Improving glycemic control by transitioning from the MiniMed^TM 640G to 770G in Japanese adults with type 1 diabetes mellitus: a prospective, single-center, observational study

Abstract

The effectiveness of a hybrid closed-loop (HCL) system in improving glycemic control is unclear in Japanese individuals. Therefore, we assessed the effect impact of the MiniMed 770G HCL system on glycemic control in this population. This prospective, single-center, 24-week observational study (registration number: UMIN000047394) enrolled 23 individuals with type 1 diabetes mellitus using the Medtronic MiniMed 640G system. The primary endpoint was the improvement in time in the range of 70–180 mg/dL after transitioning to the MiniMed 770G HCL system. We observed an increase in time in range (from 64.1 [55.8–69.5] to 70.9 [67.1–74.4] %, interquartile range 25–75%, p < 0.001) and a decrease in glycated hemoglobin level (from 7.4 [7.0–7.9] to 7.1 [6.8–7.4] %, p = 0.003). There was a significant reduction in time above the range (181–250 mg/dL: 25.8 [20.9–28.6] to 19.5 [17.1–22.1] %, p < 0.001; >251 mg/dL: 8.7 [4.0–13.0] to 4.7 [3.6–9.1] %, p < 0.001). Time below the range remained unchanged (54–69 mg/dL: 1.8 [0.4–2.4] to 2.1 [0.4–3.9] %, p = 0.24; <54 mg/dL: 0.2 [0.0–1.0] to 0.5 [0.1–1.3] %, p = 0.14). In a subgroup of 12 patients with a high HCL implementation rate, the basal insulin infusion decreased immediately after mealtime insulin administration and increased after approximately 120 minutes. The ratings from questionnaires assessing treatment burden, satisfaction, and quality of life remained unchanged. The MiniMed 770G HCL system improved glycemic control and optimized insulin delivery, particularly in patients with high implementation rates.

 Introduction

Type 1 diabetes typically results in the complete absence of insulin due to the destruction of pancreatic beta cells. Thus, insulin therapy is essential. Moreover, an exact approach to insulin therapy that closely replicates natural insulin secretion is imperative for both preventing the onset and slowing the progression of diabetic complications in the long term. In recent years, substantial advancements have been made in insulin therapy for persons with type 1 diabetes [1, 2]. A notable development is the integration of continuous subcutaneous infusion pump therapy (CSII) with continuous glucose monitoring (CGM) technology. This innovative combination enables the continuous monitoring of glucose levels in the interstitial fluid through a small subcutaneous cannula, resulting in a highly precise and finely tuned approach to insulin therapy. This integrated system is called sensor-augmented pump (SAP) therapy [3].

An outstanding example of SAP therapy is the MiniMed^TM 640G (Medtronic, Dublin, Ireland). This device not only wirelessly transmits glucose values from the CGM to the insulin infusion pump, allowing for real-time adjustments to insulin delivery as needed, but also incorporates a mechanism to temporarily suspend continuous insulin infusion when glucose levels either reach a predefined standard or decrease to a specific low threshold. This feature considerably bolsters the prevention of hypoglycemia [4] and is referred to as predictive low-glucose management (SAP + PLGM) [5, 6].

In Japan, the MiniMed^TM 770G (Medtronic), equipped with a hybrid closed-loop (HCL) functionality, became available in 2022. HCL functionality represents a sophisticated system that autonomously fine-tunes basal insulin infusion based on three crucial parameters: the calculated insulin effect value determined from the previous 6 days of insulin infusion, remaining insulin duration, and deviation from the target sensor glucose level of 120 mg/dL. Nevertheless, the introduction of this groundbreaking technology in Japan has lagged behind that of the United States and other nations for several years.

Although the effectiveness of HCL systems in improving glycemic control has been extensively documented in other countries [7], there is a noticeable absence of such data involving Japanese individuals. To address this gap, we conducted this study to assess the effect of introducing HCL functionality through the MiniMed^TM 770G system on glycemic control in Japanese adults with type 1 diabetes. We also conducted a series of questionnaires to measure patient satisfaction [8, 9], evaluate the associated burden [10, 11], and assess the quality of life of individuals using CSII [12].

 Materials and Methods

 Ethics statements

The study protocol was approved by the Ethics Committee of Shinshu University School of Medicine (approval number: 5478) and was formally registered with the UMIN Clinical Trials Registry (registration number: UMIN000047394). The study rigorously adhered to the ethical principles outlined in the Declaration of Helsinki. All participants provided written informed consent to participate in the study.

 Study design and population

This single-center, prospective, interventional, 24-week study included 25 adults diagnosed with type 1 diabetes mellitus, all of whom were receiving SAP therapy using the MiniMed^TM 640G system at Shinshu University Hospital as of April 2022. One of the 25 patients withdrew from the study because of relocation, and another patient was excluded from the analysis because she received a sodium-glucose transporter 2 inhibitor during the study. Consequently, the data from 23 patients were analyzed. We transitioned from the MiniMed ^TM 640G to the MiniMed ^TM 770G model at the study commencement. The HCL mode was introduced after the patients became fully acquainted with the new device. The target glucose level was 120 mg/dL. We do not restrict exercise for the subject throughout the study. Adjustments to the carbohydrate-to-insulin ratio were permitted at the discretion of the treating physician. During the 23-patient observation period, the carbohydrate-to-insulin ratio was increased in five patients and decreased in four patients.

 Data collection

We collected data on levels, glycated hemoglobin A1c (HbA1c), CGM, and insulin infusion doses before implementing the MiniMed^TM 770G and 24 weeks after its introduction. Furthermore, we meticulously scrutinized the CGM data during the 4 weeks immediately preceding the transition and during the final 4 weeks of the 24-week observation period.

To thoroughly assess the impact of transitioning to an HCL system for insulin infusion, we compared CGM data for 4 weeks immediately before and after the transition to the HCL system, using data from 12 patients who maintained an HCL coverage of at least 80% during the 4 weeks following the transition. Additionally, we conducted an analysis to assess changes in basal insulin infusion before and after the transition.

Additionally, we conducted surveys using the Diabetes Treatment Satisfaction Questionnaire (DTSQ) [8, 9], which is designed to evaluate patient satisfaction with diabetes treatment, Problem Areas of Diabetes Questionnaire (PAID) [10, 11], which is used to assess the perceived burden of diabetes treatment, and Continuous Subcutaneous Insulin Infusion-Related Quality of Life Scale (CSII-QOL), a quality of life questionnaire tailored for individuals using CSII [12], both before and after the study. Higher scores on all DTSQ and CSII-QOL items indicate better status, while higher scores on all PAID items indicate greater treatment burden. Our primary endpoint for analysis was changes in TIR of 70–180 mg/L. Our secondary endpoints included HbA1c levels and key metrics including the time above range (TAR) and time below range (TBR), which were derived from CGM data. We also examined any changes reported in the DTSQ, PAID, and CSII-QOL scores according to the survey responses.

 Statistical analysis

We used the Wilcoxon signed-rank test and Spearman rank correlation coefficient for statistical analysis. The statistical analysis was performed using R version 4.2.2. Statistical significance was established at a threshold of a p-value <0.05.

 Results

 Clinical anthropometric and biochemical variables

Table 1 summarizes the clinical, anthropometric, and biochemical characteristics of the study participants. Notably, at the onset of the study, the median HbA1c level was 7.4% (interquartile range 7.0–7.9%), indicating commendable glycemic control among participants from the outset. During the final 4 weeks of observation, the median utilization rate of HCL technology reached 86.0% (interquartile range 69.0–90.0%).

Table 1 Patient characteristics at baseline

	Baseline (n = 23)
Age, years	44 (38–54)
Male, N (%)	5 (22)
Weight, kg	59.5 (52.3–69.8)
Body mass index, kg/m2	23.1 (20.6–25.2)
Duration of diabetes, years	22 (18.5–30.0)
HbA1c, %	7.4 (7.0–7.9)
TDD, unit/kg/day	0.55 (0.48–0.67)

Data are presented as the median (inter-quartile range, or n (%)); HbA1c, glycated hemoglobin A1c; TDD, total daily dose of insulin.

 Glycemic management

Fig. 1 and Table 2 present the data pertaining to glycemic management, highlighting significant improvements in several key metrics during 24 weeks of the observation. The median TIR increased from 64.1 [55.8–69.5] % to 70.9 [67.1–74.4] % (median [interquartile range], p < 0.001). Furthermore, HbA1c levels exhibited a substantial decrease from 7.4 [7.0–7.9] % to 7.1 [6.8–7.4] % (p = 0.003) prior to the introduction of the intervention. In contrast, the median TAR decreased from 35.0 [26.8–41.7] % to 26.6 [21.1–30.0] % (p < 0.001), whereas TBR remained stable (1.9 [0.4–3.8] % to 2.6 [0.5–4.8] %, p = 0.059).

Fig. 1  Box and whisker plots comparing various parameters and HbA1c levels between the MiniMed^TM 640G and MiniMed^TM 770G before and after the 24-week transition. CGM data were analyzed for both periods, each comprising 4 weeks. TIR (70–180 mg/dL): TBR: TAR. HbA1c, glycated hemoglobin A1c; CGM, continuous glucose monitoring; TIR, time in range; TBR, time below range; TAR, time above range.

Table 2 Changes in glycemic control, HbA1c and insulin dose

	Baseline	At 24 weeks	p
Percentage of CGM sensor activate time, %	75.3 (53.3–92.0)	87.0 (81.9–93.0)	0.001
Percentage of HCL activate time, %		86.0 (69.0–90.0)
Sensor glucose value in range
<54 mg/dL, %	0.2 (0.0–1.0)	0.5 (0.1–1.3)	0.14
54–69 mg/dL, %	1.8 (0.4–2.4)	2.1 (0.4–3.9)	0.24
70–180 mg/dL, %	64.1 (55.8–69.5)	70.9 (67.1–74.4)	<0.001
181–250 mg/dL, %	25.8 (20.9–28.6)	19.5 (17.1–22.1)	<0.001
>251 mg/dL, %	8.7 (4.0–13.0)	4.7 (3.6–9.1)	0.007
Mean sensor glucose, mg/dL	166.2 (148.5–178.5)	155.6 (142.6–160.3)	<0.001
CV of sensor glucose, %	36.6 (33.1–40.7)	36.4 (32.2–39.5)	0.85
HbA1c, %	7.4 (7.0–7.9)	7.1 (6.8–7.4)	0.003
TDD, unit/kg/day	0.55 (0.48–0.67)	0.62 (0.47–0.74)	0.96
Basal insulin percentage of TDD, %	38.1 (30.3–43.7)	40.4 (29.9–47.6)	0.31

Data are presented as the median (inter-quartile range). CGM, continuous glucose monitoring; HCL, hybrid closed-loop; CV, coefficient of variation; HbA1c, glycated hemoglobin A1c; TDD, total daily dose of insulin.

Changes in glycemic management at 0, 12, and 24 weeks were examined. Because data at 12 weeks were missing for one patient due to a pump change, 22 patients were used for this analysis. TBR was 1.9 [0.4–3.8] %, 2.9 [0.9–7.4] %, 2.6 [0.5–4.8] % at 0, 12, and 24 weeks: TIR was 64.1 [55.8–69.5] %, 73.9 [65.9–76.9] %, 70.9 [67.1–74.4] % at 0, 12, and 24 weeks: TAR was 35.0 [26.8–41.7] %, 22.4 [17.9–30.8] %, 26.6 [21.2–29.9] % at 0, 12, and 24 weeks. TBR increased significantly at 12 weeks (p = 0.001) and decreased significantly from 12 to 24 weeks (p = 0.001). Thus, no significant change between 0 and 24 weeks (p = 0.061) was observed. TIR increased significantly at 12 weeks (p < 0.001) and did not differ significantly between 12 and 24 weeks (p = 0.463); it remained significantly elevated at 24 weeks compared to 0 weeks (p < 0.001). TAR decreased significantly at 12 weeks (p < 0.001) and did not differ between 12 and 24 weeks (p = 0.052); TAR was significantly different between 0 and 24 weeks (p = 0.001).

 Relationship between changes in TIR and age, initial HbA1c level, and HCL usage

We conducted a thorough analysis to investigate the connection between changes in TIR and numerous factors, including age, initial HbA1c level, and rate of HCL use (Fig. 2). The results showed a significant inverse relationship between age and improvements in TIR, with younger participants demonstrating more substantial enhancements than older ones (rs = –0.438, p = 0.036). Interestingly, the initial HbA1c level before study commencement did not show a significant correlation with improvements in TIR. We also did not observe any significant association between HCL use and TIR improvement.

Fig. 2  Correlations between the improvement in time in range of 70–180 mg/dL (%) after 24 weeks and the following factors: A) age, B) HbA1c level before starting the HCL system, and C) HCL system usage during the 24-week observation period. Statistical analysis of correlations was conducted using the Spearman rank correlation coefficient. HbA1c, glycated hemoglobin A1c; HCL, hybrid closed-loop.

 Insulin infusion before and after HCL implementation

When comparing the amount of insulin infusion before and after the introduction of HCL technology, we did not observe any significant differences in total daily insulin usage (before: 32.5 [27.4–45.3] U, after: 34.9 [25.9–46.5] U, p = 1.00) or the proportion of basal insulin in total insulin usage (before: 38.2 [30.3–43.7] %, after: 40.4 [29.9–47.6] %, p = 0.31).

 Changes in insulin infusion patterns with HCL technology

To gain deeper insights into how HCL implementation influences insulin infusion patterns, we performed a focused post-hoc analysis on a subgroup of 12 patients who used HCL for 80% of the time during the initial 4 weeks following HCL initiation. The inclusion criterion of 80% in the subgroup analysis was chosen to isolate the direct impact and examine the pure effect of HCL as comprehensively as possible, considering that the median HCL activation rate during the initial 4 weeks following HCL initiation was 80%. This subgroup had a mean age of 45.5 [40.3–61.0] years, a body mass index of 25.2 [23.3–28.4] kg/m², and a pre-study HbA1c level of 7.2 [6.6–7.5] %, which did not differ significantly from that of the broader study population. Table 3 shows the glycemic control indices for this specific group at 4-week intervals both before and immediately after initiating HCL treatment. Notably, TIR increased significantly from 65.1 [57.8–67.6] % to 74.7 [72.1–74.7] % (p < 0.001). Additionally, TAR in the range of 181–250 mg/dL decreased from 25.6 [18.4–27.8] % to 18.3 [15.9–21.1] % (p < 0.001), and TAR above 250 mg/dL decreased from 8.3 [4.2–12.0] % to 5.0 [2.8–5.9] % (p = 0.001), while TBR remained unchanged. On the other hand, in the group with less than 80% HCL coverage, TIR did not show significant improvement in TIR in the 4 weeks before and after HCL initiation (from 66.5 [53.1–73.7] % to 69.1 [61.8–74.4] %).

Table 3 Changes in glycemic control and insulin dosage in subgroups of 12 patients who consistently used HCL technology for ≥80% of the study duration

	baseline	at 4 weeks	p
Percentage of CGM sensor activate time, %	90.7 (84.0–94.7)	90.8 (87.0–94.5)	0.16
Percentage of HCL activate time, %		88.5 (83.5–90.5)
Sensor glucose value in range
<54 mg/dL, %	0.3 (0.1–1.4)	0.3 (0.2–1.3)	0.68
54–69 mg/dL, %	1.6 (0.8–2.9)	1.7 (0.9–3.5)	0.85
70–180 mg/dL, %	65.1 (57.8–67.6)	74.7 (72.1–76.2)	<0.001
181–250 mg/dL, %	25.6 (18.4–27.8)	18.3 (15.9–21.1)	<0.001
>251 mg/dL, %	8.3 (4.2–12.0)	5.0 (2.8–5.9)	0.001
Mean sensor glucose, mg/dL	160.5 (150.0–173.7)	148.2 (141.0–154.9)	<0.001
CV of sensor glucose, %	36.2 (32.2–41.0)	36.4 (34.8–38.8)	0.34
TDD, unit/kg/day	0.64 (0.52–0.77)	0.65 (0.54–0.76)	0.62
Basal insulin percentage of TDD, %	38.5 (29.7–42.5)	42.0 (33.0–46.2)	0.13

Data are presented as the median (inter-quartile range). CGM, continuous glucose monitoring; HCL, hybrid closed-loop; CV, coefficient of variation; TDD, total daily dose of insulin.

In Fig. 3A, we visually depict the basal insulin infusion patterns of the 12 patients who used HCL for HC 80% of the time. Prior to the implementation of HCL, basal insulin infusion displayed minimal fluctuations throughout the day. However, following the introduction of HCL technology, basal insulin infusion exhibited a triphasic pattern with distinct peaks at 0:00, 8:00, and 15:00. To investigate a potential link to dietary factors, Fig. 3B illustrates the changes in the average basal insulin infusion at 5-minute intervals, ranging from 30 minutes before to 360 minutes after the daily dinner bolus, for each of the 12 patients immediately after the introduction of HCL over a 4-week period. The data shows a rapid decrease in basal insulin infusion after bolus administration, followed by a slight increase at 30 minutes, a subsequent decrease at 60 minutes that marks a nadir, and again, an increase with a peak at 210 minutes. Subsequently, the basal insulin infusion gradually decreased to the pre-bolus level, eventually returning to the pre-bolus infusion rate at the 360-minute mark.

Fig. 3  The basal insulin infusion rate for 12 patients with HCL system use of 80%. A) The daily variation of the mean basal infusion rate during the 4 weeks immediately preceding and following the transition to the HCL system. B) The mean basal insulin infusion rate in 5-minute intervals from 30 minutes before to 360 minutes after the dinner bolus insulin dose. The basal insulin infusion rate used was the auto-basal value indicated by the pump. HCL, hybrid closed-loop.

 Comparison of pre- and post-questionnaire results for treatment satisfaction and treatment burden

Table 4 presents a comparative analysis of the outcomes obtained from the DTSQ, PAID, and CSII-QOL. Notably, all three domains of the DTSQ exhibited consistent scores with no discernible variations before and after the intervention. Similarly, the PAID and CSII-QOL scores remained stable across the pre- and post-intervention periods.

Table 4 Changes in DTSQ, PAID and CSII-QOL scores

	Baseline	At 24 weeks	p
DTSQ scores
Treatment satisfaction	30.0 (27.0–33.0)	30.0 (28.0–33.0)	0.67
Hypoglycemia perception	2.0 (1.5–3.0)	2.0 (1.0–2.5)	0.83
Hyperglycemia perception	3.0 (2.5–4.0)	3.0 (1.0–4.0)	0.16
PAID scores	43.0 (35.5–54.5)	41.0 (31.0–52.5)	0.61
CSII-QOL scores
Convenience	28.0 (25.0–29.0)	28.0 (24.5–29.0)	0.92
Social restriction	16.0 (13.5–21.0)	17.0 (13.5–21.5)	0.16
Psychological problems	30.0 (25.5–35.5)	30.0 (25.5–33.0)	0.68

Data are presented as the median (inter-quartile range).

DTSQ, Diabetes Treatment Satisfaction Questionnaire; PAID, The Problem Areas in Diabetes; CSII-QOL, Continuous Subcutaneous Insulin Infusion Related Quality-of-life.

 Discussion

In this study, we transitioned 23 individuals diagnosed with type 1 diabetes at our hospital from the MiniMed^TM 640G to the MiniMed^TM 770G incorporating HCL technology over a 24-week period. Consequently, we successfully demonstrated a significant increase in TIR, our primary endpoint, accompanied by a corresponding reduction in TAR. Furthermore, we observed a noteworthy improvement in HbA1c levels. Notably, we did not detect any significant changes in TBR or in patients’ satisfaction, perceived treatment burden, or quality of life.

In a previous randomized controlled trial (RCT) conducted by Collyns et al. [7], a comparison was made between the SAP + PLGM system and the MiniMed^TM Advanced Hybrid Closed-Loop (AHCL) system, which includes automated bolus insulin infusion. During the study period, the former exhibited a TIR of 57.9% ± 11.7%, while the latter demonstrated a TIR of 70.4% ± 8.1%, emphasizing the superior glycemic control achieved with the AHCL system. It is worth noting that the RCT employed a crossover design with a brief treatment duration of 4 weeks, and the initial TIR of our study population was 64.1%, suggesting that Collyns et al.’s study population had less optimal glycemic management than our cohort. Nevertheless, it is noteworthy that the TIR achieved in our HCL induction study is consistent with the results of other recent studies [7, 13-15].

Real-world data from European patients undergoing HCL + SAP therapy indicated a mean TIR of 72.0% [13]. Recently published Japanese data by Akiyama et al. demonstrated an improvement in TIR from 63.5% to 73.0% after 12 weeks of MiniMed^TM 770G use [16]. In the current study, we observed an increase in TIR from 64.1% to 70.9% over a 24-week period. Although direct comparisons with previous reports are challenging owing to differences in background, ethnicity, and observation duration, our study revealed a comparable improvement in blood glucose management. Notably, our data showed that the subgroup with HCL use exceeding 80% experienced a significant increase in TIR, from 65.1% to 74.7%. Although we were unable to establish a direct correlation between HCL use and TIR improvement, there was no significant improvement in TIR at 4 weeks after HCL initiation in subjects with less than 80% HCL wearing rate, suggesting that increasing wearing rate is important for improving TIR.

This study confirmed the consistency of basal and bolus insulin administration before and after the observation period. Nevertheless, we noted significant improvements in blood glucose-related indicators, such as HbA1c and TIR. Consequently, we hypothesized that the transition to HCL insulin therapy prompted alterations in insulin infusion patterns rather than changes in insulin dosage, resulting in enhanced blood-glucose-related metrics.

To substantiate this hypothesis, we conducted an extensive analysis of CGM data for 4 weeks immediately before and after switching to HCL. The analysis encompassed the daily average profile of basal insulin infusion rates and fluctuations in basal insulin infusion following bolus insulin administration during dinner for participants who consistently used the HCL system at least 80% of the time. Daily basal insulin infusion exhibited a triphasic peak following transition to HCL technology. We observed an immediate reduction in the basal infusion rate after bolus insulin administration, followed by a gradual increase. After 120 minutes, the basal insulin infusion rate surpassed pre-dinner levels. This shift suggests that the increased infusion rate facilitated by the HCL system effectively compensated for the heightened insulin requirement that occurred more than 2 hours after meals, a task that a bolus injection of ultrafast-acting insulin alone might struggle to accomplish. Certainly, a higher basal insulin infusion was observed from about 22:00 to 26:00 after the change. The latter part of this period may be due to the higher infusion volume at night, independent of the postprandial bolus. The glucose level was higher than the target glucose level (120 mg/dL) during this period and may have increased to compensate.

Insulin therapy is widely recognized as frequently imposing both psychological and physical burdens on patients. Consequently, healthcare providers must prioritize patient satisfaction with insulin therapy. In the management of type 1 diabetes, it has been well-documented that transitioning from multiple insulin injections to CSII reduces the burden on patients and enhances their overall satisfaction [17]. Therefore, in the current study, we administered a series of questionnaires previously employed to assess patient burden, treatment satisfaction, and patient quality of life. Within the scope of this investigation, no significant changes were observed in any score. This result was consistent with the findings of Akiyama et al. [16]. Our results suggest that the transition to HCL systems does not lead to a discernible improvement in burden, satisfaction, or quality of life as measured by conventional assessments. Nevertheless, it is possible that these questionnaires were not fully equipped to gauge feelings of burden, satisfaction, and overall quality of life in individuals already receiving stable SAP therapy, given that the HCL system has been shown to have a positive psychological impact on the management of type 1 diabetes mellitus [18]. Therefore, the development of more comprehensive questionnaire items is imperative.

The novelty of this study is that it defined improvement in TIR as the primary endpoint and demonstrated it in a 24-week prospective study. Akiyama et al. [16] reported improvement in TIR as a secondary endpoint in a 12-week prospective study that examined changes in patient satisfaction and psychological status before and after treatment. Although their results are qualitatively the same, given the rigorous study design, our study is the first to demonstrate the benefit of 770G on glycemic control in Japanese patients. In addition, we believe it is valuable to clarify the progress of glycemic management at 12 and 24 weeks after the change. On the other hand, the lack of change in patient satisfaction and psychological status which was a secondary endpoint in our study, confirms the findings of Akiyama et al. [16].

The international consensus on clinical targets for CGM data in individuals with type 1 diabetes specifies the following ranges: TAR, >250 mg/dL; TAR, 181–250 mg/dL; TIR, 70–180 mg/dL; TBR, 54–69 mg/dL; and TBR, <54 mg/dL, each with respective goals of <5%, <25%, >70%, <4%, and <1% [19]. In the present study, after 24 weeks, these percentages were 4.7%, 19.5%, 70.9%, 2.1%, and 0.5%, respectively, demonstrating the successful achievement of the clinical targets. In our study, TIR increased while TAR decreased, with TBR remaining stable. These findings underscore that the implementation of HCL technology led to improvements in glycemic control without a concurrent increase in hypoglycemic events. This indicates that the MiniMed^TM 770G with HCL technology is a valuable tool for Japanese individuals. However, it is important to note that although these averages have been met, individuals have still not reached these targets. This underscores the ongoing need for personalized insulin therapy for individuals with type 1 diabetes, with the expectation of more effective systems in the future. One example is the successful implementation of the AHCL system, which has been extensively documented to lead to a significant reduction in severe hypoglycemic events and incidents of diabetic ketoacidosis [20]. Furthermore, the AHCL system demonstrated its capability to achieve a TIR exceeding 70% in all participants in a previous study [21].

Our study had several limitations. First, it is important to note that the study design was not an RCT. Second, as this was a single-center study, it presents challenges in generalizing the findings, as facility-specific characteristics may come into play. Third, although the observation period spanned an extended period of 24 weeks compared with that of similar studies, we were unable to assess outcomes beyond this period. Future research in Japan should consider conducting multicenter RCTs with designs such as crossovers to address these limitations. Fourth, it is regrettable that our questionnaires did not yield conclusive results regarding the participants’ burden, satisfaction, or quality of life with insulin therapy.

In summary, use of the MiniMed^TM 770G with HCL technology showed significant improvements in glycemic parameters among Japanese individuals diagnosed with type 1 diabetes mellitus compared with the MiniMed^TM 640G with SAP + PLGM system. Importantly, there was no change in the overall insulin dosage, underscoring the pivotal role of HCL technology in optimizing insulin delivery through automatic control of basal insulin infusion rates, which contributed to these favorable results.

 Author Contributions

S.K. was involved in study design, case enrollment, data analysis and data discussion. A.S. provided case enrollment and technical advice. M.H. provided administrative and practical support for the overall study. Y.O., S.T., A.K., Y.S., Y. Asano, Y. Sato, and M.Y. participated in enrollment and data discussions. M.K. designed the study, registered the cases, and wrote the manuscript.

 Acknowledgments

This research was not supported by any grant. We thank Editage (www.editage.com) for English editing.

 Disclosure Statement

M.K. is a member of Endocrine Journal’s Editorial Board.

 Approval of the Research Protocol

This study adhered to the principles outlined in the Declaration of Helsinki (revised in Fortaleza, Brazil, October 2013) and was approved by the Ethics Committee of Shinshu University Graduate School of Medicine (approval number: 5478, approval date: March 28, 2022).

 Informed Consent

All participants willingly provided informed consent.

 Approval Date of Registry and the Registration No. of the Study/Trial

This research was officially registered with the UMIN Clinical Trials Registry (registration number: UMIN000047394; approval date: April 5, 2022).

References

• 1   Wilson  LM,  Castle  JR (2020 ) Recent advances in insulin therapy. Diabetes Technol Ther 22: 929–936.
• 2   Beck  RW,  Bergenstal  RM,  Laffel  LM,  Pickup  JC (2019) Advances in technology for management of type 1 diabetes. Lancet 394: 1265–1273.
• 3   Phillip  M,  Nimri  R,  Bergenstal  RM,  Barnard-Kelly  K,  Danne  T, et al. (2023) Consensus recommendations for the use of automated insulin delivery technologies in clinical practice. Endocr Rev 44: 254–280.
• 4   Bergenstal  RM,  Tamborlane  WV,  Ahmann  A,  Buse  JB,  Dailey  G, et al. (2010) Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes. N Engl J Med 363: 311–320.
• 5   Forlenza  GP,  Li  Z,  Buckingham  BA,  Pinsker  JE,  Cengiz  E, et al. (2018) Predictive low-glucose suspend reduces hypoglycemia in adults, adolescents, and children with type 1 diabetes in an at-home randomized crossover study: results of the PROLOG trial. Diabetes Care 41: 2155–2161.
• 6   Tsunemi  A,  Sato  J,  Kurita  M,  Wakabayashi  Y,  Waseda  N, et al. (2020) Effect of real-life insulin pump with predictive low-glucose management use for 3 months: analysis of the patients treated in a Japanese center. J Diabetes Investig 11: 1564–1569.
• 7   Collyns  OJ,  Meier  RA,  Betts  ZL,  Chan  DSH,  Frampton  C, et al. (2021) Improved glycemic outcomes with Medtronic MiniMed advanced hybrid closed-loop delivery: results from a randomized crossover trial comparing automated insulin delivery with predictive low glucose suspend in people with type 1 diabetes. Diabetes Care 44: 969–975.
• 8   Ishii  H,  Bradley  C,  Riazi  A,  Barendse  S,  Yamamoto  T (2000) The Japanese version of the diabetes treatment satisfaction questionnaire (DTSQ): translation and clinical evaluation. J Clin Exp Med 192: 809–814 (In Japanese).
• 9   Bradley  C (1994) The diabetes treatment satisfaction questionnaire (DTSQ). In: Bradley C (ed) Handbook of Psychology and Diabetes: A Guide to Psychological Measurement in Diabetes Research and Practice. Harwood Academic Publishers, Chul, Switzerland: 111–132.
• 10   Polonsky  WH,  Anderson  BJ,  Lohrer  PA,  Welch  G,  Jacobson  AM, et al. (1995) Assessment of diabetes-related distress. Diabetes Care 18: 754–760.
• 11   Hayashino  Y,  Goto  M,  Yamamoto  T,  Tsujii  S,  Ishii  H (2023) The Japanese version of problem areas in diabetes scale: a clinical and research tool to assess emotional functioning among people with diabetes. Diabetol Int 15: 117–122.
• 12   Sakane  N,  Murata  T,  Tone  A,  Kato  K,  Kimura  M, et al. (2020) Development and validation of the continuous subcutaneous insulin infusion-related quality-of-life (CSII-QOL) scale. Diabetes Technol Ther 22: 216–221.
• 13   Da  Silva J,  Bosi  E,  Jendle  J,  Arrieta  A,  Castaneda  J, et al. (2021) Real-world performance of the MiniMed^TM 670G system in Europe. Diabetes Obes Metab 23: 1942–1949.
• 14   Brown  SA,  Kovatchev  BP,  Raghinaru  D,  Lum  JW,  Buckingham  BA, et al. (2019) Six-month randomized, multicenter trial of closed-loop control in type 1 diabetes. N Engl J Med 381: 1707–1717.
• 15   Benhamou  PY,  Franc  S,  Reznik  Y,  Thivolet  C,  Schaepelynck  P, et al. (2019) Closed-loop insulin delivery in adults with type 1 diabetes in real-life conditions: a 12-week multicentre, open-label randomised controlled crossover trial. Lancet Digit Health 1: e17–e25.
• 16   Akiyama  T,  Yamakawa  T,  Orime  K,  Ichikawa  M,  Harada  M, et al. (2024) Effects of hybrid closed-loop system on glycemic control and psychological aspects in persons with type 1 diabetes treated with sensor-augmented pump: a prospective single-center observational study. J Diabetes Investig 15: 219–226.
• 17   McAuley  SA,  Lee  MH,  Paldus  B,  Vogrin  S,  de  Bock MI, et al. (2020) Six months of hybrid closed-loop versus manual insulin delivery with fingerprick blood glucose monitoring in adults with type 1 diabetes: a randomized, controlled trial. Diabetes Care 43: 3024–3033.
• 18   Farrington  C (2018) Psychosocial impacts of hybrid closed-loop systems in the management of diabetes: a review. Diabet Med 35: 436–449.
• 19   Battelino  T,  Alexander  CM,  Amiel  SA,  Arreaza-Rubin  G,  Beck  RW, et al. (2023) Continuous glucose monitoring and metrics for clinical trials: an international consensus statement. Lancet Diabetes Endocrinol 11: 42–57.
• 20   Graham  R,  Mueller  L,  Manning  M,  Habif  S,  Messer  LH, et al. (2024) Real-world use of control-IQ technology is associated with a lower rate of severe hypoglycemia and diabetic ketoacidosis than historical data: results of the control-IQ observational (CLIO) prospective study. Diabetes Technol Ther 26: 24–32.
• 21   Kesavadev  J,  Basanth  A,  Krishnan  G,  Shankar  A,  Sanal  G, et al. (2023) Real-world user and clinician perspective and experience with MiniMed^TM 780G advanced hybrid closed loop system. Diabetes Ther 14: 1319–1330.