Automated Insulin Delivery (AID) systems represent the most effective and safe treatment for the management of type 1 diabetes (T1D). Antidiabetic agents used for the treatment of type 2 diabetes, such as the Glucagon-Like Peptide-1 (GLP-1) Receptor Agonists (RAs), the dual Glucose-dependent Insulinotropic Polypeptide and GLP-1 RA and the Sodium-Glucose co-Transporter 2 inhibitors are associated with clinically significant weight loss and cardioprotective effect. Given the increased prevalence of overweight, obesity, and cardiovascular risk in patients with T1D, the addition of these medications to AID treatment is of considerable clinical interest. In this review limited data from randomized controlled and observational trials show that in overweight and obese patients with T1D treated with AID, the addition of weekly semaglutide, or tirzepatide is associated with significant weight loss, reduction in total daily insulin dose and increase in Time In target Range (TIR) without increased risk for hypoglycemia and Diabetic Ketoacidosis (DKA). Similarly, adjunctive treatment with empagliflozin resulted in increased TIR without increase in hypoglycemia, reduction in insulin requirements, and increase in the mean plasma ketone value, although DKA remained rare. However, studies of longer duration with more participants are required to establish the long-term safety and efficacy of these interventions in patients with T1D treated with AID.
Older adults represent a growing proportion of people with diabetes and often experience hypoglycemia, glycemic variability (GV), multimorbidity, frailty, and treatment-related vulnerabilities that are not fully captured by glycated hemoglobin A1c (HbA1c) alone. Continuous glucose monitoring (CGM) provides time-resolved glucose profiles, trend information, alerts, and remote data sharing, making it well suited to safety-focused geriatric diabetes care.In this narrative review, we synthesize evidence on CGM features, randomized and real-world outcomes, patient and caregiver experience, barriers to sustained use, and practical implementation in older adults. Across studies, the principal benefits of CGM vary by diabetes type and treatment context. In older adults with type 1 diabetes, randomized evidence most consistently supports reduced hypoglycemia exposure and time below range, whereas in basal-insulin-treated type 2 diabetes, CGM primarily improves time in range and reduces hyperglycemia. CGM may also support individualized treatment adjustment by revealing nocturnal hypoglycemia, GV, and postprandial patterns that are missed by intermittent testing.Real-world studies associate CGM use with fewer acute diabetes events and hospitalizations in selected insulin-treated populations, but residual confounding limits causal interpretation. Implementation evidence shows that benefit depends on more than device performance. Usability, skin tolerability, education, alert burden, caregiver workflows, digital literacy, cost, and equitable access strongly influence sustained use.We propose a pragmatic geriatric CGM pathway with an explicit triage algorithm that emphasizes risk-based candidate selection, functional assessment, tailored device and support models, individualized alerts and glycemic goals, focused review of CGM metrics, structured education, and early follow-up. Current evidence supports CGM primarily as a safety and decision-support technology for selected older adults, particularly those using insulin or at elevated hypoglycemia risk. Future studies should include frail and cognitively impaired populations and prioritize severe hypoglycemia, falls, treatment burden, caregiver burden, acute care use, quality of life, and scalable delivery models.
BACKGROUND:Contemporary data on the natural history of mild non-proliferative diabetic retinopathy (NPDR) in adults with type 1 diabetes managed under intensive therapy and continuous glucose monitoring (CGM) are limited. We aimed to characterize the long-term evolution of mild NPDR in this modern care setting and to explore clinical and glycemic factors associated with regression or progression, including CGM-derived metrics. METHODS:We conducted a retrospective cohort study of adults with type 1 diabetes and mild NPDR identified by digital fundus photography within a screening program between 2018 and 2020. Participants underwent follow-up retinal evaluation after approximately 5 years. Retinopathy outcomes were classified as regression (absence of retinopathy), stability (persistent mild NPDR), or progression (moderate/severe NPDR and/or diabetic macular edema [DME]). Clinical, biochemical, and glycemic variables, including HbA1c and CGM-derived metrics, were collected. Multivariable logistic regression identified factors independently associated with regression of mild NPDR. RESULTS:Among 113 participants (median age 39 years; median diabetes duration 21 years), regression occurred in 57.5%, 31.0% remained stable, and 11.5% progressed. Lower HbA1c at follow-up was observed in participants with regression compared with those without. Several CGM-derived metrics, including time in range and glucose management indicator, were associated with regression in univariate analyses; however, these associations were not independent of HbA1c due to strong collinearity. In multivariable analysis, lower HbA1c was the only independent predictor of regression. CONCLUSIONS:In this real-world screening-based cohort of adults with T1D, mild NPDR demonstrated a highly dynamic course, with more than half of patients experiencing regression over 5 years. Overall glycemic control, reflected by HbA1c, was the primary determinant of regression. CGM-derived metrics did not provide additional predictive value beyond HbA1c in this setting. These findings highlight the potential reversibility of early diabetic retinopathy under contemporary care and underscore the importance of intensive long-term glycemic management.
OBJECTIVE:To examine the associations between continuous glucose monitoring (CGM) metrics, including glucose management indicator (GMI) and overnight glucose levels, and pregnancy outcomes in women with type 1 diabetes. RESEARCH DESIGN AND METHODS:Secondary exploratory analysis of the CRISTAL trial including 95 pregnant women with type 1 diabetes using CGM. Associations were assessed using logistic regression and Spearman correlations, presented as odds ratios (95% confidence intervals [CIs]) adjusted for baseline HbA1c. GMI validity was assessed using scatter and Bland-Altman plots. RESULTS:Each 5% increase in overall pregnancy-specific time-in-range (TIRp) decreased the odds of gestational hypertension (odds ratio [OR] 0.63, 95% CI 0.41-0.97), birthweight >4.5 kg (OR 0.56, 95% CI 0.32-0.96), and neonatal hypoglycemia requiring hospital care (OR 0.09, 95% CI 0.01-0.57). Each 5% increase in overnight TIRp decreased the odds of gestational hypertension (OR 0.71, 95% CI 0.52-0.98) and neonatal hypoglycemia requiring hospital care (OR 0.15, 95% CI 0.03-0.79). Each 5% increase in overall time-above-range (TARp) increased the odds of birthweight >4.5 kg (OR 1.76, 95% CI 1.05-2.96), respiratory distress (OR 1.55, 95% CI 1.02-2.37), and neonatal hypoglycemia requiring hospital care (OR 5.10, 95% CI 1.14-22.78). Each 5% increase in TARp overnight increased the odds of hospital care for neonatal hypoglycemia (OR 2.55, 95% CI 1.15-5.66). Each 0.28 mmol/L increase in mean glucose and 0.5% increase in GMI were associated with increased respiratory distress (OR 1.54, 95% CI 1.07-2.23 and OR 6.15, 95% CI 1.33-28.40). Every 0.28 mmol/L increase in glycemic variability (SD) was associated with gestational hypertension (OR 1.69, 95% CI 1.02-2.80) and birthweight >4.5 kg (OR 2.31, 95% CI 1.20-4.43). Several combinations of CGM metrics (TIRp[-night], TARp[-night], SD, mean glucose) improved discriminative performance for pregnancy outcomes. GMI and HbA1c values were discordant. CONCLUSIONS:Specific combinations of CGM metrics, including overnight TIRp/TARp, may be informative for predicting pregnancy outcomes. GMI and HbA1c should not be considered interchangeable for glycemic control during pregnancy.
OBJECTIVE:To evaluate real-world glycemic outcomes, safety, treatment satisfaction, cognition, and frailty in older adults with type 1 diabetes (T1D) using advanced hybrid closed-loop (aHCL), and to compare them with those of matched older adults treated with multiple daily injections (MDIs). RESEARCH DESIGN AND METHODS:Multicenter observational study including 100 adults with T1D from 19 Spanish hospitals who initiated aHCL at ≥65 years and 100 age- and sex-matched MDI users. Glycemic outcomes before aHCL initiation were compared with the final follow-up. Final glycemic outcomes were also compared between the aHCL and MDI groups. Cognitive function and frailty were assessed using the Montreal Cognitive Assessment and FRAIL scales. RESULTS:Mean age was 71.2 ± 4.4 years. In aHCL users, time in range (TIR 70-180 mg/dL) increased from 65.3% ± 15.0% before aHCL initiation to 78.6% ± 10.5% at the final follow-up (P < 0.001), and HbA1c decreased from 7.56% ± 0.97% to 7.01% ± 0.59% (59.1 ± 10.6 mmol/mol to 53.1 ± 6.4 mmol/mol) (P < 0.001). At the final follow-up, aHCL users had a higher TIR than matched MDI users (78.6% ± 10.5% vs. 63.0% ± 18.1%; P < 0.001) and lower HbA1c (7.01% ± 0.59% vs. 7.65% ± 0.98%; 53.1 ± 6.4 mmol/mol to 59.9 ± 10.7 mmol/mol; P < 0.001). Severe hypoglycemia decreased from 28.0 to 1.6 events per 100 patient-years after aHCL initiation. A total of 60% of aHCL users had mild-to-moderate cognitive impairment, yet the final TIR was similar across cognitive strata within the aHCL group. CONCLUSIONS:In older adults with T1D, real-world aHCL initiation was associated with improved glycemic outcomes and better glycemic outcomes than in matched MDI users in a cohort with substantial cognitive vulnerability. These findings support the effectiveness of aHCL therapy in routine geriatric diabetes care.
BACKGROUND:Continuous glucose monitoring (CGM) is increasingly used in pregnancy, but data on its use in women with type 2 diabetes are limited. AIMS:To describe CGM metrics in pregnant women with type 2 diabetes and assess their association with neonatal outcomes. METHODS:We conducted a prospective, observational cohort study of women with type 2 diabetes, enrolled before 26 weeks of gestation. Participants wore a Dexcom G6 sensor for at least 10 days per trimester. Maternal characteristics and pregnancy outcomes were collected. RESULTS:We recruited 50 women with type 2 diabetes in pregnancy from three diabetes in pregnancy clinics. Women were enrolled at a mean of 16 weeks of gestation, 83% were non-European ethnicity and 74% wore the CGM >80% of the time from enrollment. Participants spent a mean of 73.0% of time in the pregnancy range (TIRp) (3.5-7.8 mmol/L), 25.6% above range (TARp), 1.5% below range, with a mean glucose of 6.8 (1.0) mmol/L across pregnancy. Lower TIRp, higher TARp, and higher mean glucose were significantly associated with large-for-gestational-age (LGA) infants. Mean glucose was significantly higher in those with an LGA infant from 12 weeks onward. LGA was significantly more frequent in those who spent ≤70% TIRp than in those who spent >70% TIRp (46.7% vs. 10.3%; P = 0.02). TARp >30% was significantly associated with the composite neonatal outcome. More than 20% TARp overnight was significantly associated with LGA. A 5% improvement in TIRp reduced LGA by 28% (odds ratio 0.72 [0.54, 0.90; P = 0.009]). Diabetes distress at enrollment was associated with a significantly lower TIRp and higher mean glucose throughout pregnancy. CONCLUSIONS:Several glycemic metrics, including TIRp and mean glucose, were associated with LGA. Higher glucose levels from 12 weeks onward were seen in mothers of LGA infants. Early pregnancy or preconception glucose optimization may be necessary to improve outcomes.
INTRODUCTION:Evidence on the long-term durability of glycemic control beyond the first year of automated insulin delivery therapy remains limited, particularly in large multicenter pediatric cohorts. The present study aimed to evaluate long-term effectiveness and identify determinants of sustained optimal outcomes over 3 years of MiniMed™ 780G use in youth with type 1 diabetes (T1D). MATERIALS AND METHODS:In this longitudinal, multicenter, real-world study, 359 youth with T1D (median age 12.2 years, 50.9% female) from 20 Italian pediatric diabetes centers were followed for 3 years after MiniMed 780G initiation. Glucose metrics, insulin delivery parameters, device settings, and engagement indicators were analyzed at 1, 2, and 3 years. Longitudinal changes were assessed using linear mixed-effects models. Multivariable logistic regression identified predictors of achieving time in tight range target (TITR ≥ 50%) at 3 years. RESULTS:Median time in range (TIR) remained within international targets but declined modestly from 75% at 1 year to 74% at 3 years (P = 0.002). The percentage of automatic correction boluses increased over time, whereas user-initiated boluses and carbohydrate entries declined (P < 0.001). Youth with higher TIR at 1 year showed a progressive reduction in TIR and greater increase in automated corrections (time × group interaction P < 0.001). At 3 years, higher SmartGuard use (odds ratio [OR]: 1.13, 95% confidence interval [CI]: 1.03-1.23; P = 0.007), optimal system settings (OR: 3.21, 95% CI: 1.33-7.77; P = 0.010), and lower automatic correction boluses (OR: 0.84, 95% CI: 0.80-0.89; P < 0.001) were independently associated with achieving TITR ≥50%. CONCLUSIONS:MiniMed 780G provides sustained glycemic control over 3 years. However, progressive reliance on automated corrections and reduced user engagement may attenuate tight glycemic control, highlighting the need for ongoing education and proactive device optimization.
Objective measures of self-management are critical for understanding glycemic outcomes in individuals with type 1 diabetes (T1D). The mealtime insulin bolus score (BOLUS), derived from insulin pump data, is a validated indicator of mealtime insulin engagement in pediatric T1D populations, but its validity in emerging adults (EA) is unknown. We examined associations between BOLUS scores and glycemic outcomes (HbA1c and continuous glucose monitoring metrics) in 347 EA with T1D (ages 18-22). Higher BOLUS scores were associated with lower HbA1c (r = -0.24, P < 0.001), greater time in range (r = 0.23, P < 0.001), and lower time above range (r = -0.23, P < 0.001). The mean BOLUS score (1.17) was substantially lower than the previously reported mean pediatric BOLUS score. Findings support the validity of BOLUS as an objective behavioral measure in EA with T1D and highlight reduced mealtime insulin engagement during this developmental period.
BACKGROUND:Carbohydrate counting (CC) is challenging and may be a barrier to automated insulin delivery (AID) use. Given the ability of AID to modulate insulin delivery, a simpler meal bolus strategy may be adequate for glycemic management. METHODS:Participants aged 14-26 using AID were enrolled in a randomized crossover trial comparing glycemic management using simple boluses versus CC for 4 weeks each. Before the simple period, participants were educated to enter a set carbohydrate amount for a small (30 g), medium (60 g), or large (90 g) meal, and carbohydrate ratios were standardized. Glycemic outcomes were compared between study periods. We hypothesized that time in range (TIR) 70-180 mg/dL would not be inferior by more than 5% during the simple period compared with the CC period. Other measures of glycemia were compared using paired t-tests. RESULTS:Among 31 participants (17.4 years; 51.6% female; type 1 diabetes duration [T1DDur.] 8.3 years; baseline TIR 64.1%), TIR with simple meal boluses was not inferior to TIR with CC (simple TIR 64.2%, CC TIR 66.0%, difference -1.8%, lower limit of 95% confidence interval: -3.9, P = 0.008 indicating noninferiority at a margin of Δ = 5). There were no differences in % time >250 mg/dL (difference 1.2%, P = 0.3) and % time <70 mg/dL (difference -0.02%, P = 0.9). After the study, 31.3% of participants preferred CC, 40.6% preferred simple boluses, and 28.1% preferred their prestudy method. CONCLUSION:Precise CC may be an unnecessary burden for T1D adolescents using AID, and requiring it could impact success with or access to these systems. Using a simple meal bolus strategy is one option to reduce burden without significant impact on glycemic outcomes (Clinical Trials Registration number- NCT06575790).
INTRODUCTION:Tirzepatide, a dual glucose-dependent insulinotropic polypeptide and glucagon-like polypeptide-1 receptor agonist, has significantly increased in use in overweight (OW)/obese people with type 1 diabetes (T1D). It is not known if tirzepatide affects the incidence and/or progression of diabetic retinopathy (DR), including diabetic macular edema (DME), in individuals with T1D. METHODS:We performed a retrospective chart review of OW/obese people with T1D using adjunctive tirzepatide treatment continuously for at least 1 year ± 2 months (cases, n = 106). Eighty-five controls with T1D not using tirzepatide were matched by age, sex, and body mass index. Retinal eye examination results were collected at baseline and follow-up (6-24 months). Cases were eligible if temporary drug discontinuations were ≤1 month. For individuals without baseline eye disease, the incidence rates of DR and DME were analyzed. For individuals with baseline DR and/or DME, progression and regression of eye diseases were evaluated. RESULTS:Mean diabetes duration was 26.2 years (cases) and 28.0 years (controls). Baseline DR and/or DME rates were high in both groups (63.2% cases vs. 71.8% controls). Most people in both groups were using an automated insulin delivery system. Mean glycated hemoglobin A1C (HbA1c) improved within 6 months (P < 0.001) and remained stable for cases, but was unchanged for controls. New-onset DR developed in 10/39 (25.6%) of cases and 7/24 (29.2%) of controls over a mean follow-up of 11.7 and 15.3 months, respectively. Incident DR occurred more frequently in individuals (cases and controls) with a rapid HbA1c decline (≥0.5% within 6 months) compared with those without it (11/28 [39.3%] vs. 6/35 [17.1%], P = 0.048). Among cases and controls with baseline DR, eye disease remained stable at follow-up for most individuals. CONCLUSIONS:OW/obese individuals with T1D treated with off-label tirzepatide developed DR similar to controls. Randomized controlled trials are needed to confirm these findings.
OBJECTIVE:Hypoglycemia remains a major concern in insulin therapy and has limited intensive glycemic control. Although automated insulin delivery substantially reduces hypoglycemia risk, relatively high low-glucose alert (LA) thresholds (LGAT) remain commonly used. This study evaluated the impact of user-set LGAT on glycemic outcomes. RESEARCH DESIGN AND METHODS:This retrospective cohort study analyzed anonymized real-world data from 169,487 MiniMed 780G users with type 1 diabetes across Europe, the Middle East, and Africa (August 1, 2024-July 31, 2025). Use of LAs, user-set thresholds, and glycemic metrics was evaluated. RESULTS:Most users (96%) enabled LGAT, and 36% enabled predictive LGAT. Median, 25th and 75th percentiles of time below 54 and 70 mg/dL remained low and within recommended targets across all alert thresholds overall, in users aged ≤15 years, and overnight. Hypoglycemia targets were achieved by >82% and >90% of users with thresholds <60 and ≥60 mg/dL, respectively. In contrast, time in range (TIR) 70-180 mg/dL and hyperglycemia targets were more frequently achieved with LGAT <60 mg/dL, with 70% and 61% meeting these targets, respectively. Overall, 43% of users with LGAT <60 mg/dL met all glycemic targets versus 31% with thresholds >80 mg/dL. CONCLUSIONS:A LGAT below 60 mg/dL is generally recommended, as it is associated with increased TIR, reduced hyperglycemia, and low time in hypoglycemia. A threshold between 60 and 70 mg/dL may provide a balanced option for those with greater hypoglycemia concerns. These recommendations can optimize system usability and glycemic outcomes while maintaining safety and minimizing alarm burden.
BACKGROUND:The rising incidence of early-onset type 2 diabetes (T2D) has made it the leading cause of pregestational diabetes worldwide. However, real-world data on glycemic control during pregnancy and its association with perinatal outcomes remain limited. OBJECTIVE:To examine associations between continuous glucose monitoring (CGM)-derived metrics and perinatal outcomes throughout pregnancy and across gestational windows in women with T2D. METHODS:We conducted a single-center retrospective cohort study including all pregnant women with T2D who delivered between January 2020 and August 2025 and used CGM for ≥7 days (n = 80). The primary composite outcome included preterm birth (<37 weeks), large-for-gestational-age infant, neonatal hypoglycemia, shoulder dystocia, neonatal intensive care admission, hyperbilirubinemia, or perinatal mortality. CGM metrics included mean glucose, time in range (TIR63-140), time below range, and glucose coefficient of variation. Associations were assessed using mean differences and adjusted logistic regression. RESULTS:Among 80 women (mean (±standard deviation) age 34 ± 6 years; body mass index 33 ± 7 kg/m2; glycated hemoglobin 7.4% ± 1.7%), 24 (30%) were diagnosed during pregnancy. Median (interquartile range) CGM use was 118 (69-187) days. Mean TIR63-140 was 72% ± 13%; 50 (63%) women achieved TIR63-140 ≥70%, 19 (24%) achieved ≥80%, and only 5 (6%) achieved the ≥90% target. Perinatal events occurred in 53 (66%) women. Mean glucose was higher (+11 mg/dL; 95% confidence interval [CI], +5 to +16) and TIR lower (-8.1 percentage points; 95% CI, -13.2 to -3.0) in women with events, with differences apparent from 9 to 12 weeks of gestation. Each 10-point decrease in TIR63-140 was associated with higher odds of perinatal events (adjusted odds ratio 1.82; 95% CI, 1.19-3.00). No significant differences were observed for other CGM-derived metrics. CONCLUSION:In women with T2D, poorer CGM-assessed glycemic control was associated with perinatal events from early pregnancy. Few women achieved the recommended glycemic targets, highlighting the need for improved management and prevention.
AIMS:This study aimed to investigate the associations between glycemic outcomes and a range of clinical and demographic factors, including treatment modality, sex, age, diabetes duration, and body mass index, in youth with type 1 diabetes in an international registry. METHODS:This observational, cross-sectional cohort study included youth <21 years from 23 countries. Proportions of individuals using different treatment modalities (continuous glucose monitoring [CGM] with injections, CGM with pump, automated insulin delivery [AID]) and achieving recommended time in tight range (TITR >50%), time in range (TIR >70%), and glycated hemoglobin (HbA1c) (≤6.5% [48 mmol/mol] and ≤7% [53 mmol/mol]) were assessed using mixed-effects fractional logistic and linear regression models. Sex, age (categorized), diabetes duration (categorized), body mass index standard deviation score (categorized), and treatment modality were included as covariates. RESULTS:Data of 7691 individuals (mean [standard deviation] age of 13.7 [4.3] years, diabetes duration 6.3 [4.2] years, 47.8% female) were included. AID users were the most likely to achieve TITR target (adjusted mean [standard error of the mean] 41.2% [2.9]), followed by CGM with insulin pump (25.2% [2.3]) and CGM with injections (13.7% [1.5], P < 0.001). A similar association was observed for proportions of individuals achieving TIR and HbA1c targets (P < 0.001). Age <6 years was associated with a higher coefficient of variation (CV) (P < 0.001) and a lower probability of achieving both TITR and TIR targets compared with other age groups (P < 0.001). In analyses of TITR associated with mean sensor glucose stratified by CV, a higher TITR for a lower CV was observed only at mean glucose levels below 150-160 mg/dL; above this threshold, the pattern reversed, with lower CV associated with lower TITR at a given mean glucose level. CONCLUSIONS:Children younger than 6 years and individuals not using glucose-responsive insulin therapy were less likely to meet the recommended glycemic targets. It is imperative to minimize these disadvantages.
OBJECTIVE:To evaluate long-term trends in metabolic outcomes among people living with type 1 diabetes (T1D) within a nationwide structured care program in Belgium with full reimbursement of diabetes technologies. METHODS:Repeated cross-sectional analyses were performed across three audit periods (2010-2011, 2017-2018, and 2023-2024). Outcomes included glycated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, systolic blood pressure (SBP), and body mass index. Trends were analyzed using generalized estimating equations adjusted for age, sex, diabetes duration, insulin delivery, and glucose monitoring modalities. In 2023-2024, glycemic outcomes were compared across technology use, including hybrid closed-loop (HCL) therapy. RESULTS:In adults, HbA1c decreased from 7.9% (62.8 mmol/mol) to 7.5% (58.5 mmol/mol, P < 0.001), with target attainment (<7%; <53 mmol/mol) increasing from 22.3% to 35.1%. In children and adolescents, HbA1c declined from 8.0% (63.5 mmol/mol) to 7.6% (59.0 mmol/mol, P < 0.01), and target attainment rose from 19.7% to 33.1% (P < 0.001). Continuous glucose monitoring (CGM) exceeded 90% by 2023-2024, while insulin pump use reached 25% in adults and 47% in younger individuals. In adults, HCL therapy was associated with lower HbA1c (7.0%; 53.5 mmol/mol), higher time-in-range (73%), and lower time-below-range (1.5%) compared with other modalities (P < 0.001). LDL cholesterol improved, with target attainment (<70 mg/dL; <1.8 mmol/L) increasing from 18.3% to 37.4% (P < 0.001), and from 15.5% to 46.5% among those with cardiovascular disease (<55 mg/dL; <1.4 mmol/L, P < 0.001). SBP remained stable. Obesity prevalence increased in all age groups. CONCLUSIONS:Over 14 years, glycemic and lipid outcomes improved alongside near-universal CGM use and increasing adoption of HCL therapy. However, rising obesity and persistent smoking-related risks highlight the need for targeted prevention strategies. These real-world data confirm that benefits seen in clinical trials translate into durable population-level improvements and support integrated care models for implementing diabetes technology effectively.
OBJECTIVE:Identifying programmable device settings and user behaviors associated with achieving glycemic targets is critical for informing clinical practice and improving outcomes with automated insulin delivery (AID) systems. This real-world analysis aimed to identify predictors of achieving optimal glycemic outcomes for people with type 1 diabetes (T1D) using the Omnipod® 5 AID System. METHODS:This retrospective analysis included real-world data from Omnipod 5 users aged ≥ 2 years with T1D in the United States and Europe who had sufficient continuous glucose monitor data (≥30 days with ≥1 reading; ≥75% of days with ≥220 readings) available in Insulet's device and person-reported datasets between January 1 and March 31, 2025. Logistic regression was used to identify programmable settings and user behaviors associated with achieving >70% time in range (TIR; 70-180 mg/dL [3.9-10.0 mmol/L]). Optimal thresholds for the top modifiable predictors were determined using Youden's J statistic, and their impact on glycemic outcomes was explored. RESULTS:Data from 176,405 users were analyzed. Predictors of achieving >70% TIR included the following: a higher number of user-initiated boluses/day, greater time in Automated Mode, use of lower glucose targets, and a more aggressive correction factor (CF) and insulin-to-carbohydrate (I:C) ratio (all P < 0.001). Use of optimized device settings (110 mg/dL [6.1 mmol/L] target, I:C ratio ≤350/total daily insulin dose [TDD], and CF ≤1500/TDD [mg/dL] or ≤83/TDD [mmol/L]) with user behaviors that reflect expected system use (≥90% time in Automated Mode, ≥3 boluses/day), used by 7.9% and 1.4% of adult and pediatric users, respectively, resulted in a higher median TIR compared with users overall (77% vs. 66% in adult and 78% vs. 62% in pediatric users, respectively), and time spent in hypoglycemia remained low across age groups. Findings were consistent across geographic regions and prior insulin regimen. CONCLUSIONS:These results provide actionable guidance for clinicians to optimize outcomes for people with T1D using the Omnipod 5 System.
Inpatient diabetes management is challenging due to acute illness, variable insulin requirements, and reliance on intermittent point-of-care glucose testing. Both hyperglycemia and hypoglycemia are associated with increased costs, length of stay, morbidity, and mortality. However, efforts to achieve tighter glycemic targets are often limited by the risk of iatrogenic hypoglycemia. Notably, hypoglycemia (glucose <3.9 mmol/L, <70 mg/dL) occurs in approximately 10% of patients in intensive care unit (ICU) settings and 3.5% of non-ICU patients and is strongly linked to mortality. Automated insulin delivery (AID) systems may improve inpatient glycemic targets while minimizing the risk of hypoglycemia. This systematic review aimed to evaluate the effects of AID systems in hospital settings. A systematic literature search was conducted on March 27, 2026, in MEDLINE, Embase, and CENTRAL, without restrictions on publication date. Randomized controlled trials (RCTs) involving inpatients managed with AID systems were included if they reported glycemic and/or clinical outcomes. Analyses were performed for ICU and non-ICU settings separately. The primary outcome was time in range (TIR) 5.6-10.0 mmol/L (100-180 mg/dL). The reporting follows the PRISMA 2020 guidelines, and the protocol was registered with PROSPERO (CRD420261308501). A total of 4858 references were screened. Five RCTs from the non-ICU setting (N = 300 participants [>80% with type 2 diabetes]) and three RCTs from the ICU setting (N = 142 [with and without preexisting diabetes]) were identified. Meta-analysis of RCTs in the non-ICU setting showed that AID increased TIR by 24.6 percentage points (95% confidence interval 20.7-28.5). A meta-analysis on ICU data could not be conducted. Across all settings, AID was associated with reduced hyperglycemia without an increase in hypoglycemia. Clinical outcomes were sparsely reported. AID systems can be safely and effectively used in non-ICU hospital settings to improve glycemic outcomes. Larger, multicenter trials are needed to confirm clinical benefits and address implementation challenges.
Early identification of children with type 1 diabetes at heightened risk for diabetic ketoacidosis (DKA) is necessary for preventive intervention. The present study aimed to examine whether an automated electronic medical record-based tool (the Risk Index for Diabetic Ketoacidosis [RI-DKA]) can reliably predict risk for future DKA using data obtained from only the first 6 months post diagnosis. Data were extracted for 3946 children who met the inclusion criteria. The RI-DKA showed an acceptable ability to discriminate between children who did and did not go on to experience a subsequent DKA event (area under the curve = 0.75), only slightly below the predictive ability in the RI-DKA validation sample. These findings indicate that the RI-DKA is a valuable tool for identifying at-risk children very early in the course of type 1 diabetes.
