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Nutritional therapies are one of the fundamentals of effective management of diabetes type 1 and type 2. Lifestyle interventions, including nutritional recommendations, are also part of the basic therapy for people with prediabetes or obesity. It is recommended that the diet should be individually adapted to personal circumstances, preferences and metabolic goals. In the age of digitalisation, mHealth interventions, like continuous glucose monitoring systems (CGM), are increasingly finding their way into nutrition therapy. The ambulatory glucose profile (AGP), a structured and graphical compilation of the obtained CGM data, can also be used as a support for dietary adjustment. After assessment of the glycaemic situation (hypoglycaemia, variability and stability of glucose levels). This publication aims to provide a general overview of nutritional recommendations, especially in Germany, and to describe the benefits of CGM measurements with regard to nutrition., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021. Published by Elsevier B.V.)

Background: The ambulatory glucose profile (AGP) uses the wealth of data that are generated by continuous glucose monitoring, including flash glucose monitoring technologies, to provide a visual representation of glucose levels over a typical standard day of usually the most recent two weeks for a person with diabetes and helps to identify patterns and trends in glucose control. The AGP allows certain patterns of glucose levels to be identified and analyzed, such that treatment adjustments can be made, and new individual treatment goals can be defined. This helps to ensure increased treatment satisfaction and adherence, quality of life, and an improvement in metabolic management for people with diabetes., Objective: To date, a range of approaches exists for interpreting the information contained in an AGP, with different priorities given to identifying and targeting patterns of hypoglycemia and the degree of variability and stability underlying the glucose levels. The objective of the present recommendation is to describe the steps for assessing an AGP in detail and to illustrate these steps using visual examples., Conclusion: This paper describes the consensus recommendations from a group of German expert diabetologists on the necessary steps for assessing an AGP in a structured and detailed way and to explain these steps using practical clinical examples.

Competing Interests: LH is active as a consultant in the development of new diagnostic options for various companies (e.g. Roche Diagnostics, Sanofi, Abbott). He is a shareholder and consultant in Profil – Institut für Stoffwech- selforschung, Neuss, and ProSciento, San Diego, USA.DD received lecture fees from Abbott, Dexcom, Lilly, Menarini, Novo Nordisk, Roche Diagnostics, Senseonics and is a member of advisory boards of BD, Profusa, Roche and Senseonics.TS received lecture fees from Abbott, Ascensia, Astra Zeneca/Bristol- Myers Squibb, Bayer, Berlin-Chemie, Boehringer Ingelheim, Eli Lilly, Medtronic, MSD, Novartis, Novo Nordisk, Sanofi. He is a member of advisory boards of Abbott, Ascensia, Bayer Vital, Boehringer Ingelheim, Eli Lilly, Janssen, Medtronic, MSD, Novo Nordisk, Sanofi and has received support for scientific projects from: Astra Zeneca/Bristol-Myers Squibb, Becton Dickinson, Eli Lilly, MSD, Novo Nordisk, Sanofi.SVS has worked as a consultant for Abbott, Dexcom, Lilly, Medtronic, NovoNordisk and Roche for the past 3 years. SVS has received lecture fees and travel expenses from the following companies in the last 3 years: Abbott, Berlin-Chemie, BPI, Lilly, Merck-Serono, Medtronic, NovoNordisk and Pfizer. MN was a consultant and speaker for the following companies: Abbott, Berlin- Chemie, MSD, Sanofi, Medtronic, Bayer Diagnostics, Astra Zeneca. SvS is in an advisory function on the Advisory Board for the optimisation of aids, medicines and information materials for children with diabetes for several companies (Abbott, Eli Lilly, Medtronic, Novo Nordisk, Dexcom). In the last 2 years she has received lecture fees from Abbott, Berlin Chemie, Eli Lilly, Medtronic, Merck, Novo Nordisk, Roche and Sanofi. KL received lecture fees from Astra Zeneca, BDI, Lilly Deutschland, Medtronic, Menarini/Berlin-Chemie, Merck Serono, MSD SHARP & DOHME, Novo Nordisk, Roche Diabetes Care, Sanofi-Aventis. She is a member of the Advisory Boards of Roche Diabetes Care, Medtronic, Dexcom and Sanofi-Aventis. GF is the medical director of IDT (Institut für Diabe tes-Technologie Forschungs- und Entwicklungsgesellschaft mbH at the University of Ulm, Ulm), which carries out clinical studies on medical products for diabetes therapy on its own initiative or on behalf of various companies. GF/IDT has received lecture/consultation fees from Abbott, Ascensia, Dexcom, LifeScan, Menarini Diagnostics, Metronom Health, Novo Nordisk, Roche, Sanofi, Sensile and Ypsomed.

Continuous glucose monitoring (CGM) systems use trend arrows to accurately display the anticipated glucose curve for the user. These are used for both "real-time" glucose monitoring and for intermittent scanning glucose monitoring. Trend arrow data are used by people with diabetes to make corrections to their glucose control. It is essential that they are correctly interpreted when adjusting insulin doses and to ensure that appropriate treatment decisions are made. The aim of this article is to provide general treatment guidance for diabetes teams and for people with diabetes using CGM in the context of trend arrows. This is based on previous recommendations for interpreting trend arrows without losing sight of the need for individual therapy adjustment.

Competing Interests: LH is active as a consultant for various companies (e.g. Roche Diagnostics, Sanofi, Abbott) in the development of new diagnostic options. He is a shareholder and advisor at Profil – Institut für Stoffwechselforschung, Neuss, as well as ProSciento, San Diego, USA. DD received remuneration from Abbott, Dexcom, Medtronic, Novo, Roche, Senseonics and is a member of the Advisory Boards of Becton Dickinson, Roche and Senseonics. TS received remuneration from Abbott, Ascensia, Astra Zeneca/Bristol- Myers Squibb, Bayer, Berlin Chemie, Boehringer Ingelheim, Eli Lilly, Medtronic, MSD, Novartis, Novo Nordisk, and Sanofi. He is a member of the Advisory Boards of Abbott, Ascensia, Bayer Vital, Boehringer Ingelheim, Eli Lilly, Janssen, Medtronic, MSD, Novo Nordisk, and Sanofi and has received support for scientific projects from: Astra Zeneca/Bristol- Myers Squibb, Becton Dickinson, Eli Lilly, MSD, Novo Nordisk, and Sanofi. SS received remuneration from Abbott, Dexcom, Roche Diagnostics, Astra Zeneca, Novo Nordisk, MSD, and Berlin Chemie. She is a member of the Advisory Boards of Abbott, Roche Diagnostics. MN was an advisor and speaker for the following companies: Abbott, Berlin Chemie, MSD, Sanofi, Medtronic, Bayer Diagnostics, and Astra Zeneca. SvS has taken on an advisory/Advisory Board position for many companies (Abbott, Eli Lilly, Medtronic, Novo Nordisk, Roche) is active in optimizing medical aid, medicine and informative literature for children with diabetes. In the past 2 years she has received remuneration from Eli Lilly, Medtronic, Merck, Novo Nordisk, Roche and Sanofi. KL received remuneration from Bayer, BDI, Lilly Deutschland, Medtronic, Menarini/Berlin Chemie, Merck Serono, MSD SHARP & DOHME, Novo Nordisk, Roche Diabetes Care, and Sanofi. She is a member of the Advisory Boards of Roche Diabetes Care, Novo Nordisk, and Sanofi-Aventis. GF is the medical head and director of the IDT (Institut für Diabetes- Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm (Institute for Diabetes Technology, Research and Development, Ulm University)), which performs clinical studies on medical products for diabetes therapy either of its own initiative or on behalf of various companies. GF/IDT received/receives remuneration/consultancy fees from Abbott, Ascensia, Bayer, Berlin-Chemie, Becton-Dickinson, Dexcom, LifeScan, Menarini Diagnostics, Novo Nordisk, Roche, Sanofi, Sensile and Ypsomed.

Background: Composite metrics have the potential to provide more complete and clinically useful information about glycemic control than traditional individual metrics such as hemoglobin A1C, %/time/area under curve of hypoglycemia and hyperglycemia., Methods: Using five key metrics that are derived from continuous glucose monitoring, we developed a new, multicomponent composite metric, the Comprehensive Glucose Pentagon (CGP) that demonstrates glycemic control both numerically and visually. Two of its axes are composite metrics-the intensity of hypoglycemia and intensity of hyperglycemia. This approach eliminates the use of the surrogate marker, hemoglobin A1C (A1C), and replaces it with glucose-centric metrics., Results: We reanalyzed the data from two randomized control trials, the STAR 3 and ASPIRE In-Home studies using the CGP. It provided new insights into the effect of sensor-augmented pumping (SAP) in the STAR 3 trial and sensor-integrated pumping with low-glucose threshold suspend (SIP+TS) in the ASPIRE In-Home trial., Conclusions: The CGP has the potential to enable health care providers, investigators and patients to better understand the components of glycemic control and the effect of various interventions on the individual elements of that control. This can be done on a daily, weekly, or monthly basis. It also allows direct comparison of the effects on different interventions among clinical trials which is not possible using A1C alone. This new composite metric approach requires validation to determine if it provides a better predictor of long-term outcomes than A1C and/or better predictor of severe hypoglycemia than the low blood glucose index (LBGI).

Background: For decades, the major source of information used to make therapeutic decisions by patients with diabetes has been glucose measurements using capillary blood samples. Knowledge gained from clinical studies, for example, on the impact of metabolic control on diabetes-related complications, is based on such measurements. Different to traditional blood glucose measurement systems, systems for continuous glucose monitoring (CGM) measure glucose in interstitial fluid (ISF). The assumption is that glucose levels in blood and ISF are practically the same and that the information provided can be used interchangeably. Thus, therapeutic decisions, that is, the selection of insulin doses, are based on CGM system results interpreted as though they were blood glucose values., Methods: We performed a more detailed analysis and interpretation of glucose profiles obtained with CGM in situations with high glucose dynamics to evaluate this potentially misleading assumption., Results: Considering physical activity, hypoglycemic episodes, and meal-related differences between glucose levels in blood and ISF uncover clinically relevant differences that can make it risky from a therapeutic point of view to use blood glucose for therapeutic decisions., Conclusions: Further systematic and structured evaluation as to whether the use of ISF glucose is more safe and efficient when it comes to acute therapeutic decisions is necessary. These data might also have a higher prognostic relevance when it comes to long-term metabolic consequences of diabetes. In the long run, it may be reasonable to abandon blood glucose measurements as the basis for diabetes management and switch to using ISF glucose as the appropriate therapeutic target.

Background: The prevention of cardiovascular disease, including diastolic cardiac dysfunction with its high prevalence and ominous prognosis, is a therapeutic challenge for patients with type 2 diabetes. Both short and long-acting insulin analogues (AI) have been shown to reduce glucose variability and provide potential benefit for cardiovascular disease although the effects on cardiac function have not yet been evaluated. This long-term, prospective, randomized controlled trial in patients with type 2 diabetes (T2D) tested the hypothesis that a multiple daily injection regimen (MDI) with AI improves postmeal glucose excursions in comparison to human insulin (HI) and that the effects of AI improve diastolic cardiac function., Methods: For 36 months, MDI treatment in 109 T2D patients was adapted every 3 months (targets: fasting glucose ≤ 110 mg/dl, postmeal glucose ≤ 150 mg/dl) in both groups: AI (insulin detemir and insulin aspart, n = 61) and HI (NPH-insulin and regular HI, n = 48). Diastolic cardiac function (myocardial velocity E' using tissue Doppler imaging and the mitral inflow ratio E/A) and vascular function were assessed before and 2 h after a standardized breakfast (48 g carbohydrates). At baseline, both groups were comparable with regards to demographic, cardiac and metabolic data. Analysis of data included traditional statistics as well as the use of a multiple imputation technique shown in brackets [ ]., Results: At 36 months, the primary endpoint, postmeal glucose, decreased by 20 ± 62 mg/dl, p = 0.038 [p = 0.021] with AI and increased insignificantly with HI (inter-group p = 0.032 [p = 0.047]) to postmeal glucose levels of 161 ± 39 with AI vs. 195 ± 54 mg/dl with HI (inter-group p = 0.002 [p = 0.010]) whereas the levels of fasting glucose and HbA1c were comparable. With AI, postmeal E' improved by 0.6 ± 1.4 cm/s, p = 0.009 [p = 0.002] and fasting E' by 0.4 ± 1.4 cm/s, p = 0.069 [p = 0.013], however, E' remained unchanged with HI. These changes were consistent with those of the traditional parameter E/A., Conclusions: MDI with AI results in better postmeal glucose control compared to HI. The treatment with AI is associated with improved diastolic cardiac function. ClinicalTrials.gov (NTC00747409).

Aims: We aimed to identify predictors of hypoglycaemia in patients with poorly controlled type 2 diabetes treated with a single daily bolus of insulin glulisine on top of insulin glargine and oral antidiabetic drugs (basal-plus regimen)., Methods: We retrospectively analysed four large basal-plus trials including 713 patients (47% female) with type 2 diabetes, mean age of 59.9 ± 9.5 years and diabetes duration of 11 ± 7.0 years. Predictors for symptomatic, severe and nocturnal hypoglycaemia were identified by multivariate logistic regression analyses, calculation of odds ratios (ORs) and Wald 95% confidence intervals (CIs)., Results: Mean numbers of hypoglycaemic events per year were 4.64 ± 11.4 (symptomatic < 60 mg/dl), 0.59 ± 2.28 (nocturnal) and 0.03 ± 0.22 (severe). A total of 44.5% of patients reached the composite endpoint of glycated haemoglobin (HbA1c) <7.0% plus no severe hypoglycaemia, and 26.7% reached the composite of HbA1c <7.0% plus no symptomatic hypoglycaemia. Predictors of nocturnal and symptomatic hypoglycaemia were female gender (OR 1.82; 95% CI 1.07-3.11 and OR 1.89; 95% CI 1.31-2.78), diabetes duration >10 versus <5 years (OR 2.61; 95% CI 1.03-6.59 and OR 2.01; 95% CI 1.15-3.51) and higher basal insulin dose (per unit of increase) (OR 1.01; 95% CI 1.00-1.03 and OR 1.01; 95% CI 1.00-1.02). Conversely, a higher body mass index (BMI) (27-30 vs. <27 kg/m(2) and >30 vs. <27 kg/m(2) ) conferred a reduced risk of symptomatic hypoglycaemia with an OR of 0.53 (95% CI 0.31-0.90) and an OR of 0.61 (95% CI 0.39-0.97)., Conclusions: Female gender, a long diabetes duration and higher basal insulin dose were predictors of hypoglycaemia, while protection was provided by BMI > 30. These results may help to successfully establish basal-plus insulin regimen in individual patients on their transition from basal-only to basal-bolus treatment., (© 2013 John Wiley & Sons Ltd.)

In recent years, the treatment of type 1 diabetes has changed significantly. An important diagnostic and therapeutic support tool is the continuous glucose monitoring (CGM) showing its best performance when used in combination with an insulin pump therapy. Before the availability of CGM the consideration of glucose regulation and therapeutic success was based solely on selectively measured blood glucose levels and HbA1c. In contrast to the blood glucose measurements CGM measures in the interstitial fluid and opens a new dimension of diabetes therapy, we call it "glucose dynamics". The knowledge of the continuous glucose course and its trends has proved to be a highly relevant additional parameter which in practical terms has a particularly stabilizing influence on blood glucose profiles. CGM therefore offers the option of a fine-tuning of metabolic control by experienced heath care professionals and the patient, making blood glucose control in general and unplanned activities and problems in everyday life better controllable. However, despite the tremendous potential of CGM in combination with a pump therapy the basic settings of an effective pump therapy are crucial. Particularly the right basal insulin coverage as the first step is the key issue for success. With support of CGM there is an enormous potential to facilitate the adjustment and optimization of insulin pump therapy.

In people with type 2 diabetes (T2DM), hyperglycemia has a negative impact on cardiac function and cardiovascular risk. Beneficial effects of improved postprandial glycemic control have been shown for cardiovascular risk only. To demonstrate these beneficial effects on myocardial function, we investigated well-controlled T2DM patients on three insulin regimens with different impact on postprandial glucose control. For 24 months, 61 T2DM participants in a randomized study had either conventional therapy (CT) with human premixed insulin b.d. (n=20), intensified therapy (ICT) with Lispro at meals and NPH at bedtime (n=24), or supplementary therapy (SIT) with human regular insulin at meals (n=17). Metabolism and cardiovascular function were assessed before and 2 hours after a standardized carbohydrate breakfast (48 g) using tissue Doppler to measure diastolic myocardial function (E'). Age, BMI, dose of insulin, cardiovascular disease, and medication were comparable between the groups. Hb1Ac was comparable with CT, ICT, and SIT (6.6+/-0.6, 6.2+/-0.6, and 6.4+/-0.7%) and so was fasting glucose. Post-meal glucose increment was 60+/-45 mg/dl with CT, but 15+/-52 and 8+/-58 mg/dl with ICT and SIT (p<0.006). E' was significantly lower (p<0.03) with CT (6.8+/-1.0 cm/s) vs. ICT (7.7+/-1.6) and SIT (7.8+/-1.2 cm/s), and correlated with post-meal glucose (r=-0.2644, p<0.046). Intima-media thickness and arterial stiffness parameters were higher in CT (p<0.04). In T2DM patients, the long-term insulin regimens CT, ICT, and SIT achieved overall good metabolic control with significant differences, however, in postprandial glucose increments. The regimens achieving better post-meal glucose control were associated with better myocardial/vascular function.

Objective: This longitudinal study performed continuous evaluation of daily blood glucose level profiles in healthy normal-weight pregnant patients during various gestational age and determined normal levels., Study Design: Thirty-two healthy normal-weight pregnant women received a continuous glucose monitoring system (CGMS) device for periods of 72h in the 16th, 22nd, 30th and 36th weeks of gestational age and at 6 weeks after delivery. All observations took place in the outpatient clinic of the Charité hospital. The daily blood glucose level profiles obtained with the CGMS provided pre- and postprandial blood glucose levels and a mean glucose value for a 24-h period. Caloric intake was determined using detailed food logs. Additionally, a fetal biometry and an measurement of maternal weight were performed at each visit. The correlation was tested using Spearman's test., Results: The average age of the study subjects was 29.6+/-4.5. Average pre-pregnancy BMI was 22.4+/-2.5kg/m(2). The births occurred on average in the 40th week of pregnancy. Average caloric intake was 2223+/-356kcal. No significant changes in caloric intake were observed during the course of the study. The blood glucose levels showed a significant rise throughout the course of the pregnancy, going from 4.84+/-0.4mmol/l (87.2+/-7.2mg/dl) during the 30th week of pregnancy to 5.22+/-0.5mmol/l (94.0+/-9.0mg/dl) during the 36th week (p=0.002). Postpartum levels were 5.20+/-0.5mmol/l (93.7+/-9.0mg/dl) (p=0.51). Fasting blood glucose levels did not change during the course of the pregnancy. A noticeable aspect were the significantly increased fasting postpartum levels with 5.02+/-0.6mmol/l (90.4+/-10.8mg/dl) (p=0.00). Analysis of the postprandial glucose levels confirmed a rise from 5.30+/-0.6mmol/l (95.5+/-10.8mg/dl) in the 16th week to 6.14+/-0.7mmol/l (110.6+/-12.6mg/dl) in the fourth study phase (36th week), and a decrease after the birth to 5.59+/-0.6mmol/l (100.7+/-10.8mg/dl). These measurements were adapted to the gestational age., Conclusion: Continuous measured glucose levels rose during the pregnancy in healthy pregnant women in spite of normal pre-pregnancy metabolism and unchanged carbohydrate intake during gestation. These results suggest the necessity of gestational-age-dependent cut-off values.

The microdialysis technique was used for following the glucose content of the extracellular subcutaneous (SC) fluid under varying blood glucose levels in rats. The glucose content in the microdialysis perfusion fluid was continuously analyzed by means of the measuring flow chamber of an ex vivo glucose monitor. In six ChBB rats blood glucose levels were varied between 40 mg/dl and 575 mg/dl by intravenous (IV) infusion of glucose and by SC injections of insulin, respectively. After a running-in period of about half an hour, the glucose content in the perfusion fluid was closely related to the blood glucose concentration (r > 0.92) up to a time period of 6 hrs. The "relative recovery" rate of glucose by the microdialysis probe in the SC tissue varied within the 6 experimental sessions. The relative recovery rate could be shown to be not dependent on the absolute blood glucose levels in the individual rat within the glucose concentration range tested.

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