustrated using findings from the German Fr1da general-population study. Genetic risk factors for T1D development in individuals with family history are discussed, as well as impacts of positive screening results including influence on diabetic ketoacidosis (DKA) rates and psychological aspects. In parallel, recommendations and consensus guidelines from other national screening efforts are introduced. Building on this, we address challenges in nationwide T1D family-based screening integration and explore leveraging health care systems for cost-effective implementation. We also provide practical aspects to overcome barriers for family-based T1D screening and introduce monitoring strategies in individuals with early-stage T1D. With the advent of disease-modifying therapies (DMTs) for delaying T1D progression, there is now a rationale at hand that offers an IAb screening incentive. Collectively, we emphasize the critical role of early detection and monitoring among at-risk relatives in mitigating the burden of T1D on individuals, families, and health care systems.

Background: Gestational diabetes mellitus (GDM) is a frequent metabolic complication during pregnancy that significantly impacts both maternal and neonatal health outcomes regularly resulting in NH. Exploring the interactions between maternal characteristics, neonatal outcomes, and data collected from wearable technologies, such as continuous glucose monitoring (CGM) could potentially enable the development of predictive models and support personalized care.

Methods: This study employed probabilistic modeling, using Bayesian networks (BNs), to analyze data from the STEADY SUGAR clinical trial (N = 118 women with GDM) with the aim of discovering interactions between maternal characteristics, CGM-derived features calculated in the 90 days preceding delivery, and neonatal outcomes, particularly NH. The final BN returns a graph and conditional probability tables between inputs and outputs, whose statistical relevance has been quantified via odds ratios (ORs).

Results: Direct associations were identified between NH and maternal hypertension (OR: 2.13 [1.02, 4.46]), family history for diabetes (OR: 1.43 [0.57, 3.57]), and elevated maternal body mass index (BMI) (OR: 3.59 [1.42, 9.08] comparing lower vs higher BMI categories). Cesarean delivery also influenced NH risk (OR: 2.05 [0.98, 4.28]). Indirect associations involving medication regimens and delivery type were significant. Ethnic disparities emerged, notably higher hyperglycemia among Afro-American patients (OR: 2.91 [1.19, 7.11]), highlighting ethnicity-related variations in glycemic control. Notably, CGM-derived metrics were associated with multiple neonatal outcomes.

Conclusions: Bayesian network allowed to explore the complex interactions between variables in pregnancies affected by GDM. This framework will be extended with wider data sets to provide valuable insights for clinical decision-making able to mitigate maternal and neonatal risks.

Introduction: Prior studies have not identified if continuous glucose monitoring (CGM) metrics at a critical gestational age window can discriminate risk of adverse pregnancy outcomes. We evaluated late second- and third-trimester CGM metrics by gestational age associated with pregnancy outcomes in gravidas with type 1 diabetes (T1DM).

Methods: Dexcom G6 CGM data from a retrospective cohort of singleton gestations with T1DM (2018-2022) at an academic medical center were analyzed. Time in, above, and below range 63 to 140 mg/dL (TIR, TAR, TBR), glycemic variability, and mean glucose concentration were computed in two-week CGM intervals from 24⁰ to 39⁶ weeks^days. Adverse pregnancy outcomes were hypertensive disorders of pregnancy (HDP), large-for-gestational age (LGA), and neonatal hypoglycemia. Linear mixed-effects models were fitted on CGM metrics computed from two-week CGM intervals, with gestational age, adverse pregnancy outcomes (i.e. presence/absence of HDP, LGA, and/or neonatal hypoglycemia), and their interaction as fixed effects.

Results: In 87 gravidas with preconception median hemoglobin A1c 6.5% (IQR 6.0, 7.1) and maternal body mass index 24.8 kg/m² (IQR 21.9, 27.1), 71% had at least one adverse pregnancy outcome. Between weeks 24⁰ and 37⁶, gravidas with HDP had higher TAR and mean glucose and lower TIR (P < .05). Gravidas with LGA had lower TBR between weeks 24⁰ and 35⁶. TIR, TAR, and mean glucose evolution differed by HDP status, with greatest divergence between groups at 28⁰ to 29⁶ weeks' gestation (P ≤ .001).

Conclusion: CGM metrics in the late second to early third trimester, a period of peak insulin resistance, may help to distinguish risk of HDP and LGA in gravidas with T1DM.

Background: Perioperative hyperglycemia in people with diabetes is associated with increased morbidity, mortality, and health care costs. Despite guideline recommendations to institute interventions to reduce hyperglycemia, standardized protocols that integrate into clinical workflows are lacking. In this article, we evaluate the efficacy of a digitally embedded, glycemic management protocol in people with diabetes undergoing surgery.

Methods: We conducted a retrospective analysis of a quality improvement study conducted at a tertiary-care academic hospital. Adults with diabetes undergoing noncardiac surgery with more than two hours of procedure time were included. A multidisciplinary protocol was implemented guiding insulin administration and glucose monitoring across preoperative, intraoperative, and post-anesthesia care unit (PACU) phases. People undergoing surgery during one year before protocol implementation were compared with those in the year after. The primary outcome was the proportion of intraoperative glucose readings within 70 to 180 mg/dL. Secondary outcomes included glucose control in other perioperative phases, hypoglycemia incidence, and 30-day postoperative complications.

Results: Among 1254 adults (634 pre-intervention, 620 post-intervention), the mean proportion of intraoperative glucose values in the target range of 70 to 180 mg/dL showed a modest yet statistically significant improvement after protocol implementation (0.65 vs 0.72, P = .021). We found a reduced risk of hypoglycemia in the preoperative phase (3.7% vs 1.3%, P = .007) and no increased risk of hypoglycemia in the intraoperative or PACU phases. An increase in glucose monitoring and intravenous insulin use was noted across all phases of care (P < .001).

Conclusions: Implementation of a digitally embedded perioperative glycemic management protocol improved glucose monitoring and intraoperative glucose control without increasing hypoglycemia. These findings support the safe and effective use of the protocol across surgical specialties and case urgencies, supporting the value of integrating decision support tools into clinical workflows.

Integration of direct electron transfer-type (DET-type) Burkholderia cepacia glucose dehydrogenase (BcGDH) with an extended gate field effect transistor (EGFET) transducer to measure glucose in human plasma is a promising approach to overcome technology limitations in commercial continuous glucose monitors (CGM). Sensors were fabricated using microwire electrodes and were characterized for selectivity against interferents, reversibility, stability, and validated ex vivo. DET-type EGFET sensors showed low signal bias against a variety of interfering compounds and demonstrated acute reversibility and stability, while also successfully measuring glucose ex vivo in human plasma with a limit of detection of 0.94 mM. The DET-type EGFET glucose sensor was operated ex vivo over a physiological concentration range, demonstrating the feasibility of using EGFET-based transduction of DET-BcGDH for future use in CGM applications.

Background: There is emerging interest in the application of foot temperature monitoring as means of diabetic foot ulcer (DFU) prevention. However, the variability in temperature readings of neuropathic feet remains unknown. The aim of this study was to analyze the long-term consistency of foot thermograms of diabetic feet at the risk of DFU.

Methods: A post-hoc analysis of thermal images of 15 participants who remained ulcer-free during a 12-month follow-up were unblinded at the end of the trial. Skin foot temperatures of 12 plantar, 15 dorsal, 3 lateral, and 3 medial regions of interests (ROIs) were derived on monthly thermograms. The temperature differences (∆Ts) of corresponding ROIs of both feet were calculated.

Results: Over the 12-month study period, out of the total 2026 plantar data points, 20.3% ROIs were rated as abnormal (absolute ∆T ≥ 2.2°C). There was a significant between-visit variability in the proportion of plantar ROIs with ∆T ≥ 2.2°C (range 7.6%-30.8%, chi-square test, P = .001). The proportion of patients presenting with hotspots (ROIs with ∆T ≥ 2.2°C), abnormal plantar foot temperature (mean ∆T of 12 plantar ROIs ≥ 2.2°C), and abnormal whole foot temperature (mean ∆T of 33 ROIs ≥ 2.2°C) varied between visits and showed no pattern (P > .05 for all comparisons). This variability was not related to the season of assessment.

Conclusions: Despite the high rate of hotspots on monthly thermograms, all feet remained intact. This study underscores a significant between-visit inconsistency in thermal images of neuropathic feet which should be considered when planning DFU-prevention programs for self-testing and behavior modification.