Citations

Background and Objective: The premise of effective closed-loop insulin therapy for type 1 diabetes (T1D) relies on the accuracy of continuous interstitial fluid glucose sensing that represents the crucial afferent arm of such a system. An important determinant of sensor accuracy is the physiological time lag of glucose transport from the vascular to the interstitial space. The purpose of current studies was to determine the physiological time lag of glucose transport from the vascular to the abdominal subcutaneous interstitial space in T1D. Method: Four microdialysis catheters were inserted into the abdominal subcutaneous space in 6 T1D subjects under overnight fasted conditions. Plasma glucose was maintained at 113.7 ± 6.3 mg/dl using a continuous intravenous insulin infusion. After sequential intravenous bolus administrations of glucose isotopes, timed plasma and interstitial fluid samples were collected chronologically and analyzed for tracer enrichments. Results: We observed a median (range) time lag of tracer appearance (time to detection) into the interstitial space after intravenous bolus of 6.8 (4.8-9.8) minutes, with all participants having detectable values by 9.8 minutes. Conclusions: We conclude that in the overnight fasted state in T1D adults, the delay of glucose appearance from the vascular to the interstitial space is less than 10 minutes, thereby implying that this minimal physiological time lag should not be a major impediment to the development of an effective closed-loop control system for T1D.

Controlling meal-related glucose excursions continues to be a therapeutic challenge in diabetes mellitus. Mechanistic reasons for this need to be understood better to develop appropriate therapies. To investigate delayed gastric emptying effects on postprandial glucose turnover, insulin sensitivity, and β-cell responsivity and function, as a feasibility study prior to studying patients with type 1 diabetes, we used the triple tracer technique C-peptide and oral minimal model approach in healthy subjects. A single dose of 30 μg of pramlintide administered at the start of a mixed meal was used to delay gastric emptying rates. With delayed gastric emptying rates, peak rate of meal glucose appearance was delayed, and rate of endogenous glucose production (EGP) was lower. C-peptide and oral minimal models enabled the assessments of β-cell function, insulin sensitivity, and β-cell responsivity simultaneously. Delayed gastric emptying induced by pramlintide improved total insulin sensitivity and decreased total β-cell responsivity. However, β-cell function as measured by total disposition index did not change. The improved whole body insulin sensitivity coupled with lower rate of appearance of EGP with delayed gastric emptying provides experimental proof of the importance of evaluating pramlintide in artificial endocrine pancreas approaches to reduce postprandial blood glucose variability in patients with type 1 diabetes.

To provide an understanding of both the preclinical and clinical aspects of closed-loop artificial pancreas systems, we provide a discussion of this topic as part of this two-part Bench to Clinic narrative. Here, the Bench narrative provides an in-depth understanding of insulin-glucose-glucagon physiology in conditions that mimic the free-living situation to the extent possible in type 1 diabetes that will help refine and improve future closed-loop system algorithms. In the Clinic narrative, Doyle and colleagues compare and evaluate technology used in current closed-loop studies to gain further momentum toward outpatient trials and eventual approval for widespread use.

Objective: We evaluate the prevalence, etiology, and outcomes of hypoglycemia requiring emergency medical services (EMS) in patients without diabetes mellitus (non-DM). Methods: We reviewed medical records of all ambulance calls for non-DM with blood glucose <70 mg/dl in Olmsted County, Minnesota, between January 1, 2003, and December 31, 2009. Results: A total of 131 patients (age 51 ± 19 years; 54 % females) made 142 EMS calls, while 10 patients made repeated calls. Causes of hypoglycemia were critical illness (42; 32%), alcohol and polysubstance use (36; 27.5 %), insulinoma/ bariatric surgery (10; 8%), restricted oral intake (7; 5%), and multiple factors (3; 27.5 %). Patients with alcohol and polysubstance abuse were younger ( p = .002). A total of 54 patients had additional hypoglycemia predisposing comorbidities/factors [adrenal insufficiency (2), end-stage renal disease (11) and chronic liver disease (7), beta blockers use (34), and pentamidine use (1)]. Repeated calls and emergency room transportation were similar, but hospitalization varied across the etiologies, with the lowest proportion in the multiple-factor-related hypoglycemia group ( p = .01). Duration of follow-up was 1.28 (interquartile range 0.13–2.70) years. A total of 38 patients died, and age-adjusted mortality varied across different etiologies ( p < .001), with highest among critically ill. Cancer caused the highest number of deaths (7/38; 18%), while 1 death was due to hypoglycemia. Conclusions: There were multiple etiologies for hypoglycemic episodes in community-dwelling non-DM that required EMS. Critical illness, multifactorial causes, and alcohol/polysubstance abuse were common causes. Hospitalization and mortality were higher with critical illnesses.

Objective: The objective is to report a contemporary population-based estimate of hypoglycemia requiring emergency medical services (EMS), its burden on medical resources, and its associated mortality in patients with or without diabetes mellitus (DM, non-DM), which will enable development of prospective strategies that will capture hypoglycemia promptly and provide an integrated approach for prevention of such episodes. Methods: We retrieved all ambulance calls activated for hypoglycemia in Olmsted County, Minnesota, between January 1, 2003 and December 31, 2009. Results: A total of 1473 calls were made by 914 people (DM 8%, non-DM 16%, unknown DM status 3%). Mean age was 60 ± 16 years with 49% being female. A higher percentage of calls were made by DM patients (87%) with proportionally fewer calls coming from non-DM patients (11%) (chi-square test, p < .001), and the remaining 2% calls by people with unknown DM status. Emergency room transportation and hospitalization were significantly higher in non-DM patients compared to DM patients ( p < .001) and type 2 diabetes mellitus compared to type 1 diabetes mellitus ( p < .001). Sulphonylureas alone or in combination with insulin varied during the study period ( p = .01). The change in incidence of EMS for hypoglycemia was tracked during this period. However, causality has not been established. Death occurred in 240 people, 1.2 (interquartile range 0.2–2.7) years after their first event. After adjusting for age, mortality was higher in non-DM patients compared with DM patients ( p < .001) but was not different between the two types of DM. Conclusions: The population burden of EMS requiring hypoglycemia is high in both DM and non-DM patients, and imposes significant burden on medical resources. It is associated with long-term mortality.

Background: Safe and effective glucose control in the intensive care unit (ICU) continues to be actively pursued. Large clinical trials have examined the safety and efficacy of insulin infusion protocols in medical and surgical ICUs. We report experiences of a single-center standardized nurse-driven insulin infusion protocol in three ICUs in an observational quality-improvement study. Method: We analyzed the hourly point-of-care arterial blood glucose obtained during ICU insulin infusion protocol (protocol A) with a glucose target of 80–130 mg/dl in medical and surgical ICUs in February 2009. Following Normoglycemia in Intensive Care Evaluation and Survival Using Glucose Algorithm Regulation (NICE-SUGAR) study results, the protocol was amended (protocol B) to achieve target glucose of 110–150 mg/dl. The performance of protocol B was assessed in the ICUs in May 2010 and compared with protocol A with respect to glucose concentrations and rates of severe (<40 mg/dl) and moderate (40–60 mg/dl) hypoglycemia. Results: With protocol A, in medical ( n = 44) and surgical ( n = 164) ICUs taken together, median glucose was 119 mg/dl, with severe and moderate hypoglycemia rates 1.4% (3/208) and 7.7% (16/208), respectively, which were significantly lower than those reported by the NICE-SUGAR and the Leuven studies. With protocol B, in medical ( n = 44) and surgical ( n = 167) ICUs taken together, median glucose was 132 mg/dl, with severe and moderate hypoglycemia of 0 % (0/211) and 0.5% (1/211), respectively. Conclusion: The current ICU insulin infusion protocol (protocol B) reduces severe and moderate hypoglycemia without compromising glucose control when compared with protocol A. This could potentially impact patient-important outcomes.

Objective: We conducted a systematic review and meta-analysis to assess the efficacy of continuous glucose monitoring (CGM) in improving glycemic control and reducing hypoglycemia compared to self-monitored blood glucose (SMBG). Methods: We searched MEDLINE, EMBASE, Cochrane Central, Web of Science, and Scopus for randomized trials of adults and children with type 1 or type 2 diabetes mellitus (T1DM or T2DM). Pairs of reviewers independently selected studies, assessed methodological quality, and extracted data. Meta-analytic estimates of treatment effects were generated using a random-effects model. Results: Nineteen trials were eligible and provided data for meta-analysis. Overall, CGM was associated with a significant reduction in mean hemoglobin A1c [HbA1c; weighted mean difference (WMD) of −0.27% (95% confidence interval [CI] −0.44 to −0.10)]. This was true for adults with T1DM as well as T2DM [WMD −0.50% (95% CI −0.69 to −0.30) and −0.70 (95% CI, −1.14 to −0.27), respectively]. No significant effect was noted in children and adolescents. There was no significant difference in HbA1c reduction between studies of real-time versus non-real-time devices (WMD −0.22%, 95% CI, −0.59 to 0.15 versus −0.30%, 95% CI, −0.49 to −0.10; p for interaction 0.71). The quality of evidence was moderate due to imprecision, suggesting increased risk for bias. Data for the incidence of severe or nocturnal hypoglycemia were sparse and imprecise. In studies that reported patient satisfaction, users felt confident about the device and gave positive reviews. Conclusion: Continuous glucose monitoring seems to help improve glycemic control in adults with T1DM and T2DM. The effect on hypoglycemia incidence is imprecise and unclear. Larger trials with longer follow-up are needed to assess the efficacy of CGM in reducing patient-important complications without significantly increasing the burden of care for patients with diabetes.

OBJECTIVE The goal was to develop a new index of insulin sensitivity in patients with type 1 diabetes estimated from continuous glucose monitoring (CGM) and subcutaneous insulin delivery data under carefully controlled conditions. RESEARCH DESIGN AND METHODS The database consists of 12 subjects with type 1 diabetes, studied during breakfast, lunch, and dinner, in a clinical research unit, wearing both subcutaneous insulin pump and CGM device. Frequent blood samples were drawn for measurements of plasma glucose and insulin concentrations in order to estimate insulin sensitivity with the oral minimal model (SIMM). The new index of insulin sensitivity (SISP) was calculated with a simple algebraic formula for each meal, using only CGM and insulin pump data and compared with SIMM. RESULTS SI SP was well correlated with SIMM (r = 0.825; P &lt; 10−8), and diurnal pattern was also similar to SIMM. CONCLUSIONS A novel method for estimating insulin sensitivity in subjects with type 1 diabetes on sensor-augmented insulin pump therapy has been presented. This new index correlates well with the reference oral minimal model estimate of insulin sensitivity. The knowledge of patient-specific insulin sensitivity and its diurnal variation can help in optimizing insulin therapy in type 1 diabetes and could also inform next-generation closed-loop control systems.