A narrative commentary about interoperability in medical devices and data used in diabetes therapy from an academic EU/UK/US perspective.

People living with diabetes have many medical devices available to assist with disease management. A critical aspect that must be considered is how systems for continuous glucose monitoring and insulin pumps communicate with each other and how the data generated by these devices can be downloaded, integrated, presented and used. Not only is interoperability associated with practical challenges, but also devices must adhere to all aspects of regulatory and legal frameworks. Key issues around interoperability in terms of data ownership, privacy and the limitations of interoperability include where the responsibility/liability for device and data interoperability lies and the need for standard data-sharing protocols to allow the seamless integration of data from different sources. There is a need for standardised protocols for the open and transparent handling of data and secure integration of data into electronic health records. Here, we discuss the current status of interoperability in medical devices and data used in diabetes therapy, as well as regulatory and legal issues surrounding both device and data interoperability, focusing on Europe (including the UK) and the USA. We also discuss a potential future landscape in which a clear and transparent framework for interoperability and data handling also fulfils the needs of people living with diabetes and healthcare professionals.

Comparison of Control-IQ and open-source AndroidAPS automated insulin delivery systems in adults with type 1 diabetes: The CODIAC study.

AIM: To compare open-source AndroidAPS (AAPS) and commercially available Control-IQ (CIQ) automated insulin delivery (AID) systems in a prospective, open-label, single-arm clinical trial. METHODS: Adults with type 1 diabetes who had been using AAPS by their own decision entered the first 3-month AAPS phase then were switched to CIQ for 3 months. The results of this treatment were compared with those after the 3-month AAPS phase. The primary endpoint was the change in time in range (% TIR; 70-80 mg/dL). RESULTS: Twenty-five people with diabetes (mean age 34.32 ± 11.07 years; HbA1c 6.4% ± 3%) participated in this study. CIQ was comparable with AAPS in achieving TIR (85.72% ± 7.64% vs. 84.24% ± 8.46%; P = .12). Similarly, there were no differences in percentage time above range (> 180 and > 250 mg/dL), mean sensor glucose (130.3 ± 13.9 vs. 128.3 ± 16.9 mg/dL; P = .21) or HbA1c (6.3% ± 2.1% vs. 6.4% ± 3.1%; P = .59). Percentage time below range (< 70 and < 54 mg/dL) was significantly lower using CIQ than AAPS. Even although participants were mostly satisfied with CIQ (63.6% mostly agreed, 9.1% strongly agreed), they did not plan to switch to CIQ. CONCLUSIONS: The CODIAC study is the first prospective study investigating the switch between open-source and commercially available AID systems. CIQ and AAPS were comparable in achieving TIR. However, hypoglycaemia was significantly lower with CIQ.

Levels of retinol and retinoic acid in pancreatic cancer, type-2 diabetes and chronic pancreatitis.

AIMS: Retinoids participate in multiple key processes in the human body e.g., vision, cell differentiation and embryonic development. There is growing evidence of the relationship between retinol, its active metabolite- all-trans retinoic acid (ATRA) - and several pancreatic disorders. Although low levels of ATRA in pancreatic ductal adenocarcinoma (PDAC) tissue have been reported, data on serum levels of ATRA in PDAC is still limited. The aim of our work was to determine serum concentrations of retinol and ATRA in patients with PDAC, type-2 diabetes mellitus (T2DM), chronic pancreatitis (CHP) and healthy controls. METHODS: High performance liquid chromatography with UV detection (HPLC) was used to measure serum levels of retinol and ATRA in 246 patients with different stages of PDAC, T2DM, CHP and healthy controls. RESULTS: We found a significant decrease in the retinol concentration in PDAC (0.44+/-0.18 mg/L) compared to T2DM (0.65+/-0.19 mg/L, P<0.001), CHP (0.60+/-0.18 mg/L, P< 0.001) and healthy controls (0.61+/-0.15 mg/L, P<0.001), significant decrease of ATRA levels in PDAC (1.14+/-0.49 ug/L) compared to T2DM (1.37+/-0.56 ug/L, P<0.001) and healthy controls(1.43+/-0.55 ug/L, P<0.001). Differences between early stages (I+II) of PDAC and non-carcinoma groups were not significant. We describe correlations between retinol, prealbumin and transferrin, and correlation of ATRA and IGFBP-2. CONCLUSION: Significant decrease in retinol and ATRA levels in PDAC compared to T2DM, healthy individuals and/or CHP supports existing evidence of the role of retinoids in PDAC. However, neither ATRA nor retinol are suitable for detection of early PDAC. Correlation of ATRA levels and IGFBP-2 provides new information about a possible IGF and retinol relationship.

Low Initial Adherence with Flash Glucose Monitoring is Not a Predictor of Long-Term Glycemic Outcomes: Longitudinal Analysis of the Association Between Experience, Adherence, and Glucose Control for FreeStyle Libre Users.

INTRODUCTION: Frequent scanning of FreeStyle Libre (FSL) flash glucose monitoring sensors is known to be important whilst wearing an active sensor, but adherence to sensor reapplication is also critical to effective glucose monitoring. We report novel measures of adherence for users of the FSL system and their association with improvements in metrics of glucose control. METHODS: Anonymous data were extracted for 1600 FSL users in the Czech Republic with ≥ 36 completed sensors from October 22, 2018 to December 31, 2021. "Experience" was defined by the number of sensors used (1-36 sensors). "Adherence" was defined by time between the end of one sensor and the start of the next (gap time). User adherence was analyzed for four experience levels after initiating FLASH; Start (sensors 1-3); Early (sensors 4-6); Middle (sensors 19-21); End (sensors 34-36). Users were split into two adherence levels based on mean gap time during Start period, "low" (> 24 h, n = 723) and "high" (≤ 8 h, n = 877). RESULTS: Low-adherence users reduced their sensor gap times significantly: 38.5% applied a new sensor within 24 h during sensors 4-6, rising to 65.0% by sensors 34-36 (p < 0.001). Improved adherence was associated with increased %TIR (time in range; mean + 2.4%; p < 0.001), reduced %TAR (time above range; mean - 3.1%; p < 0.001), and reduced glucose coefficient of variation (CV; mean - 1.7%; p < 0.001). CONCLUSIONS: With experience, FSL users became more adherent in sensor reapplication, with associated increases in %TIR, and reductions in %TAR and glucose variability.

Lower Glycated Hemoglobin with Real-Time Continuous Glucose Monitoring Than with Intermittently Scanned Continuous Glucose Monitoring After 1 Year: The CORRIDA LIFE Study.

Background: The aim was to compare the efficacy of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) focusing on glycated hemoglobin (HbA1c) as the primary endpoint. Methods: The CORRIDA LIFE was a 12-month, real-world, nonrandomized study that is part of the CORRIDA clinical trials program. The study compared rtCGM (Dexcom G5 or G6) and isCGM (FreeStyle Libre 14-Day; Abbott) in adults with type 1 diabetes (T1D). Only patients on multiple daily insulin injections or continuous subcutaneous insulin infusion with no automatic functions were included in this study. Primary outcome was the difference in HbA1c between study groups at 12 months. Results: One hundred ninety-one adults with T1D (mean age 40 ± 13 years, HbA1c 8.1% ± 3.4% [65 ± 14 mmol/mol]) participated in this study; 81 patients initiated rtCGM and 110 initiated isCGM. After 12-months, HbA1c was significantly lower with rtCGM versus isCGM (7.1% ± 3.1% [54.1 ± 10.1 mmol/mol] vs. 7.7% ± 3.3% [61.2 ± 12.2 mmol/mol]), P = 0.0001. The percentage of time in hypoglycemia (<70 mg/dL [<3.9 mmol/L]) was lower among rtCGM vs. isCGM participants [4.3% ± 2.8% vs. 6.4% ± 5.3%], P = 0.003). Patients with rtCGM spent less time in clinically significant hypoglycemia (<54 mg/dL [<3.0 mmol/L]) (0.9% ± 1.0% vs. 2.3% ± 2.5%, P < 0.0001) and more time in target range (70-180 mg/dL [3.9-10 mmol/L]) than isCGM users (67.5% ± 14.8% vs. 57.8% ± 17.0%), P = 0.0002. Conclusions: rtCGM was superior to isCGM in HbA1c, hypoglycemia, and other glycemic outcomes. Our findings provide guidance to clinicians when discussing monitoring options with their patients. The study was registered at www.clinicaltrials.gov (NCT04759495).

Skin autofluorescence corresponds to microvascular reactivity in diabetes mellitus.

Advanced glycation accelerated by chronic hyperglycaemia contributes to the development of diabetic vascular complications throughout several mechanisms. One of these mechanisms is supposed to be impaired microvascular reactivity, that precedes significant vascular changes. The aim of this study was to find an association between advanced glycation, the soluble receptor for AGEs (sRAGE), and microvascular reactivity (MVR) in diabetes. Skin autofluorescence (SAF), which reflects advanced glycation, was assessed by AGE-Reader, MVR was measured by laser Doppler fluxmetry and evaluated together with sRAGE in 43 patients with diabetes (25 Type 1 and 18 Type 2) and 26 healthy controls of comparable age. SAF was significantly higher in patients with diabetes compared to controls (2.4 ± 0.5 vs. 2.0 ± 0.5 AU; p < 0.01). Patients with diabetes with SAF > 2.3 AU presented significantly worse MVR in both post-occlusive reactive hyperaemia (PORH) on the finger and forearm, and thermal hyperaemia (TH), compared to patients with SAF < 2.3 AU. SAF was age dependent in both diabetes (r = 0.41, p < 0.01) and controls (r = 0.45, p < 0.05). There was no association between SAF and diabetes control expressed by glycated haemoglobin. A significant relationship was observed between SAF and sRAGE in diabetes (r = 0.56, p < 0.001), but not in controls. A significant inverse association was found between SAF and MVR on the forearm in diabetes (PORH: r = -0.42, p < 0.01; TH: r = -0.46, p < 0.005). Both advanced glycation expressed by higher SAF or sRAGE and impaired MVR are involved in the pathogenesis of vascular complications in diabetes, and we confirm a strong interplay of these processes in this scenario.

Novel biochemical markers for non-invasive detection of pancreatic cancer.

To identify non-invasive biomarkers of non-metastatic pancreatic cancer (PC), the blood from 186 patients (PC n=28; DM-diabetes mellitus n=60; ChP-chronic pancreatitis n=47; healthy controls n=51) was analyzed for 58 candidate biomarkers. Their effectiveness to identify PC was compared with CA19-9. Panel defined by Random-forest (RF) analysis (CA19-9, AAT, IGFBP2, albumin, ALP, Reg3A, HSP27) outperforms CA19-9 in discrimination of PC from DM (AUC 0.92 vs. 0.82). Panel (S100A11, CA72-4, AAT, CA19-9, CB, MMP-7, S100P-s, Reg3A) is better in discrimination PC from ChP than CA19-9 (AUC 0.90 vs. 0.75). Panel (MMP-7, Reg3A, sICAM1, OPG, CB, ferritin) is better in discrimination PC from healthy controls than CA19-9 (AUC 0.89 vs. 0.78). Panel (CA19-9, S100P-pl, AAT, albumin, adiponectin, IGF-1, MMP7, S100A11) identifies PC among other groups better than CA19-9 (AUC 0.91 vs. 0.80). Panel defined by logistic regression analysis (prealbumin, IGFBP-2, DJ-1, MIC-1, CA72-4) discriminates PC from DM worse than CA19-9 (AUC 0.80 vs. 0.82). Panel (IGF-1, S100A11, Reg1alfa) outperforms CA19-9 in discrimination PC from ChP (AUC 0.76 vs. 0.75). Panel (IGF-2, S100A11, Reg3A) outperforms CA19-9 in discrimination PC from healthy controls (AUC 0.95 vs. 0.78). Panel (albumin, AAT, S100P-serum, CRP, CA19-9, TFF1, MMP-7) outperforms CA19-9 in identification PC among other groups (AUC 0.89 vs. 0.8). The combination of biomarkers identifies PC better than CA19-9 in most cases. S100A11, Reg3A, DJ-1 were to our knowledge identified for the first time as possible serum biomarkers of PC.

Hybrid Closed-Loop Systems for the Treatment of Type 1 Diabetes: A Collaborative, Expert Group Position Statement for Clinical Use in Central and Eastern Europe.

In both pediatric and adult populations with type 1 diabetes (T1D), technologies such as continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), or sensor-augmented pumps (SAP) can consistently improve glycemic control [measured as glycated hemoglobin (HbA1c) and time in range (TIR)] while reducing the risk of hypoglycemia. Use of technologies can thereby improve quality of life and reduce the burden of diabetes management compared with self-injection of multiple daily insulin doses (MDI). Novel hybrid closed-loop (HCL) systems represent the latest treatment modality for T1D, combining modern glucose sensors and insulin pumps with a linked control algorithm to offer automated insulin delivery in response to blood glucose levels and trends. HCL systems have been associated with increased TIR, improved HbA1c, and fewer hypoglycemic events compared with CSII, SAP, and MDI, thereby potentially improving quality of life for people with diabetes (PwD) while reducing the costs of treating short- and long-term diabetes-related complications. However, many barriers to their use and regional inequalities remain in Central and Eastern Europe (CEE). Published data suggest that access to diabetes technologies is hindered by lack of funding, underdeveloped health technology assessment (HTA) bodies and guidelines, unfamiliarity with novel therapies, and inadequacies in healthcare system capacities. To optimize the use of diabetes technologies in CEE, an international meeting comprising experts in the field of diabetes was held to map the current regional access, to present the current national reimbursement guidelines, and to recommend solutions to overcome uptake barriers. Recommendations included regional and national development of HTA bodies, efficient allocation of resources, and structured education programs for healthcare professionals and PwD. The responsibility of the healthcare community to ensure that all individuals with T1D gain access to modern technologies in a timely and economically responsible manner, thereby improving health outcomes, was emphasized, particularly for interventions that are cost-effective.

Pre-school and school-aged children benefit from the switch from a sensor-augmented pump to an AndroidAPS hybrid closed loop: A retrospective analysis.

OBJECTIVE: Data on closed loop systems in young children with type 1 diabetes (T1D) are limited. We tested the efficacy and safety of an open-source, do-it-yourself automated insulin delivery system AndroidAPS in preschool and school-aged children. RESEARCH DESIGN AND METHODS: This retrospective study analyzed diabetes control in 18 preschool (3-7 years) and 18 school-aged children (8-14 years) with T1D who switched from a sensor-augmented pump (SAP) to AndroidAPS. We compared the CGM parameters and HbA1c levels 3 months before and 6 months after the initiation of AndroidAPS therapy and evaluated frequency of severe adverse events during AndroidAPS use, the most frequent reasons for its interruption, and the experience and psychosocial benefits of AndroidAPS use. RESULTS: General glycemic control was significantly improved after the switch from SAP to AndroidAPS. Time in range (TIR) increased in both preschool (70.8%-78.6%, p = 0.004) and school-aged children (77.2%-82.9%, p < 0.001), whereas HbA1c levels decreased (preschool children 53.8-48.5 mmol/mol, p < 0.001; school-aged children 52.6-45.1 mmol/mol, p = 0.001). Time spent in range of 3.0-3.8 mmol/L increased slightly in school children (2.6%-3.8%, p = 0.040), but not in preschool children (3.0%-3.0%, p = 0.913). Time spent at <3 mmol/L remained unchanged in both preschool (0.95%-0.67%, p = 0.432) and school-aged children (0.8%-0.8%, p = 1.000). No episodes of severe hypoglycemia or DKA and significant improvement of quality of life were reported by AndroidAPS users. CONCLUSIONS: AndroidAPS seems effective for T1D control both in preschool and school-age children but further validation by prospective studies is necessary.

Real-time CGM Is Superior to Flash Glucose Monitoring for Glucose Control in Type 1 Diabetes: The CORRIDA Randomized Controlled Trial.

OBJECTIVE: The aim of this trial was to compare the efficacy of real-time and intermittently scanned continuous glucose monitoring (rtCGM and isCGM, respectively) in maintaining optimal glycemic control. RESEARCH DESIGN AND METHODS: In this randomized study, adults with type 1 diabetes (T1D) and normal hypoglycemia awareness (Gold score <4) used rtCGM (Guardian Connect Mobile) or isCGM (FreeStyle Libre) during 4 days of physical activity (exercise phase) and in the subsequent 4 weeks at home (home phase). Primary end points were time in hypoglycemia (<3.9 mmol/L [<70 mg/dL]) and time in range (3.9-10.0 mmol/L [70-180 mg/dL]). The isCGM group wore an additional masked Enlite sensor (iPro2) for 6 days to check for bias between the different sensors used by the rtCGM and isCGM systems. RESULTS: Sixty adults with T1D (mean age 38 ± 13 years; A1C 62 ± 12 mmol/mol [7.8 ± 1.1%]) were randomized to rtCGM (n = 30) or isCGM (n = 30). All participants completed the study. Percentage of time in hypoglycemia (<3.9 mmol/L [<70 mg/dL]) was lower among rtCGM versus isCGM participants in the exercise phase (6.8 ± 5.5% vs. 11.4 ± 8.6%, respectively; P = 0.018) and during the home phase (5.3 ± 2.5% vs. 7.3 ± 4.4%, respectively; P = 0.035). Hypoglycemia differences were significant and most notable during the night. rtCGM participants spent more time in range (3.9-10 mmol/L [70-180 mg/dL]) than isCGM participants throughout both the exercise (78.5 ± 10.2% vs. 69.7 ± 16%, respectively; P = 0.0149) and home (75.6 ± 9.7% vs. 67.4 ± 17.8%, respectively; P = 0.0339) phases. The results were robust to the insignificant bias between rtCGM and isCGM sensors that masked CGM found in the isCGM arm. CONCLUSIONS: rtCGM was superior to isCGM in reducing hypoglycemia and improving time in range in adults with T1D with normal hypoglycemia awareness, demonstrating the value of rtCGM alarms during exercise and in daily diabetes self-management.

Glycemic Outcomes in Adults With T1D Are Impacted More by Continuous Glucose Monitoring Than by Insulin Delivery Method: 3 Years of Follow-Up From the COMISAIR Study.

OBJECTIVE: This study assessed the clinical impact of four treatment strategies in adults with type 1 diabetes (T1D): real-time continuous glucose monitoring (rtCGM) with multiple daily insulin injections (rtCGM+MDI), rtCGM with continuous subcutaneous insulin infusion (rtCGM+CSII), self-monitoring of blood glucose with MDI (SMBG+MDI), and SMBG with CSII (SMBG+CSII). RESEARCH DESIGN AND METHODS: This 3-year, nonrandomized, prospective, real-world, clinical trial followed 94 participants with T1D (rtCGM+MDI, n = 22; rtCGM+CSII, n = 26; SMBG+MDI, n = 21; SMBG+CSII, n = 25). The main end points were changes in A1C, time in range (70-180 mg/dL [3.9-10 mmol/L]), time below range (<70 mg/dL [<3.9 mmol/L]), glycemic variability, and incidence of hypoglycemia. RESULTS: At 3 years, the rtCGM groups (rtCGM+MDI and rtCGM+CSII) had significantly lower A1C (7.0% [53 mmol/mol], P = 0.0002, and 6.9% [52 mmol/mol], P < 0.0001, respectively), compared with the SMBG+CSII and SMBG+MDI groups (7.7% [61 mmol/mol], P = 0.3574, and 8.0% [64 mmol/mol], P = 1.000, respectively), with no significant difference between the rtCGM groups. Significant improvements in percentage of time in range were observed in the rtCGM subgroups (rtCGM+MDI, 48.7-69.0%, P < 0.0001; and rtCGM+CSII, 50.9-72.3%, P < 0.0001) and in the SMBG+CSII group (50.6-57.8%, P = 0.0114). Significant reductions in time below range were found only in the rtCGM subgroups (rtCGM+MDI, 9.4-5.5%, P = 0.0387; and rtCGM+CSII, 9.0-5.3%, P = 0.0235). Seven severe hypoglycemia episodes occurred: SMBG groups, n = 5; sensor-augmented insulin regimen groups, n = 2. CONCLUSIONS: rtCGM was superior to SMBG in reducing A1C, hypoglycemia, and other end points in individuals with T1D regardless of their insulin delivery method. rtCGM+MDI can be considered an equivalent but lower-cost alternative to sensor-augmented insulin pump therapy and superior to treatment with SMBG+MDI or SMBG+CSII therapy.

Excellent Glycemic Control Maintained by Open-Source Hybrid Closed-Loop AndroidAPS During and After Sustained Physical Activity.

OBJECTIVE: Officially licensed hybrid closed-loop systems are not currently available worldwide; therefore, open-source systems have become increasingly popular. Our aim was to assess the safety, feasibility, and efficacy of an open-source hybrid closed-loop system (AndroidAPS) versus SmartGuard® technology for day-and-night glucose control in children under extreme sports conditions. RESEARCH DESIGN AND METHODS: Twenty-two children (16 girls, 6-15 years of age, median HbA1c 56 ± 9 mmol/mol) were enrolled in this pivotal winter sports camp study. The participants were divided into two groups using either the AndroidAPS or SmartGuard technology. Physical exertion was represented by all-day alpine skiing. The primary endpoints were mean glucose level, time below the threshold of 3.9 mmol/L, and time within the target range of 3.9 to 10 mmol/L. RESULTS: The children using the AndroidAPS had significantly lower mean glycemia levels (7.2 ± 2.7 vs. 7.7 ± 2.8 mmol/L; 129.6 ± 49 vs. 138.6 ± 50 mg/dL, P < 0.042) than the children using the SmartGuard. The proportion of time below the target (median 5.0% ± 2.5% vs. 3.0% ± 2.3%, P = 0.6) and in the target zone (63% ± 9.5% vs. 63% ± 18%, P = 0.5) did not significantly differ. The AndroidAPS group experienced more frequent malfunctions of the cannula set (median 0.8 ± 0.4 vs. 0.2 ± 0.4, P = 0.02), which could have affected the results. No significant difference was found in the amount of carbohydrates consumed for the prevention and treatment of hypoglycemia [median 40 ± 23 vs. 25 ± 29 g/(patient ·3 days)]. No episodes of severe hypoglycemia or other serious adverse events were noted. CONCLUSIONS: This pilot study showed that the AndroidAPS system was a safe and feasible alternative to the SmartGuard Technology.

[Glycemic variability and microvascular complications of diabetes]. / Glykemická variabilita a mikrovaskulární komplikace diabetu.

Vascular complications of diabetes result from long lasting unsatisfactory glycemic control. We usually assess glycemic control based on the value of glycated hemoglobin HbA1c. The glycated hemoglobin test, however, says nothing about short-term glycemic fluctuations. Recently, continuous monitoring of glycemia has enabled us an in-depth assessment of changes in glucose concentrations, called glycemic variability. Together with the research of short-term glycemic variability, also the study of long-term fluctuations in glycemic control based on HbA1c variability has now intensified. Glycemic variability may be related to oxidation stress, endothelial dysfunction and inflammation, the factors traditionally associated with vascular damage. This overview summarizes the recent findings in the field of glycemic variability and its possible association with microvascular complications in patients with type 1 and type 2 diabetes.Key words: glycemic variability, HbA1c variability, microvascular complications, type 1 and type 2 diabetes mellitus.

Effectiveness of SmartGuard Technology in the Prevention of Nocturnal Hypoglycemia After Prolonged Physical Activity.

BACKGROUND: The prevention of postexercise nocturnal hypoglycemia after prolonged physical activity using sensor-augmented pump (SAP) therapy with predictive low-glucose management (PLGM) has not been well studied. We conducted a study at a pediatric diabetes camp to determine whether a SAP with PLGM reduces the frequency of nocturnal hypoglycemia after prolonged physical activity more effectively than a SAP with a carbohydrate intake algorithm. METHODS: During a 1-week sport camp, 20 children (aged 10-13 years) with type 1 diabetes (T1D) managed by SAP therapy either with (n = 7) or without PLGM (n = 13) were studied. The hypoglycemia management strategy and the continuous glucose monitoring (CGM)/PLGM settings were standardized. The incidence, severity, and duration of hypoglycemia and carbohydrate intake were documented and compared. RESULTS: The PLGM system was activated on 78% of all nights (once per night on average). No difference was found between the SAP and PLGM groups in the mean overnight glucose curve or mean morning glucose (7.8 ± 2 mmol/L vs. 7.4 ± 3 mmol/L). There was no difference in the frequency and severity of hypoglycemia. However, the SAP group consumed significantly more carbohydrates to prevent and treat hypoglycemia than those in the PLGM group; the values were 10 ± 2 and 1 ± 2 gS (P < 0.0001) in the SAP and PLGM groups, respectively. Moreover, the SAP group spent a significantly longer time in hypoglycemia (64 ± 2 min vs. 38 ± 2 min, P < 0.05). We observed a difference in the time distribution of nocturnal hypoglycemia (10 to 12 p.m. in the PLGM group and 3 to 7 a.m. in the SAP group, P < 0.05). CONCLUSION: With PLGM system, euglycemia after prolonged physical activity was largely maintained with a minimal carbohydrate intake.

[Short-term and long-term glycemic variability and its relationship to microvascular complications of diabetes]. / Krátkodobá a dlouhodobá glykemická variabilita a její vztah k mikrovaskulárním komplikacím diabetu.

Vascular complications of diabetes result from long lasting unsatisfactory glycemic control. We usually assess glycemic control based on the value of glycated hemoglobin HbA1c. The glycated hemoglobin test, however, says nothing about short-term glycemic fluctuations. Recently, continuous monitoring of glycemia has enabled us an in-depth assessment of changes in glucose concentrations, called glycemic variability. In connection with the research into short-term glycemic variability, also the study of long-term fluctuations in glycemic control based on HbA1c variability has now intensified. Glycemic variability may be related to oxidation stress, endothelial dysfunction and inflammation, the factors traditionally associated with vascular damage. Several studies have described the relation of glycemic variability to macrovascular complications of diabetes, still its relation to microvascular complications remains unclear. This overview summarizes the recent findings in the field of glycemic variability and its possible association with retinopathy, nephropathy and neuropathy.Key words: type 1 and 2 diabetes mellitus - glycemic variability - microvascular complications - HbA1c - variability.

[Clinical efficacy and safety of basal insulin analogue glargine in patients with type 2 diabetes mellitus]. / Klinická úcinnost a bezpecnost bazálního inzulinového analoga glarginu v lécbe pacientu s diabetes mellitus 2. typu.

Basal insulin has a clearly defined position in the recommendations for the treatment of patients with type 2 diabetes mellitus. General most common indication for administration is the addition in situation of the failure of noninsulin antidiabetic therapy or early insulin treatment of diabetes, as one of the second choice after metformin. In the recent years there is significant expansion of the range of antidiabetic drugs, including basal insulin analogues. In connection with the introduction of concentrated long-acting basal insulin analogues into the clinical practice many questions regarding clinical efficacy and safety raises especially comparing with the "classical" basal insulin analogues. Although it is very likely that in the current clinical practice these differences in a number of indications are of minimal impact, it is possible that in some situations clinically relevant differences can be found among the basal insulin analogues.Key words: basal insulin analogues - concentrated insulin - diabetes mellitus - EDITION trial - glargine - hypoglycemia - insulin therapy.

Comparison of Different Treatment Modalities for Type 1 Diabetes, Including Sensor-Augmented Insulin Regimens, in 52 Weeks of Follow-Up: A COMISAIR Study.

OBJECTIVE: To compare different treatment modalities for patients with type 1 diabetes (T1D) based on real-time continuous glucose monitoring (RT-CGM) or self-monitoring of blood glucose (SMBG) combined with multiple daily injections (MDIs) or continuous subcutaneous insulin infusion (CSII). RESEARCH DESIGN AND METHODS: Sixty-five T1D patients were followed up for a year. Of these, 27 started RT-CGM as part of a sensor-augmented insulin regimen (SAIR); within this SAIR group, 15 subjects started sensor-augmented pump (SAP) therapy and the remaining 12 continued with MDIs (MDIs + RT-CGM). A second group of 20 patients initiated CSII without RT-CGM, while a third group of 18 subjects continued on MDIs and SMBG. The main endpoints were reduction of HbA1c, glycemic variability (GV), and incidence of hypoglycemia. RESULTS: After a year, the baseline mean HbA1c in the SAIR group (8.3%) decreased to 7.1% (P < 0.0001); both SAIR subgroups, SAP and MDIs + RT-CGM, showed comparable improvement. The CSII group also had reduced HbA1c (8.4% ± 0.9% vs. 7.9% ± 0.7%; P < 0.05). Both SAIRs were superior to MDIs (P = 0.002) and CSII (P = 0.0032). GV was also lowered, both in the SAIR (P < 0.0001) and CSII (P < 0.05) groups. Reduced incidence of hypoglycemia was observed only with SAIR (8% ± 4% vs. 6% ± 3%; P < 0.01). CONCLUSION: Both SAIRs, SAP and MDIs + RT-CGM, provided significant and comparable decrease of HbA1c with concurrent reduction of hypoglycemia. This improvement was greater than that seen with CSII. The combination of RT-CGM and MDIs can be a suitable alternative to SAP for some patients.