BACKGROUND: Advances in paediatric type 1 diabetes management and increased use of diabetes technology have led to improvements in glycaemia, reduced risk of severe hypoglycaemia, and improved quality of life. Since 1993, progressively lower HbA1c targets have been set. The aim of this study was to perform a longitudinal analysis of HbA1c, treatment regimens, and acute complications between 2013 and 2022 using data from eight national and one international paediatric diabetes registries. METHODS: In this longitudinal analysis, we obtained data from the Australasian Diabetes Data Network, Czech National Childhood Diabetes Register, Danish Registry of Childhood and Adolescent Diabetes, Diabetes Prospective Follow-up Registry, Norwegian Childhood Diabetes Registry, England and Wales' National Paediatric Diabetes Audit, Swedish Childhood Diabetes Registry, T1D Exchange Quality Improvement Collaborative, and the SWEET initiative. All children (aged ≤18 years) with type 1 diabetes with a duration of longer than 3 months were included. Investigators compared data from 2013 to 2022; analyses performed on data were pre-defined and conducted separately by each respective registry. Data on demographics, HbA1c, treatment regimen, and event rates of diabetic ketoacidosis and severe hypoglycaemia were collected. ANOVA was performed to compare means between registries and years. Joinpoint regression analysis was used to study significant breakpoints in temporal trends. FINDINGS: In 2022, data were available for 109 494 children from the national registries and 35 590 from SWEET. Between 2013 and 2022, the aggregated mean HbA1c decreased from 8·2% (95% CI 8·1-8·3%; 66·5 mmol/mol [65·2-67·7]) to 7·6% (7·5-7·7; 59·4mmol/mol [58·2-60·5]), and the proportion of participants who had achieved HbA1c targets of less than 7% (<53 mmol/mol) increased from 19·0% to 38·8% (p<0·0001). In 2013, the aggregate event rate of severe hypoglycaemia rate was 3·0 events per 100 person-years (95% CI 2·0-4·9) compared with 1·7 events per 100 person-years (1·0-2·7) in 2022. In 2013, the aggregate event rate of diabetic ketoacidosis was 3·1 events per 100 person-years (95% CI 2·0-4·8) compared with 2·2 events per 100 person-years (1·4-3·4) in 2022. The proportion of participants with insulin pump use increased from 42·9% (95% CI 40·4-45·5) in 2013 to 60·2% (95% CI 57·9-62·6) in 2022 (mean difference 17·3% [13·8-20·7]; p<0·0001), and the proportion of participants using continuous glucose monitoring (CGM) increased from 18·7% (95% CI 9·5-28·0) in 2016 to 81·7% (73·0-90·4) in 2022 (mean difference 63·0% [50·3-75·7]; p<0·0001). INTERPRETATION: Between 2013 and 2022, glycaemic outcomes have improved, parallel to increased use of diabetes technology. Many children had HbA1c higher than the International Society for Pediatric and Adolescent Diabetes (ISPAD) 2022 target. Reassuringly, despite targeting lower HbA1c, severe hypoglycaemia event rates are decreasing. Even for children with type 1 diabetes who have access to specialised diabetes care and diabetes technology, further advances in diabetes management are required to assist with achieving ISPAD glycaemic targets. FUNDING: None. TRANSLATIONS: For the Norwegian, German, Czech, Danish and Swedish translations of the abstract see Supplementary Materials section.
- MeSH
- diabetes mellitus 1. typu * epidemiologie krev farmakoterapie MeSH
- dítě MeSH
- glykovaný hemoglobin * analýza MeSH
- hypoglykemie epidemiologie MeSH
- hypoglykemika * terapeutické užití MeSH
- kojenec MeSH
- krevní glukóza * analýza MeSH
- lidé MeSH
- longitudinální studie MeSH
- mladiství MeSH
- předškolní dítě MeSH
- registrace * statistika a číselné údaje MeSH
- regulace glykemie statistika a číselné údaje metody MeSH
- výsledek terapie MeSH
- Check Tag
- dítě MeSH
- kojenec MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- předškolní dítě MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Klinický problém hypoglykémie je prítomný v diabetológii už od objavu inzulínu pred viac ako 100 rokmi. Nové technológie v manažmente diabetu, akými sú kontinuálne monitorovanie glukózy (Continuous Glucose Monitoring – CGM) alebo inzulínové pumpy integrované s CGM technológiou do hybridných uzavretých systémov na podávanie inzulínu (Advanced Hybrid Closed Loop Systems – AHCL) majú jednoznačné dôkazy pre signifikantnú a klinicky relevantnú redukciu výskytu hypoglykémie. CGM technológia, okrem samotného efektu na redukciu výskytu hypoglykémie, pomohla v prvom rade odhaliť jej skutočnú a predtým nepoznanú mieru výskytu. Autor v prehľadovom článku diskutuje relevantné klinické štúdie a dáta z reálnej praxe (Real World Evidence – RWE) a ich význam pre klinickú prax.
The clinical problem of hypoglycaemia has been with us since the discovery of insulin more than 100 years ago. Modern diabetes technologies, such as continuous glucose monitoring (CGM) or advanced hybrid closed loop systems (AHCL), have unequivocal evidence for significant and clinically meaningful reduction of hypoglycaemia. On top of that, CGM technology has helped us to discover the real extent of the hypoglycaemia ‘problem’ in the lives of our patients. This article reviews the relevant clinical studies and real world evidence data and their impact on clinical practice.
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.
- MeSH
- diabetes mellitus * farmakoterapie MeSH
- elektronické zdravotní záznamy MeSH
- krevní glukóza MeSH
- lidé MeSH
- selfmonitoring glykemie * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
- Geografické názvy
- Spojené království MeSH
- Klíčová slova
- bempedová kyselina,
- MeSH
- ezetimib terapeutické užití MeSH
- hypolipidemika * aplikace a dávkování ekonomika farmakologie terapeutické užití MeSH
- kardiovaskulární nemoci * farmakoterapie komplikace mortalita prevence a kontrola MeSH
- klinická studie jako téma MeSH
- kombinovaná farmakoterapie metody MeSH
- komplikace diabetu MeSH
- kongresy jako téma MeSH
- krevní glukóza účinky léků MeSH
- LDL-cholesterol krev účinky léků MeSH
- lidé MeSH
- rizikové faktory kardiovaskulárních chorob MeSH
- statiny terapeutické užití MeSH
- Check Tag
- lidé MeSH
- Klíčová slova
- teplizumab,
- MeSH
- diabetes mellitus 1. typu * diagnóza prevence a kontrola terapie MeSH
- diabetes mellitus MeSH
- glykovaný hemoglobin analýza MeSH
- humanizované monoklonální protilátky terapeutické užití MeSH
- kontinuální monitorování glukózy MeSH
- krevní glukóza MeSH
- lidé MeSH
- regulace glykemie MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs). METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy. RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose. CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.
- MeSH
- diabetes mellitus * krev diagnóza MeSH
- krevní glukóza * analýza MeSH
- lidé MeSH
- reprodukovatelnost výsledků MeSH
- selfmonitoring glykemie * přístrojové vybavení normy MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
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.
- MeSH
- diabetes mellitus 1. typu * farmakoterapie MeSH
- dospělí MeSH
- glykovaný hemoglobin MeSH
- hypoglykemika terapeutické užití MeSH
- inzulin terapeutické užití MeSH
- inzulinové infuzní systémy MeSH
- inzuliny * MeSH
- krevní glukóza MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- prospektivní studie MeSH
- selfmonitoring glykemie metody MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- Publikační typ
- časopisecké články MeSH
- MeSH
- analýza dat MeSH
- diabetes mellitus terapie MeSH
- krevní glukóza * analýza MeSH
- lidé MeSH
- regulace glykemie MeSH
- selfmonitoring glykemie metody MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- přehledy MeSH
- MeSH
- diabetes mellitus diagnóza terapie MeSH
- glykovaný hemoglobin analýza MeSH
- kontinuální monitorování glukózy MeSH
- krevní glukóza * analýza MeSH
- lidé MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- komentáře MeSH
- souhrny MeSH
