Abstract
Background
Hybrid closed-loop (HCL) systems adjust basal insulin levels using real-time glucose levels obtained from continuous glucose monitors (CGM). This study evaluated the MiniMed 770G system in Korean youths with childhood-onset type 1 diabetes (T1D).
Methods
Of the 457 patients followed-up for childhood-onset T1D for > 1 year at Seoul National University Children’s Hospital and Seoul National University Bundang Hospital between February 2022 and May 2023, 20 patients (10 boys, 10 girls) who used a MiniMed 770G system for ≥ 3 months with a CGM active time of > 70% were enrolled. Glycemic outcomes, including glycated hemoglobin A1c (HbA1c), and CGM-derived metrics (time in range [TIR], time below range, time above range > 180 mg/dL and > 250 mg/dL [TAR 180 and TAR 250], and coefficient of variation [CV]) were analyzed. Generalized estimating equation (GEE) analysis compared glycemic outcomes between auto-mode users (> 85% and ≤ 85%) during the 1-year follow-up.
Results
The median age at HCL initiation was 14.0 years (interquartile range [IQR], 11.2, 17.9), with a median diabetes duration of 6.5 years (IQR, 5.7, 8.9). The numbers of auto-mode (> 85%) users at 3, 6, 9, and 12 months were 10, 9, 9, and 7, respectively. Compared to auto-mode (≤ 85%) users, auto-mode (> 85%) users demonstrated 0.75 lower HbA1c (P = 0.037), 7.0 higher TIR (P = 0.015), 6.7 lower TAR 180 (P = 0.031), and 3.2 lower CV (P = 0.001) during the year using GEE analysis. In an analysis of auto-mode (> 85%) users, the median TIR, TAR, and CV significantly improved from 59% at baseline to 74.5% at 3 months (P = 0.008), and from 65% at baseline to 73% at 6 months (P = 0.012). Neither severe hypoglycemia nor diabetic ketoacidosis was observed throughout the year. The most common reasons for auto-mode exit were hyperglycemia and a lack of calibration.
Conclusion
Use of HCL system with auto-mode (> 85%) enhanced glycemic control in youth with childhood-onset T1D during the study period.
Keywords: Insulin Infusion Systems; Diabetes Mellitus, Type 1; Glycated Hemoglobin; Pediatrics
Graphical Abstract
INTRODUCTION
Although the prevalence of type 1 diabetes (T1D) is relatively low in South Korea, its incidence is gradually increasing both domestically and globally.1 In 2016, the overall incidence of childhood-onset T1D was 4.77 per 100,000 persons based on the Korean National Health Insurance Service (NHIS).2 With the advent of technology for the management of diabetes, the use of continuous glucose monitors (CGM) and insulin pumps in 2010–2019 increased from 1.4% to 39.3% and from 2.1% to 14.0%, respectively, according to a multicenter study of Korean children and adolescents with T1D.3
Since sensor-augmented pumps (SAPs), which link an insulin pump to a CGM, were first introduced, SAPs with a predictive low-glucose suspension function that stops the infusions prior to the onset of hypoglycemia have been sequentially developed and clinically verified.4 Subsequently, an automated insulin delivery (AID) system, referred to as a closed-loop system, was developed to automatically adjust the insulin dose in response to CGM data using a dosing algorithm. One type of AID system is the hybrid closed-loop (HCL) system, which requires manual entry but has an auto-mode feature that adjusts the basal insulin level every 5 minutes based on CGM feedback, whereas the advanced HCL system delivers both automated basal and correction bolus insulin doses.5 The HCL system is recognized for its safety, improved glycemic control, and prevention of hypoglycemia, particularly with the extended use of the auto-mode feature.6
Recent guidelines issued by the American Diabetes Association and the International Society for Pediatric and Adolescent Diabetes advocate for the usage of AID systems by pediatric patients with T1D.7,8 Research in Korea demonstrated that the early initiation of SAPs in patients with T1D yields enhanced therapeutic efficacy.9 The Korean NHIS has partially reimbursed the cost of CGM sensors and transmitters since 2019 and insulin pumps since 2020. According to NHIS data, 751 (18.7%) of 4,021 patients aged < 20 years with T1D were prescribed a CGM in December 2019.10 The Korean Ministry of Food and Drug Safety approved the HCL system in May 2021.11 Although the use of CGM and insulin pumps is expected to increase, few studies have analyzed the effects of AID systems on glycemic outcomes among Korean youth.
In this study, we evaluated the effectiveness and safety of the HCL system in Korean youth with childhood-onset T1D. We also examined the barriers for patients in continuing with the auto-mode as the core algorithm in HCL systems.
METHODS
Participants
The study included 20 patients with childhood-onset T1D who initiated the use of an HCL system, MiniMed 770G system, (Medtronic, Northridge, CA, USA) between February 2022 and May 2023 at Seoul National University Children’s Hospital (n = 15) and Seoul National University Bundang Hospital (n = 5). Of the 457 patients who were followed-up for childhood-onset T1D for > 1 year during the study period, 418 used a CGM; and of these, 24 initiated use of the MiniMed 770G system. Four patients were excluded owing to loss to follow up (n = 1), deciding not to use auto-mode (HCL system; n = 1), and insufficient CGM use (CGM active time ≤ 70%, n = 2). Finally, 20 patients who continued to use the HCL system for at least 3 months and maintained a CGM active time of > 70% for at least 14 days12 were included in this study (Supplementary Fig. 1).
Measures
Descriptive characteristics and glycemic outcomes
Clinical data on age, sex, body mass index (BMI), and insulin regimen were obtained before the initiation of the MiniMed 770G system. Weight was measured using a digital scale (150 A; Cas Co., Ltd., Seoul, Korea), and height (cm) was measured using a Harpenden stadiometer (Holtain Ltd., Crymych, Wales, UK). The height and BMI z-scores were determined based on the 2017 Korean National Growth Charts.13 The presence of severe hypoglycemia with impaired consciousness requiring the help of others or diabetic ketoacidosis (hyperglycemia with a venous blood pH < 7.3 or bicarbonate level < 18 mmol/L) was documented. Data on glycated hemoglobin A1c (HbA1c) levels and 30-day CGM metric were collected every 3 months, including at baseline. HbA1c values were collected only when a CGM was used at least 70% of the time. CGM metrics, including time in range (TIR), time above range (> 180 mg/dL [TAR 180] and > 250 mg/dL [TAR 250]), time below range (< 70 mg/dL [TBR 70] and < 54 mg/dL [TBR 54]), coefficient of variation (CV), and total daily insulin dose (TDD, IU/day) were collected from each patient’s Carelink™ account every 3 months during follow-up. The CGM-derived glycemic targets were defined as TIR (> 70%), TAR 180 (< 25%), TAR 250 (< 5%), TBR 70 (< 4%), TBR 54 (< 1%), and CV (≤ 36%).12
Auto-mode usage
The proportion of auto-mode usage (%) and 14 reasons for exiting the SmartGuard auto-mode system were recorded. These 14 reasons were categorized into the following major reasons: 1) “hyperglycemia,” encompassing system messages including “high sensor glucose (SG) auto-mode exit” and “auto-mode max delivery”; 2) “no calibration,” including “no calibration occurred,” “basal glucose (BG) required for auto-mode,” and “sensor algorithm underread”; 3) “sensor-related problems,” comprising “sensor updating,” “sensor expired,” and “auto-mode warm-up”; 4) “hypoglycemia,” represented by “auto-mode min delivery”; 5) “user exit,” involving “auto-mode disabled by user” and “pump suspended by user”; and 6) “others,” including “no SG values,” “alarms,” and “unidentified.”
Statistical analysis
Statistical analyses were performed using R version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria). Nonparametric analyses were performed after testing for normality. Continuous variables are expressed as medians with interquartile ranges (IQR). HbA1c levels and CGM metric data were compared between baseline and follow-up at 3-month intervals using the Wilcoxon signed-rank sum test (continuous variables) and McNemar test (categorical variables). Based on the median value (85%) of the auto-mode usage rate in a previous study,14 the auto-mode effect was analyzed in high (> 85%) and low (≤ 85%) auto-mode usage groups. A generalized estimating equation (GEE) was employed to assess the glycemic variable differences through 1 year between high (> 85%) and low (≤ 85%) auto-mode usage groups. At 3, 6, 9, and 12 months, HbA1c levels and CGM metrics in participants with high (> 85%) auto-mode were compared to their respective baseline values using the Wilcoxon signed-rank test (continuous variables) and McNemar’s test (categorical variables). Statistical significance was set at P < 0.05.
Ethics statement
This retrospective study protocol was reviewed and approved by the Institutional Review Board of Seoul National University Hospital (approval No. H-2306-058-1436), and Seoul National University Bundang Hospital (approval No. B-2311-863-403), and the requirement for informed consent was waived.
RESULTS
Baseline characteristics
The study included 20 Korean youths (10 boys and 10 girls) with childhood-onset T1D (Table 1). Median age at MiniMed 770G initiation was 14.0 years (IQR, 11.2, 17.9), with a median diabetes duration of 6.5 years (IQR, 5.7, 8.9). Median height and BMI z-scores were 0.6 (IQR, −0.1, 0.8) and −0.1 (IQR, −0.5, 1.59), respectively. Previous treatments included multiple daily injections (MDI, n = 4), SAP with a predictive low-glucose suspension function (MiniMed 640G, n = 15), and low-glucose suspension (DIA:CONN G8, n = 1). Median age at MiniMed 770G system initiation was 16.8 and 13.2 years in the MDI and SAP group respectively; only the TDD differed significantly between the MDI (0.7 IU/kg/day) and SAP (0.96 IU/kg/day) groups (P = 0.014, Table 1).
Table 1. Baseline characteristic.
| Characteristics | Total | Previous insulin therapy | |
|---|---|---|---|
| Multiple daily injections (n = 4) | Sensor augmented pump (n = 16)a | ||
| Male | 10 (50.0) | 2 (50.0) | 8 (50.0) |
| Age at MiniMed 770G system initiation, yr | 14.0 (11.2, 17.9) | 16.8 (13.6, 19.3) | 13.2 (11.5, 16.9) |
| Height z-score | 0.6 (−0.1, 0.8) | 0.4 (−0.1, 1.2) | 0.6 (−0.1, 0.8) |
| BMI z-score | −0.1 (−0.5, 1.59) | 0.5 (−0.7, 1.4) | −0.1 (−0.3, 1.4) |
| Age at T1D diagnosis, yr | 7.4 (3.2, 10.0) | 10.0 (4.8, 14.9) | 7.3 (4.4, 8.5) |
| Duration of diabetes, yr | 6.5 (5.7, 8.9) | 7.7 (5.7, 8.4) | 6.2 (5.7, 9.0) |
| HbA1c, % | 7.7 (7.3, 8.0) | 8.2 (6.4, 9.2) | 7.7 (7.3, 8.0) |
| CGM active time, % | 86.0 (78.0, 94.0) | 95.5 (87.0, 97.9) | 82.5 (75.5, 89.5) |
| TIR, % | 62.5 (51.0, 68.0) | 52.5 (37.0, 70.5) | 65.5 (54.5, 68.0) |
| TAR 250 mg/dL, % | 9.5 (5.5, 16.0) | 19.0 (7.5, 31.0) | 8.0 (5.5, 12.5) |
| TAR 180 mg/dL, % | 32.5 (27.5, 47.5) | 45.5 (22.0, 62.5) | 37.5 (26.8, 41.8) |
| TBR 70 mg/dL, % | 3.0 (1.0, 5.0) | 2.0 (0.5, 7.5) | 3.5 (1.5, 5.0) |
| TBR 54 mg/dL, % | 1 (0, 1.0) | 0 (0, 0.5) | 0.5 (0, 1.0) |
| CV, % | 38.2 (35.9, 42.6) | 41.7 (37.3, 47.0) | 37.5 (35.4, 41.4) |
| TDD, IU/kg/day | 0.92 (0.76, 1.14) | 0.7 (0.67, 0.72) | 0.96 (0.83, 1.22)* |
Values are presented as number (%) or median (interquartile range).
BMI = body mass index, T1D = type 1 diabetes, HbA1c = glycated hemoglobin A1c, CGM = continuous glucose monitoring, TIR = time in range, TAR = time above range, TBR = time below range, CV = coefficient of variation, TDD = total daily insulin dose.
aSensor-augmented pump including a predicted low-glucose suspension (n = 15) and low-glucose suspension (n = 1).
*P < 0.05.
Quarterly glycemic outcomes compared to baseline
The number of patients using a CGM (active time > 70%) at 3, 6, 9, and 12 months was 20, 19, 19, and 18, respectively. At baseline, the median HbA1c was 7.65% (IQR, 7.25, 8.0), and the median TAR 180 (TAR 250), TIR, TBR 70 (TBR 54), and CV values were 32.5% (9.5%), 62.5%, 3.0% (0%), and 38.2% respectively, with a median of 86% (IQR, 78, 94) of CGM active time (Table 1). After the initiation of the MiniMed 770G system, the median HbA1c levels changed to 7.35%, 7.7%, 7.4%, and 7.55% at the 3-, 6-, 9-, and 12-month follow-ups, respectively, with no statistically significant differences (Supplementary Table 1). However, the median TIR values increased significantly till 6 months, to 70.5% (P = 0.021) and 72% (P = 0.031) at 3- and 6-months, respectively. Despite no significant changes in TBR 70 and TBR 54 values, the median TAR 180 and TAR 250 (< 5%) values changed significantly only at 3 months to 27% (P = 0.047) and 50% (P = 0.046), respectively. The median CV decreased significantly at three and nine months by 35.25% (P = 0.019) and 35.5% (P < 0.05), respectively. Supplementary Table 2 shows previous SAP users’ quarterly glycemic outcomes significant only when the 3-month TIR increased from a median of 65.5% to 70.5% (P < 0.05).
Comparison between high (> 85%) and low (≤ 85%) auto-mode users
The median auto-mode usage rates at 3, 6, 9, and 12 months were 85.5% (IQR, 53, 92.5), 84% (IQR, 55, 93), 84% (IQR, 73, 91), and 80% (IQR, 67, 90), respectively. The number of high auto-mode users (> 85%) decreased over time, with 10, 9, 9, and 7 patients at each time point (Supplementary Fig. 2). Analysis of CGM metrics showed that high auto-mode users (> 85%) had a median HbA1c of 7.4%, TIR of 73%, TAR 250 of 4%, TAR 180 of 25%, TBR 70 of 2%, and CV of 33.5%, whereas low auto-mode users (≤ 85%) had a median HbA1c of 7.5%, TIR of 67%, TAR 250 of 8%, TAR 180 of 30%, TBR 70 of 2%, and CV of 38% at 1 year of follow-up (Fig. 1). According to GEE analysis summarized in Table 2, high auto-mode users demonstrated significantly lower HbA1c (0.75 decrease, P = 0.037 in total participants; 0.84, P = 0.022 in previous SAP users); higher TIR (7.0, P = 0.015; 6.6, P = 0.012); and reduced TAR 250 (5.7, P = 0.012; 6.4, P = 0.005), TAR 180 (6.7, P = 0.031; 6.5, P = 0.026), and CV (3.2, P = 0.001; 2.9, P = 0.008) compared to low auto-mode users, both in the total cohort and among previous SAP users. No significant differences were observed between the groups in TBR 70 or TBR 54.
Fig. 1. Continuous glucose monitors metrics distribution by auto-mode usage rate (> 85% vs. ≤ 85%). (A) HbA1c; (B) TIR; (C) TAR 250; (D) TAR 180; (E) TBR 70; (F) CV. Median and interquartile range values are presented.
HbA1c = glycated hemoglobin A1c, TIR = time in range, TAR = time above range, TBR = time below range, CV = coefficient of variation.
Table 2. Glycemic outcome differences between auto-mode usage rate (> 85% vs. ≤ 85%).
| Glycemic outcomesa | Total (n = 20) | Previous SAP users only (n = 16) | ||
|---|---|---|---|---|
| (95% CI) | P value | (95% CI) | P value | |
| HbA1c | −0.754 (−1.461, −0.047) | 0.037 | −0.84 (−1.56, −0.12) | 0.022 |
| TIR | 6.992 (1.375, 12.609) | 0.015 | 6.64 (1.46, 11.83) | 0.012 |
| TAR 250 | −5.700 (−10.124, −1.276) | 0.012 | −6.36 (−10.79, −1.94) | 0.005 |
| TAR 180 | −6.742 (−12.884, −0.600) | 0.031 | −6.47 (−12.16, −0.78) | 0.026 |
| TBR 70 | −0.250 (−1.210, 0.709) | 0.609 | −0.18 (−1.23, 0.93) | 0.752 |
| TBR 54 | −0.089 (−0.494, 0.316) | 0.667 | −0.04 (−0.52, 0.44) | 0.866 |
| CV | −3.204 (−5.144, −1.264) | 0.001 | −2.89 (−5.03, −0.76) | 0.008 |
CI = confidence interval, HbA1c = glycated hemoglobin A1c, TIR = time in range, TAR = time above range, TBR = time below range, CV = coefficient of variation.
aGlycemic outcome differences of high (> 85%) and low (≤ 85%) auto-mode were analyzed in total (n = 20) and previous sensor-augmented pump users (n = 16) groups, by the generalized estimating equation.
Glycemic outcomes in high (> 85%) auto-mode users
Fig. 2 and Supplementary Table 3 show the quarterly glycemic outcomes of high (> 85%) auto-mode users. TIR, TAR 250, and TAR 180 changed significantly till 6 months. The median TIR increased from 59% to 74.5% at 3 months (P = 0.008) and from 65% to 73% at 6 months (P = 0.012), with the proportion of participants achieving TIR > 70% rising from 10% to 80% at 3 months (P = 0.008) and from 11.1% to 77.8% at 6 months (P = 0.046). The median TAR 180 decreased from 34.5% to 24% at 3 months (P = 0.017) and 33% to 24% at 6 months (P = 0.032), while TAR 250 decreased from 11% to 3.5% at 3 months (P = 0.018); the baseline decreased from 8.0% to 4.0% at 6 months (P = 0.021). Glycemic variability, as measured by CV, also significantly reduced till 9 months. The median CV decreased from 38.2% to 33% at 3 months (P = 0.002), from 38.2% to 32.5% at 6 months (P = 0.010), and from 36.4% to 33.5% at 9 months (P = 0.003). Furthermore, the proportion of participants achieving CV (≤ 36%) increased from a baseline of 30% to 80% at 3 months (P = 0.025) and from a baseline of 44.4% to 88.9% at 9 months (P = 0.046).
Fig. 2. Quarterly glycemic ranges of the continuous glucose monitors report: comparisons with the baseline in high (> 85%) auto-mode users. (A) Baseline vs. 3-month; (B) Baseline vs. 6-month; (C) Baseline vs. 9-month; (D) Baseline vs. 12-month. Values are presented as medians.
*P < 0.05.
Safety and system adherence
No severe hypoglycemia or diabetic ketoacidosis occurred during the 1-year follow-up, including baseline. Fig. 3 shows the 6 major reasons for exiting auto-mode. “Hyperglycemia (35.6%)” and “no calibration (23.6%)” were the most common system messages, followed by “user exit,” “sensor problem,” “others,” and “hypoglycemia.” The quarterly auto-mode exit frequency and reason trend are shown in Supplementary Figs. 3 and 4. “Hyperglycemia” increased from the 9-month follow-up without a significant increasing trend.
Fig. 3. Reasons for auto-mode exit. First, “Hyperglycemia,” encompasses messages including “high SG auto-mode exit” and “auto-mode max delivery.” Second, “no calibration,” includes “no calibration occurred,” “basal glucose required for auto-mode,” and “sensor algorithm underread.” Third, “sensor-related problems,” comprises “sensor updating,” “sensor expired,” and “auto-mode warm up.” Fourth, “hypoglycemia,” is represented by “auto-mode min delivery.” Fifth, “user exit,” which involves “auto-mode disabled by user” and “pump suspended by user.” Last, the category “others,” includes “no SG values,” “alarms,” and “unidentified.” Values are presented as numbers (%).
SG = sensor glucose.
DISCUSSION
This year-long study of Korean youths with childhood-onset T1D demonstrated superior glycemic outcomes with the MiniMed 770G HCL system when auto-mode engagement exceeded 85%. High-adherence users achieved clinically significant reductions in HbA1c levels, increased TIR, and lower glucose variability (CV), alongside decreased TAR. Critically, the TBR remained unchanged, confirming that no elevated risk of hypoglycemia existed. No severe hypoglycemic or diabetic ketoacidosis events occurred during the study period. Hyperglycemia-related exits and calibration lapses were the primary reasons for auto-mode discontinuation. Although limited by the sample size and two-center design, this study provides pivotal evidence for the efficacy and safety of HCL technology in East Asian youth populations with T1D. These findings emphasize the importance of sustained auto-mode engagement in optimizing glycemic control while addressing the behavioral challenges in device adherence.
Similarly, previous studies demonstrated that greater auto-mode use was correlated with greater improvements in HbA1c15,16,17 and TIR.16,17 However, maintaining a high auto-mode usage rate is challenging, and usage rates tend to decrease over time.15,17 Our study had decreased proportions of high (> 85%) auto-mode users from 50% (10/20), 47% (9/19), 47% (9/19), and 39% (7/18) at 3-, 6-, 9-, and 12-month respectively as well. In addition, although not statistically significant, the proportion of hyperglycemia among the reasons for auto-mode exit increased from 9 months. Both the decrease in the high auto-mode usage rate and the increased proportion of hyperglycemia as an exit reason from 9 months onward may explain the lack of improvement in TIR compared to baseline at 9 and 12-month. Major exit reasons reported in previous studies14,18,19 were similar to our findings, both calibration difficulty and hyperglycemia. For advanced HCL (e.g., MiniMed 780G), the next stage insulin pump model, auto-mode exit due to missing calibration does not occur, but to use auto-mode without exit due to hyperglycemia, it is necessary to educate patients not to miss insulin injections before meals. In addition, continuous technical improvements and patient education are needed to address the well-known causes of hyperglycemia such as infusion set malfunctions, pump malfunctions (dead battery, incorrect settings), insulin issues (expired, exposed to temperature extremes), and site problems (irritation, infection).
The application of HCL systems showed significant improvements in TIR and CV at 3- and 6-month follow-ups in an analysis of the total cohort as well as high auto-mode users (> 85%). Although there was no statistical difference in HbA1c levels reflecting 3-month average glucose, TIR and TAR significantly improved with CV reduction. The small sample size in this study (n = 20) may have been difficult to demonstrate statistical power at HbA1c levels with less variation compared to TIR levels. Although our study did not show significant decrease in TBR levels, previous studies20,21,22,23,24 have reported that HCL systems significantly mitigated hypoglycemia risk.
This study has several limitations. As a retrospective real-world analysis rather than a prospective randomized clinical trial, it is constrained by a highly adherent group of small sample size and the inability to fully account for confounding factors such as dietary patterns, physical activity levels, and pubertal development stages. Although we analyzed CGM data spanning 30 days with > 70% sensor active time, the findings might have been more robust with a larger cohort achieving both > 70% CGM adherence and > 85% auto-mode utilization, coupled with extended 90-day glucose datasets. Despite these limitations, the study provides valuable real-world evidence supporting the efficacy of HCL systems in childhood-onset T1D, particularly demonstrating the glycemic advantages of sustained auto-mode engagement (> 85%). The cohort’s homogeneity in diabetes duration and prior CGM experience enhances internal validity, while detailed characterization of auto-mode exit reasons offers practical insights for system optimization. These results corroborate international findings,6,25,26,27 confirming consistent glycemic benefits of HCL technology in East Asian youth populations. Furthermore, this work establishes a foundation for future investigations into psychosocial, algorithmic, and ethnocultural determinants influencing AID outcomes.
In conclusion, the MiniMed 770G HCL system with high auto-mode engagement (> 85%) was effective in improving glycemic control in Korean youth with childhood-onset T1D. No serious adverse events or episodes of severe hypoglycemia were observed during the study period, supporting the safety of the system. Further larger studies are required to validate these findings.
Footnotes
Disclosure: The authors have no potential conflicts of interest to disclose.
- Conceptualization:Woo HA, Jeong SJ, Lee YJ, Kim HY, Gu M, Kim JY, Kim J, Shin CH,.
- Lee YA Data curation:Woo HA.
- Formal analysis:Woo HA, Jeong SJ, Lee YJ.
- Investigation:Woo HA.
- Methodology:Woo HA, Jeong SJ, Lee YJ, Kim HY, Kim J, Shin CH, Lee YA.
- Resources:Lee YJ, Kim HY, Gu M, Kim JY, Kim J, Shin CH, Lee YA.
- Validation:Woo HA, Jeong SJ, Lee YJ, Lee YA.
- Visualization:Woo HA, Jeong SJ, Lee YJ, Lee YA.
- Writing - original draft:Woo HA.
- Writing - review & editing:Woo HA, Jeong SJ, Lee YJ, Kim HY, Gu M, Kim JY, Kim J, Shin CH, Lee YA.
SUPPLEMENTARY MATERIALS
Quarterly glycemic outcomes compared to baseline (n = 20)
Quarterly glycemic outcomes of previous sensor-augmented pump users compared with baseline (n = 16)
Quarterly glycemic outcomes of auto-mode > 85% users compared with baseline
Patient inclusion flow diagram. Schematic depicting inclusion and exclusion criteria by which 20 patients were selected from among the 457 patients with T1D followed-up in the pediatric endocrinology clinics.
Quarterly auto-mode usage distribution.
Quarterly auto-mode exit frequency. Values are presented as median (interquartile range).
Quarterly auto-mode exit trend by reason (exit count per person per month).
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Associated Data
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Supplementary Materials
Quarterly glycemic outcomes compared to baseline (n = 20)
Quarterly glycemic outcomes of previous sensor-augmented pump users compared with baseline (n = 16)
Quarterly glycemic outcomes of auto-mode > 85% users compared with baseline
Patient inclusion flow diagram. Schematic depicting inclusion and exclusion criteria by which 20 patients were selected from among the 457 patients with T1D followed-up in the pediatric endocrinology clinics.
Quarterly auto-mode usage distribution.
Quarterly auto-mode exit frequency. Values are presented as median (interquartile range).
Quarterly auto-mode exit trend by reason (exit count per person per month).