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Background:
Glucose sensors consist of real-time continuous glucose monitoring (rtCGM) and intermittently scanned CGM (isCGM). Their clinical use has been widely increasing during the past 5 years. The aim of this study is to evaluate percentage of time in range (TIR) in a large group of children with type 1 diabetes (T1D) using glucose sensors wit...
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Context 1
... differences were found in the CGM metrics among the four treatment strategies (Figure 1) Table 2 shows children and adolescents achieving CGM-based targets as suggested by recent international consensus recommendations (7) according to treatment strategies. All of the targets were achieved more frequently by subjects using rtCGM independently from the insulin-delivery system. ...
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... However, only a very small number of them, less than 25 %, managed to have HbA1c values in the desired target [17]. On the other hand, it had already been reported that using the MDI and CGM treatment modality, only 49 % of those using isCGM and 56 % of those using rtCGM achieved a percentage of time in the glucose target range 70-180 mg/dL [18]. ...
... These findings support the clear superiority of AID systems for achieving optimal glycemic control as measured by TIR and HbA1c, demonstrated by several clinical trials and studies conducted in real-world settings. [16][17][18][19][20] Additionally, recent studies investigating the clinical significance of GRI as a new metric for the evaluation of the quality and safety of glycemic control in subjects with type 1 diabetes have demonstrated that HCL systems are associated with ''low-risk'' glycemic control, 21,22 which means minimal time spent with high or low glucose levels. ...
Introduction:
To evaluate time in tight range (TITR) 70-140 mg/dL (3.9- 7.8 mmol/L), its correlation with standard continuous glucose monitoring (CGM) metrics and the clinical variables that possibly have a substantial impact on its value, in a large cohort of pediatric subjects using different treatment strategies.
Material and methods:
A total of 854 children and adolescents with type 1 diabetes were consecutively recruited in this real-world, dual-center, cross-sectional study. Participants were categorized into four treatment groups (multiple daily injections + real-time CGM, multiple daily injections + intermittently scanned CGM, sensor augmented pump, and hybrid closed loop (HCL)). Demographical and clinical data, including CGM data, were collected and analyzed.
Results:
The overall study population exhibited an average TITR of 36.4±12.8%. HCL users showed higher TITR levels compared to the other treatment groups (p<0.001). A time in range (TIR) cut-off value of 71.9% identified subjects achieving a TITR≥50% (AUC 0.98; 95%CI 0.97-0.99, p<0.001), and a strong positive correlation between these two metrics was observed (r=0.95, p<0.001). An increase in TIR of 1% was associated with 1.84 (R2 Nagelkerke=0.35, p<0.001) increased likelihood of achieving TITR≥50%. Use of HCL systems (B=7.78; p<0.001), disease duration (B=-0.26, p=0.006), coefficient of variation (B=-0.30, p=0.004), and glycated haemoglobin (B=-8.82; p<0.001) emerged as significant predictors of TITR levels.
Conclusions:
Our study highlights that most children and adolescents with type 1 diabetes present TITR levels below 50%, except those using HCL. Tailored interventions and strategies should be implemented to increase TITR.
... This positive effect is strictly associated with glucose sensor use for at least 60% of the time [2] . Similarly, combining CGM systems with continuous subcutaneous insulin infusion (CSII) reduces HbA1c and increases TIR without detrimental effects on the number of hypoglycemic events when compared with multiple daily injections (MDI) with self-monitoring of blood glucose (SMBG) or the use of CSII alone [3][4][5][6]. ...
... It has also been reported that using more complex technology (SAP versus MDI, for instance) is associated with better TIR and lower HbA1c values [6]. Here we confirmed this finding, also finding lower GRI when using AIDs compared with SAP or MDI. ...
... While it has been observed that the frequency of use decreases over time in young people with T1D, we registered high levels of use even after 2.3 ± 1.9 years. This positive outcome may be due in part to improved CGM technology and the use of education programs on CGM for children and their caregivers in pediatric centers with extensive experience using this technology for diabetes care [6]. Interestingly, diabetes duration, rather than years of CGM experience, was a determinant of reduced hassles related to CGM, probably because patients who had experienced previous less accurate CGM models are now more satisfied with the newer technologies. ...
Aims:
Continuous glucose monitoring (CGM) can improve glucometrics in children with type 1 diabetes (T1D), and its efficacy is positively related to glucose sensor use for at least 60% of the time. We therefore investigated the relationship between CGM satisfaction as assessed by a robust questionnaire and glucose control in pediatric T1D patients.
Methods:
This was a cross-sectional study of children and adolescents with T1D using CGM. The CGM Satisfaction (CGM-SAT) questionnaire was administered to patients and demographic, clinical, and glucometrics data were recorded.
Results:
Two hundred and ten consecutively enrolled patients attending 14 Italian pediatric diabetes clinics completed the CGM-SAT questionnaire. CGM-SAT scores were not associated with age, gender, annual HbA1c, % of time with an active sensor, time above range (TAR), time below range (TBR), and coefficient of variation (CV). However, CGM satisfaction was positively correlated with time in range (TIR, p < 0.05) and negatively correlated with glycemia risk index (GRI, p < 0.05).
Conclusions:
CGM seems to have a positive effect on glucose control in patients with T1D. CGM satisfaction is therefore an important patient-reported outcome to assess and it is associated with increased TIR and reduced GRI.
... Compared to MDI, CSII reflects more faithfully the physiological insulin secretion and allows more precise and accurate dose adjustments. An Italian multicenter study analyzed the difference between MDI with or without a real-time sensor and insulin pump, demonstrating that glucose profile was better with continuous glucose monitoring (realtime CGM, rtCGM, Dexcom, San Diego, CA, USA) compared to discontinuous glucose monitoring (intermittently scanned CGM, isCGM, Flash Libre), and the results were even better with automated insulin delivery device [51]. Only 28% of patients with SAP, that is, an insulin pump not connected to CGM, reach the target of TIR > 70%. ...
... The protective effect of the intensive treatment on the development of nephropathy was maintained even during the 5-7 years of follow-up [103]. A higher TIR, a parameter associated with a lower risk of developing MA [104], can be easily obtained by the simultaneous use of real-time CGM and insulin pumps compared to intermittently scanned CGM and MDI [51]. However, whether CSII is preferable to MDI to ensure better glycemic control and decrease the risk of microvascular complications in the pediatric population is still a debated issue [105][106][107]. ...
Type 1 diabetes (T1D) is one of the most common chronic diseases in childhood, with a progressively increasing incidence. T1D management requires lifelong insulin treatment and ongoing health care support. The main goal of treatment is to maintain blood glucose levels as close to the physiological range as possible, particularly to avoid blood glucose fluctuations, which have been linked to morbidity and mortality in patients with T1D. Indeed, the guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) recommend a glycated hemoglobin (HbA1c) level < 53 mmol/mol (<7.0%) for young people with T1D to avoid comorbidities. Moreover, diabetic disease strongly influences the quality of life of young patients who must undergo continuous monitoring of glycemic values and the administration of subcutaneous insulin. In recent decades, the development of automated insulin delivery (AID) systems improved the metabolic control and the quality of life of T1D patients. Continuous subcutaneous insulin infusion (CSII) combined with continuous glucose monitoring (CGM) devices connected to smartphones represent a good therapeutic option, especially in young children. In this literature review, we revised the mechanisms of the currently available technologies for T1D in pediatric age and explored their effect on short- and long-term diabetes-related comorbidities, quality of life, and life expectation.
... The first hybrid closed-loop (HCL) system, with automated insulin delivery but still requiring user inputs, was approved for the treatment of Type 1 Diabetes (T1D) by the U.S. Food and Drug Administration in September 2016. Closed-loop (CL) systems, also referred to as Automated insulin delivery (AID) systems or artificial pancreas (AP) systems, adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that translates in real time the information it receives from the real-time CGM and computes the amount of insulin to be delivered by the insulin pump [1]. Different algorithms are available; they are safe and allow youths with T1D to achieve optimal glucose control reducing glycated hemoglobin (HbA1c) by 0.3-0.7%, ...
... Different algorithms are available; they are safe and allow youths with T1D to achieve optimal glucose control reducing glycated hemoglobin (HbA1c) by 0.3-0.7%, reducing the time below range (<70 mg/dL), and increasing the time in range (70-180 mg/dL, TIR) [1,2]. The psychological benefits associated with the use of AID technology usually include improved QoL and quality of sleep, reduced diabetes distress, reduced fear of hypoglycemia, and improved safety, flexibility, and satisfaction [2]. ...
In people with type 1 diabetes, Automated Insulin Delivery (AID) systems adjust insulin delivery in response to sensor glucose data and consist of three components: an insulin pump, a continuous glucose sensor, and an algorithm that determines insulin delivery. To date, all the available AID systems require users to announce carbohydrate intake and deliver meal boluses, as well as respond to system alarms. The use of AID devices both initially and over time may be influenced by a variety of psychological factors. Analysis of patient-related outcomes should be taken into account, while recruiting applicants for the systems who are motivated and have realistic expectations in order to prevent AID dropout. We report an up-to-date summary of the available measures and semi-structured interview content to assess AID expectations, acceptance, and satisfaction using the AID systems. In conclusion, we suggest, before and after starting using AID systems, performing a specific evaluation of the related psychological implications, using validated measures and semi-structured interviews, that allows diabetes care providers to tailor their education approach to the factors that concern the patient at that time; they can teach problem-solving skills and other behavioral strategies to support sustained use of the AID system.
... The PID algorithm automatically calculates the basal insulin rates and the insulin sensitivity factor (ISF), regardless of the parameters set, based on the insulin needs of the previous 5-7 days. Insulin delivery is then adapted based on blood sugar values detected by the sensor [18]. The automatic mode works for daily insulin dosages above approximately 8 U/day; for lower dosages the instrument can be used in manual mode. ...
Type 1 diabetes (T1D) patients’ lifestyle and prognosis has remarkably changed over the years, especially after the introduction of insulin pumps, in particular advanced hybrid closed loop systems (AHCL). Emerging data in literature continuously confirm the improvement of glycemic control thanks to the technological evolution taking place in this disease. As stated in previous literature, T1D patients are seen to be more satisfied thanks to the use of these devices that ameliorate not only their health but their daily life routine as well. Limited findings regarding the use of new devices in different age groups and types of patients is their major limit. This review aims to highlight the main characteristics of each Automated Insulin Delivery (AID) system available for patients affected by Type 1 Diabetes Mellitus. Our main goal was to particularly focus on these systems’ efficacy and use in different age groups and populations (i.e., children, pregnant women). Recent studies are emerging that demonstrate their efficacy and safety in younger patients and other forms of diabetes.
... For our sampling window of school hours (8 AM to 3 PM), the small proportion of children (5%) in our study meeting a TIR of 70% was striking. In pediatric cohorts without an automated insulin delivery (AID) system, mean TIR has been reported to be 40-61%, with values difering by country and by use of multiple daily injections or insulin pumps [19][20][21]. In one real-world European cohort, 14% of children using real-time CGM with multiple daily injections and 28% of children using an insulin pump with real-time CGM achieved a TIR of 70%, though they did not impose any time-period restrictions and their sample included all youth less than 18 years of age [21]. ...
... In pediatric cohorts without an automated insulin delivery (AID) system, mean TIR has been reported to be 40-61%, with values difering by country and by use of multiple daily injections or insulin pumps [19][20][21]. In one real-world European cohort, 14% of children using real-time CGM with multiple daily injections and 28% of children using an insulin pump with real-time CGM achieved a TIR of 70%, though they did not impose any time-period restrictions and their sample included all youth less than 18 years of age [21]. Historically, European children tend to achieve hemoglobin A1c targets more often than children in the United States [22]. ...
Objective. Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and nonschool time. Methods. We conducted a retrospective analysis of CGM metrics in children 7–12 years (n = 217, diabetes duration 3.5 ± 2.5 years, hemoglobin A1c 7.5 ± 0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school. Results. Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) were lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school. Conclusion. Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines. Keywords: type 1 diabetes, school health, continuous glucose monitoring, time in range, glycemic control.
... Evolving technologies offer the potential to highly improve glycemic control. Systems which integrate insulin infusion with continuous glucose monitoring (CGM) are now widely used by T1D patients (1)(2)(3)(4)(5). ...
Background and aimsTandem Control-IQ and MiniMed 780G are the main Advanced Hybrid Closed Loop (AHCL) systems currently available in pediatric and adult patients with Type 1 Diabetes (T1D). The aim of our study was to evaluate glycemic control after 1-year of follow-up extending our previous study of 1-month comparison between the two systems.Methods
We retrospectively compared clinical and continuous glucose monitoring (CGM) data from the patients included in the previous study which have completed 1-year observation period. The study population consisted of 74 patients, 42 Minimed 780G users and 32 Tandem Control-IQ users. Linear mixed models with random intercept were performed to study the variations over time and the interaction between time and system; Mann-Whitney or T-test were used to compare systems at 1-year.ResultsBoth systems have been shown to be effective in maintaining the glycemic improvement achieved one month after starting AHCL. Significant changes over time were observed for TIR, TAR, TAR>250mg/dl, average glucose levels and SD (p<0.001). At 1-year follow-up Minimed 780G obtained better improvement in TIR (p<0.001), TAR (p=0.002), TAR>250mg/dl (p=0.001), average glucose levels (p<0.001). The comparison of the glycemic parameters at 1-year showed a significant superiority of Minimed 780G in terms of TIR (71% vs 68%; p=0.001), TAR (p=0.001), TAR>250 (p=0.009), average glucose levels(p=0.001) and SD (p=0.031).Conclusions
The use of AHCL systems led to a significant improvement of glycemic control at 1-month, which is maintained at 1-year follow-up. MiniMed is more effective than Tandem in reaching the International recommended glycemic targets. Continuous training and education in the use of technology is essential to get the best out of the most advanced technological tools.
... Careful attention should be paid to severe diabetic distress in adults with T1D. There was no marked difference in the TIR between the isCGM-and SMBG-based insulin dosing groups in children with T1D attending a summer camp (39) or in a real-world setting (40). This classification might help tailor diabetes management, but a further examination, including randomized controlled trials, will be required to confirm these issues. ...
Objective This study investigated self-monitoring of blood glucose (SMBG) adherence and flash glucose monitoring patterns using a cluster analysis in Japanese type 1 diabetes (T1D) patients with intermittently scanned continuous glucose monitoring (isCGM).
Methods We measured SMBG adherence and performed a data-driven cluster analysis using a hierarchical clustering in T1D patients from Japan using the FreeStyle Libre system. Clusters were based on three variables (testing glucose frequency and referred Libre data for hyperglycemia or hypoglycemia).
Patients We enrolled 209 participants. Inclusion criteria were patients with T1D, duration of isCGM use ≥3 months, age ≥20 years old, and regular attendance at the collaborating center.
Results The rate of good adherence to SMBG recommended by a doctor was 85.0%. We identified three clusters: cluster 1 (low SMBG test frequency but high reference to Libre data, 17.7%), cluster 2 (high SMBG test frequency but low reference to Libre data, 34.0%), and cluster 3 (high SMBG test frequency and high reference to Libra data, 48.3%). Compared with other clusters, individuals in cluster 1 were younger, those in cluster 2 had a shorter Libre duration, and individuals in cluster 3 had lower time-in-range, higher severe diabetic distress, and high intake of snacks and sweetened beverages. There were no marked differences in the incidence of diabetic complications and rate of wearing the Libre sensor among the clusters.
Conclusions We stratified the patients into three subgroups with varied clinical characteristics and CGM metrics. This new substratification might help tailor diabetes management of patients with T1D using isCGM.
... Thus, in our situation, the delayed diagnosis was not due to medical professionals confusing the signs of T1DM with those of COVID-19. More complicated relationships seem to have been at play, such as those that affect families' propensity to seek medical attention and the availability of health resources (16) . ...
