Long-term use of Minimed™ 780G in children and adolescents with type 1 diabetes under real-world conditions: The benefits of optimal settings

IF 5.7 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM Diabetes, Obesity & Metabolism Pub Date : 2025-01-31 DOI:10.1111/dom.16226
Bruno Bombaci MD, Stefano Passanisi PhD, Marco Calderone MD, Fabio Macrì MD, Fortunato Lombardo MD, Giuseppina Salzano PhD
{"title":"Long-term use of Minimed™ 780G in children and adolescents with type 1 diabetes under real-world conditions: The benefits of optimal settings","authors":"Bruno Bombaci MD,&nbsp;Stefano Passanisi PhD,&nbsp;Marco Calderone MD,&nbsp;Fabio Macrì MD,&nbsp;Fortunato Lombardo MD,&nbsp;Giuseppina Salzano PhD","doi":"10.1111/dom.16226","DOIUrl":null,"url":null,"abstract":"<p>The MiniMed 780G™ (Medtronic, Northridge, CA), launched in 2020, is currently available in more than 40 countries worldwide. This device uses a proportional–integral–derivative algorithm combined with fuzzy logic features, adjusting basal insulin delivery rate based on customizable glycaemic targets (100, 110 or 120 mg/dL) and delivering automated correction boluses. Furthermore, the algorithm features meal detection and safe bolus technologies to minimize post-meal glycaemic excursions.<span><sup>1</sup></span></p><p>Although numerous experimental and real-world studies have demonstrated the benefits related to the MiniMed 780G™ use in youth with type 1 diabetes (T1D), there is still no strong evidence of its sustained effectiveness beyond 1 year of use.<span><sup>2-5</sup></span></p><p>The aim of this study is to evaluate glycaemic outcomes in a population of children and adolescents with T1D during their first 24 months of Minimed 780G™ system use in real-world conditions.</p><p>A single-centre, longitudinal, real-world design was adopted. Children and adolescents with T1D who began using the Minimed™ 780G system between November 2020 and May 2024 were enrolled. Local ethical committee approval was obtained (n. 39-23). Participants were included if they met the following criteria: a diagnosis of T1D, age &lt;18 years at the time of starting automated insulin delivery (AID) therapy, and provided informed consent for remote access to clinical data.</p><p>The following time points were considered across the study period: 2 weeks preceding automatic mode activation (T0), 2 weeks after activation of the automatic mode (T1), 12 months after automatic mode activation (T2), 24 months post-activation (T3). Prior to May 2022, all participants used a 3-day infusion set, whereas afterward, all users were gradually switched to a 7-day infusion set.</p><p>At each time point, we collected CGM metrics including mean sensor glucose and its standard deviation (SD), percentage of time between 70 and 180 mg/dL (TIR), percentage of time between 70 and 140 mg/dL (TITR), percentage of time above 180 mg/dL (TAR), percentage of time between 180 and 250 mg/dL (TAR<sub>Level1</sub>), percentage of time above 250 mg/dL (TAR<sub>Level2</sub>), percentage of time below 70 mg/dL (TBR), percentage of time between 54 and 70 mg/dL (TBR<sub>Level1</sub>), percentage of time below 54 mg/dL (TBR<sub>Level2</sub>), glucose management indicator (GMI), coefficient of variation (CV) and glycaemia risk index (GRI). All metrics were acquired from CareLink System® platform, considering time intervals of 15 days.</p><p>Numerical data were expressed as mean and standard deviation, while categorical variables were reported as absolute frequencies and percentages. A parametric approach was adopted since the numerical variables followed a normal distribution, as confirmed by the Kolmogorov–Smirnov test. To compare clinical variables, including glycaemic control indicators, across the different time points, paired-samples Student <i>t</i> test was used to compare baseline and the first 2 weeks of automatic mode use, and repeated-measures analysis of variance (ANOVA) was applied to compare T1, T2 and T3. Post hoc pairwise comparisons were conducted using Tukey test, with Bonferroni correction applied for multiple comparisons, yielding a corrected significance level of 0.017.</p><p>At time points T1, T2 and T3, clinical variables and system settings were compared between achievers and non-achievers of CGM targets of TITR ≥50% and TBR ≤4% using Student <i>t</i> test for numerical variables and the chi-square test for categorical variables. Additionally, a logistic regression model was applied to identify baseline predictors for the simultaneous achievement of TITR ≥50% and TBR ≤4%. Statistical analyses were performed using IBM SPSS software for Windows, Version 22 (IBM Corp., Armonk, NY, United States), with a <i>p</i> value of less than 0.05 considered statistically significant.</p><p>We included 111 children and adolescents starting therapy with the Minimed™ 780G, with a slight prevalence of males (55.0%). The mean age of the study participants was 12.7 ± 3.3 years, with an average duration of diabetes of 4.7 ± 3.4 years. Prior to using the Minimed™ 780G system, 46 individuals (41.4%) were on multiple daily insulin injections, while 65 (58.6%) were already using an insulin pump. The average HbA1c in the year preceding enrollment was 7.2% ± 0.9%. At T0, the mean BMI <i>Z</i>-score was 0.8 ± 1.2.</p><p>Based on the time of initiation of device use, all participants completed a 6-month observational period, 97 (87.4%) achieved 12-month use of the Minimed 780G, and 46 (41.4%) completed the 24-month follow-up period.</p><p>Immediately after the switch from manual to automatic mode, we observed significant improvement of TBR<sub>Level1</sub> (2.2 ± 1.7 vs. 1.9% ± 1.7%; <i>p</i> = 0.015), TBR (2.6 ± 2.2 vs. 2.4% ± 2.4%; <i>p</i> = 0.045), TITR (43.1% ± 10.1% vs. 51.5% ± 8.6%; <i>p</i> &lt;0.001), TIR (66.9 ± 10.8 vs. 76.0% ± 7.6%; <i>p</i> &lt;0.001), TAR<sub>Level1</sub> (24.0 ± 7.2 vs. 18.3 ± 5.8; <i>p</i> &lt;0.001), TAR<sub>Level2</sub> (6.5 ± 4.8 vs. 3.6% ± 3.0%; <i>p</i> &lt;0.001), TAR (30.6 ± 10.8 vs. 21.9% ± 7.8%; <i>p</i> &lt;0.001), CV (34.6 ± 4.0 vs. 33.0% ± 4.0%; <i>p</i> &lt;0.001), mean sensor glucose (156.5 ± 15.6 vs. 144.7 ± 11.3 mg/dL; <i>p</i> &lt;0.001) and GRI (36.3 ± 12.5 vs. 23.4 ± 8.0; <i>p</i> &lt;0.001).</p><p>Glucose metrics remained statistically unchanged over the subsequent 24 months of follow-up, with no significant differences between T1, T2 and T3 (Figure 1).</p><p>When comparing achievers and non-achievers of TITR ≥50% and a TBR ≤4% at T1, we found lower percentage of automatic correction boluses (<i>p</i> = 0.009) and more frequent use of active insulin time (AIT) 2 h (<i>p</i> = 0.005) and optimal settings, consisting of both AIT 2 h and SmartGuard target 100 mg/dL (<i>p</i> = 0.003) among achievers. Similar findings were observed at T2 (Table 1).</p><p>The logistic regression analysis did not identify any baseline predictors for the simultaneous achievement of TITR ≥50% and TBR ≤4%, except for an inverse association between the mean HbA1c value in the 12 months prior to enrollment and target achievement at T2 (<i>B</i> = −1.126; 95% CI 0.173–0.607; <i>p</i> &lt;0.001).</p><p>Our data confirm the immediate benefits of the Minimed™ 780G use in automatic mode, resulting in significant improvements of key CGM metrics, including TIR and TITR, and reduction in hypoglycaemic events. These results align with previous studies that reported substantial short-term benefits of AID systems in youths, starting within 2 weeks after the activation of automatic mode.<span><sup>5, 6</sup></span></p><p>Notably, our data revealed that improvements in CGM data were sustained up to 24 months, with no significant differences between 12- and 24-month metrics. Similarly, a prospective study on 50 youths showed sustained performance of the device in terms of TIR across 2-year study period.<span><sup>7</sup></span> Another follow-up analysis on 35 preschoolers participating to a non-randomized, prospective, single-arm clinical trial, revealed persistence of positive effect of the Minimed™ 780G on glycaemic control up to 18 months.<span><sup>8</sup></span> The stability of glycaemic outcomes up to 2 years is particularly noteworthy given the real-world challenges of device adherence and behavioural variability in children and adolescents. Diabetes management in youths is often characterized by numerous challenges, including specific physiological factors that bring significant daily glucose excursions and psychological and behavioural issues typical of this age, with a significant portion of adolescents not achieving recommended glycaemic targets.<span><sup>9, 10</sup></span></p><p>In our analysis, we focused on the characteristics of subjects achieving a TITR of 50% without exceeding the recommended threshold for time spent in hypoglycemia. TITR has been recently proposed as an alternative metric to TIR for clinical practice, as it more accurately reflects time spent in the euglycaemic range. Interestingly, we found that participants who met glycaemic targets of TITR ≥50% and TBR ≤4% were more likely to use more stringent device settings. However, this association was not confirmed after 24 months. Further studies with larger cohorts are needed to validate this trend and to elucidate potential underlying determinants. AIT of 2 h along with SmartGuard target set at 100 mg/dL have already been identified as predictors of improved TIR among 12 870 Minimed™ 780G users.<span><sup>11</sup></span> A subanalysis focusing on individuals aged ≤15 years from the same population further demonstrated that the percentage of individuals simultaneously achieving the recommended targets for TIR, TBR and GMI was significantly higher among those using optimal settings than the general population.<span><sup>12</sup></span> Similarly, consistent use of AIT of 2 h and a SmartGuard target of 100 mg/dL has been strongly associated to higher TITR levels.<span><sup>6</sup></span></p><p>Finally, our analysis revealed a reduced percentage of automatic correction boluses among participants who simultaneously achieved TITR and TBR targets. This finding was consistent across all time points and aligns with previous studies demonstrating an association between a higher proportion of automatic correction boluses and suboptimal glycaemic outcomes among AID users.<span><sup>5, 11</sup></span> A study on youths with T1D using the MiniMed™ 780G reported that an automatic correction bolus percentage below 30% was associated with higher levels of TIR and TITR.<span><sup>13</sup></span> This trend underscores the critical role of user-initiated boluses and accurate carbohydrate counting in achieving optimal glycaemic control.<span><sup>14</sup></span></p><p>Despite its strengths, our study has some limitations, including the decreasing sample size over the 24-month period, which reflects the fact that some participants were enrolled more recently and the single-center design, that may limit the generalizability of the findings.</p><p>In conclusion, our study demonstrated that the Minimed™ 780G provides sustained improvements in glycaemic control for up to 24 months in children and adolescents with T1D. Achieving time in tight range targets without increasing the risk of hypoglycemia is strongly associated with the use of optimal device settings.</p><p>BB and SP conceptualized the study and wrote the first draft of the article. FM and MC researched data. GS reviewed and edited the manuscript. FL contributed to discussion and reviewed and edited the manuscript. All authors approved the final version of the manuscript. SP is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.</p><p>No funding was received for this article.</p><p>BB reports travel grants from Movi SpA and Abbott. FL has received speaker and consultant honoraria from Sanofi and speaking honoraria from Movi SpA. SP received speaking honoraria from Movi SpA.</p>","PeriodicalId":158,"journal":{"name":"Diabetes, Obesity & Metabolism","volume":"27 4","pages":"2309-2312"},"PeriodicalIF":5.7000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/dom.16226","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes, Obesity & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://dom-pubs.onlinelibrary.wiley.com/doi/10.1111/dom.16226","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
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Abstract

The MiniMed 780G™ (Medtronic, Northridge, CA), launched in 2020, is currently available in more than 40 countries worldwide. This device uses a proportional–integral–derivative algorithm combined with fuzzy logic features, adjusting basal insulin delivery rate based on customizable glycaemic targets (100, 110 or 120 mg/dL) and delivering automated correction boluses. Furthermore, the algorithm features meal detection and safe bolus technologies to minimize post-meal glycaemic excursions.1

Although numerous experimental and real-world studies have demonstrated the benefits related to the MiniMed 780G™ use in youth with type 1 diabetes (T1D), there is still no strong evidence of its sustained effectiveness beyond 1 year of use.2-5

The aim of this study is to evaluate glycaemic outcomes in a population of children and adolescents with T1D during their first 24 months of Minimed 780G™ system use in real-world conditions.

A single-centre, longitudinal, real-world design was adopted. Children and adolescents with T1D who began using the Minimed™ 780G system between November 2020 and May 2024 were enrolled. Local ethical committee approval was obtained (n. 39-23). Participants were included if they met the following criteria: a diagnosis of T1D, age <18 years at the time of starting automated insulin delivery (AID) therapy, and provided informed consent for remote access to clinical data.

The following time points were considered across the study period: 2 weeks preceding automatic mode activation (T0), 2 weeks after activation of the automatic mode (T1), 12 months after automatic mode activation (T2), 24 months post-activation (T3). Prior to May 2022, all participants used a 3-day infusion set, whereas afterward, all users were gradually switched to a 7-day infusion set.

At each time point, we collected CGM metrics including mean sensor glucose and its standard deviation (SD), percentage of time between 70 and 180 mg/dL (TIR), percentage of time between 70 and 140 mg/dL (TITR), percentage of time above 180 mg/dL (TAR), percentage of time between 180 and 250 mg/dL (TARLevel1), percentage of time above 250 mg/dL (TARLevel2), percentage of time below 70 mg/dL (TBR), percentage of time between 54 and 70 mg/dL (TBRLevel1), percentage of time below 54 mg/dL (TBRLevel2), glucose management indicator (GMI), coefficient of variation (CV) and glycaemia risk index (GRI). All metrics were acquired from CareLink System® platform, considering time intervals of 15 days.

Numerical data were expressed as mean and standard deviation, while categorical variables were reported as absolute frequencies and percentages. A parametric approach was adopted since the numerical variables followed a normal distribution, as confirmed by the Kolmogorov–Smirnov test. To compare clinical variables, including glycaemic control indicators, across the different time points, paired-samples Student t test was used to compare baseline and the first 2 weeks of automatic mode use, and repeated-measures analysis of variance (ANOVA) was applied to compare T1, T2 and T3. Post hoc pairwise comparisons were conducted using Tukey test, with Bonferroni correction applied for multiple comparisons, yielding a corrected significance level of 0.017.

At time points T1, T2 and T3, clinical variables and system settings were compared between achievers and non-achievers of CGM targets of TITR ≥50% and TBR ≤4% using Student t test for numerical variables and the chi-square test for categorical variables. Additionally, a logistic regression model was applied to identify baseline predictors for the simultaneous achievement of TITR ≥50% and TBR ≤4%. Statistical analyses were performed using IBM SPSS software for Windows, Version 22 (IBM Corp., Armonk, NY, United States), with a p value of less than 0.05 considered statistically significant.

We included 111 children and adolescents starting therapy with the Minimed™ 780G, with a slight prevalence of males (55.0%). The mean age of the study participants was 12.7 ± 3.3 years, with an average duration of diabetes of 4.7 ± 3.4 years. Prior to using the Minimed™ 780G system, 46 individuals (41.4%) were on multiple daily insulin injections, while 65 (58.6%) were already using an insulin pump. The average HbA1c in the year preceding enrollment was 7.2% ± 0.9%. At T0, the mean BMI Z-score was 0.8 ± 1.2.

Based on the time of initiation of device use, all participants completed a 6-month observational period, 97 (87.4%) achieved 12-month use of the Minimed 780G, and 46 (41.4%) completed the 24-month follow-up period.

Immediately after the switch from manual to automatic mode, we observed significant improvement of TBRLevel1 (2.2 ± 1.7 vs. 1.9% ± 1.7%; p = 0.015), TBR (2.6 ± 2.2 vs. 2.4% ± 2.4%; p = 0.045), TITR (43.1% ± 10.1% vs. 51.5% ± 8.6%; p <0.001), TIR (66.9 ± 10.8 vs. 76.0% ± 7.6%; p <0.001), TARLevel1 (24.0 ± 7.2 vs. 18.3 ± 5.8; p <0.001), TARLevel2 (6.5 ± 4.8 vs. 3.6% ± 3.0%; p <0.001), TAR (30.6 ± 10.8 vs. 21.9% ± 7.8%; p <0.001), CV (34.6 ± 4.0 vs. 33.0% ± 4.0%; p <0.001), mean sensor glucose (156.5 ± 15.6 vs. 144.7 ± 11.3 mg/dL; p <0.001) and GRI (36.3 ± 12.5 vs. 23.4 ± 8.0; p <0.001).

Glucose metrics remained statistically unchanged over the subsequent 24 months of follow-up, with no significant differences between T1, T2 and T3 (Figure 1).

When comparing achievers and non-achievers of TITR ≥50% and a TBR ≤4% at T1, we found lower percentage of automatic correction boluses (p = 0.009) and more frequent use of active insulin time (AIT) 2 h (p = 0.005) and optimal settings, consisting of both AIT 2 h and SmartGuard target 100 mg/dL (p = 0.003) among achievers. Similar findings were observed at T2 (Table 1).

The logistic regression analysis did not identify any baseline predictors for the simultaneous achievement of TITR ≥50% and TBR ≤4%, except for an inverse association between the mean HbA1c value in the 12 months prior to enrollment and target achievement at T2 (B = −1.126; 95% CI 0.173–0.607; p <0.001).

Our data confirm the immediate benefits of the Minimed™ 780G use in automatic mode, resulting in significant improvements of key CGM metrics, including TIR and TITR, and reduction in hypoglycaemic events. These results align with previous studies that reported substantial short-term benefits of AID systems in youths, starting within 2 weeks after the activation of automatic mode.5, 6

Notably, our data revealed that improvements in CGM data were sustained up to 24 months, with no significant differences between 12- and 24-month metrics. Similarly, a prospective study on 50 youths showed sustained performance of the device in terms of TIR across 2-year study period.7 Another follow-up analysis on 35 preschoolers participating to a non-randomized, prospective, single-arm clinical trial, revealed persistence of positive effect of the Minimed™ 780G on glycaemic control up to 18 months.8 The stability of glycaemic outcomes up to 2 years is particularly noteworthy given the real-world challenges of device adherence and behavioural variability in children and adolescents. Diabetes management in youths is often characterized by numerous challenges, including specific physiological factors that bring significant daily glucose excursions and psychological and behavioural issues typical of this age, with a significant portion of adolescents not achieving recommended glycaemic targets.9, 10

In our analysis, we focused on the characteristics of subjects achieving a TITR of 50% without exceeding the recommended threshold for time spent in hypoglycemia. TITR has been recently proposed as an alternative metric to TIR for clinical practice, as it more accurately reflects time spent in the euglycaemic range. Interestingly, we found that participants who met glycaemic targets of TITR ≥50% and TBR ≤4% were more likely to use more stringent device settings. However, this association was not confirmed after 24 months. Further studies with larger cohorts are needed to validate this trend and to elucidate potential underlying determinants. AIT of 2 h along with SmartGuard target set at 100 mg/dL have already been identified as predictors of improved TIR among 12 870 Minimed™ 780G users.11 A subanalysis focusing on individuals aged ≤15 years from the same population further demonstrated that the percentage of individuals simultaneously achieving the recommended targets for TIR, TBR and GMI was significantly higher among those using optimal settings than the general population.12 Similarly, consistent use of AIT of 2 h and a SmartGuard target of 100 mg/dL has been strongly associated to higher TITR levels.6

Finally, our analysis revealed a reduced percentage of automatic correction boluses among participants who simultaneously achieved TITR and TBR targets. This finding was consistent across all time points and aligns with previous studies demonstrating an association between a higher proportion of automatic correction boluses and suboptimal glycaemic outcomes among AID users.5, 11 A study on youths with T1D using the MiniMed™ 780G reported that an automatic correction bolus percentage below 30% was associated with higher levels of TIR and TITR.13 This trend underscores the critical role of user-initiated boluses and accurate carbohydrate counting in achieving optimal glycaemic control.14

Despite its strengths, our study has some limitations, including the decreasing sample size over the 24-month period, which reflects the fact that some participants were enrolled more recently and the single-center design, that may limit the generalizability of the findings.

In conclusion, our study demonstrated that the Minimed™ 780G provides sustained improvements in glycaemic control for up to 24 months in children and adolescents with T1D. Achieving time in tight range targets without increasing the risk of hypoglycemia is strongly associated with the use of optimal device settings.

BB and SP conceptualized the study and wrote the first draft of the article. FM and MC researched data. GS reviewed and edited the manuscript. FL contributed to discussion and reviewed and edited the manuscript. All authors approved the final version of the manuscript. SP is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

No funding was received for this article.

BB reports travel grants from Movi SpA and Abbott. FL has received speaker and consultant honoraria from Sanofi and speaking honoraria from Movi SpA. SP received speaking honoraria from Movi SpA.

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在现实条件下长期使用Minimed™780G治疗1型糖尿病儿童和青少年:最佳设置的益处
MiniMed 780G™(Medtronic, Northridge, CA)于2020年推出,目前在全球40多个国家有售。该设备使用比例-积分-导数算法结合模糊逻辑特征,根据可定制的血糖目标(100,110或120mg /dL)调整基础胰岛素输送率,并提供自动校正丸。此外,该算法还具有膳食检测和安全丸技术,以最大限度地减少餐后血糖漂移。尽管大量的实验和现实研究已经证明了MiniMed 780G™在青少年1型糖尿病(T1D)患者中的益处,但仍没有强有力的证据表明其使用1年以上的持续有效性。2-5本研究的目的是评估在现实条件下使用Minimed 780G™系统的前24个月T1D儿童和青少年人群的血糖结局。采用单中心、纵向、真实世界设计。在2020年11月至2024年5月期间开始使用Minimed™780G系统的T1D儿童和青少年被纳入研究。获得当地伦理委员会的批准(n. 39-23)。如果参与者符合以下标准:诊断为T1D,开始自动胰岛素输送(AID)治疗时年龄≥18岁,并提供远程访问临床数据的知情同意。在整个研究期间考虑以下时间点:自动模式激活前2周(T0),自动模式激活后2周(T1),自动模式激活后12个月(T2),激活后24个月(T3)。在2022年5月之前,所有参与者使用3天输液器,而之后,所有用户逐渐切换到7天输液器。在每个时间点,我们收集了CGM指标,包括平均传感器葡萄糖及其标准差(SD), 70至180 mg/dL之间的时间百分比(TIR), 70至140 mg/dL之间的时间百分比(TITR),超过180 mg/dL的时间百分比(TAR), 180至250 mg/dL之间的时间百分比(TARLevel1),超过250 mg/dL的时间百分比(TARLevel2),低于70 mg/dL的时间百分比(TBR), 54至70 mg/dL之间的时间百分比(TBRLevel1)。低于54 mg/dL的时间百分比(TBRLevel2)、血糖管理指标(GMI)、变异系数(CV)和血糖风险指数(GRI)。所有指标均从CareLink System®平台获取,考虑时间间隔为15天。数值数据以平均值和标准差表示,而分类变量以绝对频率和百分比报告。经Kolmogorov-Smirnov检验证实,数值变量服从正态分布,因此采用参数方法。为了比较不同时间点的临床变量,包括血糖控制指标,使用配对样本Student t检验比较基线和使用自动模式的前2周,使用重复测量方差分析(ANOVA)比较T1、T2和T3。事后两两比较采用Tukey检验,多重比较采用Bonferroni校正,校正显著性水平为0.017。在T1、T2和T3时间点,采用数值变量的Student t检验和分类变量的卡方检验,比较TBR≥50%和TBR≤4%的CGM目标完成者和未完成者的临床变量和系统设置。此外,应用逻辑回归模型确定同时达到TITR≥50%和TBR≤4%的基线预测因子。统计学分析采用IBM SPSS软件for Windows, Version 22 (IBM Corp., Armonk, NY, United States), p值小于0.05认为有统计学意义。我们纳入了111名儿童和青少年,以Minimed™780G开始治疗,男性患病率略高(55.0%)。研究参与者的平均年龄为12.7±3.3岁,平均糖尿病病程为4.7±3.4年。在使用Minimed™780G系统之前,46人(41.4%)每天多次注射胰岛素,65人(58.6%)已经使用胰岛素泵。入组前一年的平均HbA1c为7.2%±0.9%。T0时,BMI Z-score平均值为0.8±1.2。根据设备开始使用的时间,所有参与者完成了6个月的观察期,97名(87.4%)完成了12个月的Minimed 780G使用,46名(41.4%)完成了24个月的随访期。从手动模式切换到自动模式后,我们观察到TBRLevel1的显著改善(2.2±1.7 vs. 1.9%±1.7%;p = 0.015), TBR(2.6±2.2∶2.4%±2.4%;p = 0.045), TITR(43.1%±10.1%比51.5%±8.6%;p &lt;0.001), TIR(66.9±10.8∶76.0%±7.6%;p & lt; 0.001), TARLevel1(24.0±7.2和18.3±5.8;p & lt; 0.001), TARLevel2(6.5±4.8与3.6%±3.0%;p &lt;0.001), TAR(30.6±10.8∶21.9%±7)。 8%;p &lt;0.001), CV(34.6±4.0 vs. 33.0%±4.0%;p &lt;0.001),平均传感器葡萄糖(156.5±15.6 vs 144.7±11.3 mg/dL;p & lt; 0.001)和GRI(36.3±12.5和23.4±8.0;p & lt; 0.001)。在随后的24个月的随访中,血糖指标在统计学上保持不变,T1、T2和T3之间没有显著差异(图1)。当比较T1时TITR≥50%和TBR≤4%的完成者和未完成者时,我们发现,在完成者中,自动纠正剂量的百分比较低(p = 0.009),更频繁地使用活性胰岛素时间(AIT) 2小时(p = 0.005)和最佳设置,包括AIT 2小时和SmartGuard目标100 mg/dL (p = 0.003)。在T2时观察到类似的结果(表1)。逻辑回归分析没有发现任何基线预测因子可以同时达到TITR≥50%和TBR≤4%,除了入组前12个月的平均HbA1c值与T2时的目标实现呈负相关(B = - 1.126;95% ci 0.173-0.607;p & lt; 0.001)。我们的数据证实了在自动模式下使用Minimed™780G的直接好处,导致关键CGM指标(包括TIR和TITR)的显着改善,并减少了低血糖事件。这些结果与先前的研究一致,这些研究报告了AID系统在青少年中的短期效益,在自动模式激活后两周内开始。值得注意的是,我们的数据显示,CGM数据的改善持续了24个月,在12个月和24个月的指标之间没有显著差异。同样,一项针对50名青少年的前瞻性研究显示,该设备在2年的研究期间,在TIR方面表现持续另一项对35名学龄前儿童参与的非随机、前瞻性单臂临床试验的随访分析显示,Minimed™780G对血糖控制的积极作用持续长达18个月考虑到现实世界中儿童和青少年的设备依从性和行为变异性的挑战,长达2年的血糖结果的稳定性尤其值得注意。青少年糖尿病的管理通常面临许多挑战,包括导致每日血糖显著升高的特定生理因素,以及这个年龄段典型的心理和行为问题,很大一部分青少年没有达到推荐的血糖目标。9,10在我们的分析中,我们关注的是达到50%的TITR而不超过推荐的低血糖时间阈值的受试者的特征。最近,人们建议将TITR作为临床实践中TIR的替代指标,因为它更准确地反映在血糖范围内的时间。有趣的是,我们发现满足TITR≥50%和TBR≤4%血糖目标的参与者更有可能使用更严格的设备设置。然而,这种关联在24个月后没有得到证实。需要更大规模的进一步研究来验证这一趋势,并阐明潜在的潜在决定因素。在12870名Minimed™780G用户中,2小时的AIT和100mg /dL的SmartGuard目标已经被确定为TIR改善的预测因子一项针对同一人群中年龄≤15岁的个体的亚分析进一步表明,在使用最佳设置的人群中,同时达到推荐的TIR、TBR和GMI目标的个体百分比显著高于普通人群同样,持续使用2小时的AIT和100 mg/dL的SmartGuard目标与较高的TITR水平密切相关。最后,我们的分析显示,在同时达到TITR和TBR目标的参与者中,自动纠正丸的百分比降低了。这一发现在所有时间点上都是一致的,并且与先前的研究一致,这些研究表明,在AID使用者中,较高比例的自动纠正丸与次优血糖结局之间存在关联。一项使用MiniMed™780G对青少年T1D患者进行的研究报告显示,自动校正剂量百分比低于30%与较高的TIR和TIR水平相关。13这一趋势强调了用户初始剂量和准确的碳水化合物计数在实现最佳血糖控制方面的关键作用。14尽管有其优势,我们的研究也有一些局限性,包括24个月期间的样本量减少,这反映了一些参与者是最近才入组的事实,以及单中心设计,这可能限制了研究结果的普遍性。总之,我们的研究表明,Minimed™780G为患有T1D的儿童和青少年提供了长达24个月的持续血糖控制改善。在不增加低血糖风险的情况下,在短时间内达到目标与使用最佳设备设置密切相关。 BB和SP对研究进行了概念化并撰写了文章的初稿。FM和MC研究数据。GS对稿件进行了审阅和编辑。FL参与了讨论并审阅和编辑了手稿。所有作者都认可了手稿的最终版本。SP是这项工作的担保人,因此可以完全访问研究中的所有数据,并对数据的完整性和数据分析的准确性负责。本文未收到任何资助。BB报道了Movi SpA和雅培的旅行补助。FL获得了赛诺菲和Movi SpA的演讲和顾问荣誉。SP从Movi SpA获得演讲酬金。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Diabetes, Obesity & Metabolism
Diabetes, Obesity & Metabolism 医学-内分泌学与代谢
CiteScore
10.90
自引率
6.90%
发文量
319
审稿时长
3-8 weeks
期刊介绍: Diabetes, Obesity and Metabolism is primarily a journal of clinical and experimental pharmacology and therapeutics covering the interrelated areas of diabetes, obesity and metabolism. The journal prioritises high-quality original research that reports on the effects of new or existing therapies, including dietary, exercise and lifestyle (non-pharmacological) interventions, in any aspect of metabolic and endocrine disease, either in humans or animal and cellular systems. ‘Metabolism’ may relate to lipids, bone and drug metabolism, or broader aspects of endocrine dysfunction. Preclinical pharmacology, pharmacokinetic studies, meta-analyses and those addressing drug safety and tolerability are also highly suitable for publication in this journal. Original research may be published as a main paper or as a research letter.
期刊最新文献
Effects of GLP-1 receptor agonists on cognitive function in patients with type 2 diabetes: A systematic review and meta-analysis based on randomized controlled trials. The importance of treatment sequencing with SGLT2 inhibitors and GLP-1 receptor agonists combination for kidney function preservation in type 2 diabetes. Increasing cardiovascular mortality in young adults with diabetes mellitus as a contributing cause in the United States. Targeting gut-derived NETosis: A paradigm shift in understanding metformin's therapeutic action. Associations between anthropometric measures of obesity and prediabetes risk: A dose-response meta-analysis of cohort studies.
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