# Advanced Hybrid Closed-Loop Systems Versus Sensor-Augmented Pump Therapy in Adolescents with Type 1 Diabetes: A Comprehensive Literature Review of Time-in-Range Outcomes Over Minimum 6-Month Periods

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### Background and Context

Type 1 diabetes (T1D) is one of the most prevalent chronic conditions affecting children and adolescents worldwide. In 2022, an estimated 1.52 million individuals under the age of 20 were living with T1D globally, and the management of this condition during adolescence represents one of the most clinically challenging scenarios in all of pediatric endocrinology (PMC11524997). Adolescence is characterized by profound hormonal and physiological changes — including puberty-associated insulin resistance, erratic meal and exercise patterns, increasing autonomy from parental supervision, and heightened psychosocial stressors — all of which conspire to worsen glycemic control precisely at the developmental stage when long-term complication trajectories are being established (PMC11019566). The majority of young people with T1D do not achieve the guideline-recommended HbA1c below 7% (53 mmol/mol), as suggested by all major guidelines (PMC9437950). This persistent gap between therapeutic goals and real-world outcomes has driven decades of technological innovation in insulin delivery.

The central metric for evaluating glycemic control in T1D has evolved substantially over the past decade. While HbA1c remains the cornerstone of long-term glycemic assessment, continuous glucose monitoring (CGM) has enabled the measurement of time-in-range (TIR), defined as the percentage of time sensor glucose values remain within 70–180 mg/dL (3.9–10.0 mmol/L). International consensus guidelines now recognize TIR ≥70% as a primary therapeutic target for most individuals with T1D (PMC10613700). Sensor-augmented pump (SAP) therapy — combining real-time CGM with continuous subcutaneous insulin infusion (CSII) — represented a major advance over multiple daily injections (MDI) and conventional pump therapy, demonstrating HbA1c reductions and improved hypoglycemia detection. However, SAP therapy still requires substantial user engagement for insulin dose decisions, and the Cambridge 12-week RCT demonstrated that hybrid closed-loop insulin delivery significantly improved TIR and reduced hypoglycemia compared with SAP therapy in individuals with suboptimally controlled T1D across all age groups, including adolescents (PMC6182127).

The emergence of hybrid closed-loop (HCL) and advanced hybrid closed-loop (AHCL) systems represents the most significant paradigm shift in T1D management since the introduction of CGM. These systems integrate CGM data with algorithm-directed insulin pump delivery, automating basal insulin adjustments and — in the case of AHCL systems — delivering automatic correction boluses in response to predicted or actual hyperglycemia. The distinction between standard HCL (e.g., Medtronic MiniMed 670G, which targets 120 mg/dL and delivers micro-boluses) and AHCL systems (e.g., Medtronic MiniMed 780G and Tandem t:slim X2 with Control-IQ) is clinically important. The 780G incorporates individualized basal target set points (100, 110, and 120 mg/dL) and autocorrection insulin boluses to a fixed glucose target of 120 mg/dL, and real-world studies have demonstrated meaningfully superior glycemic outcomes for AHCL over standard HCL systems (PMC8630740). The question of precisely how much TIR improvement AHCL systems confer over SAP therapy in adolescents aged 12–18 years, over a minimum 6-month period, is the central clinical question this review addresses — a question with direct implications for treatment guidelines, health technology assessment, and reimbursement decisions across healthcare systems.

The clinical urgency of this question is underscored by the rapid regulatory approval and real-world deployment of AHCL systems across Europe, North America, and beyond. According to data from the Gaslini Institute study, the Tandem Control-IQ system is approved for use from 6 years of age in both the USA and Europe, and the Medtronic MiniMed 780G is approved for use from 7 years of age (PMC12242179). The NHS England Closed Loop Study in Children and Young People, launched in 2021, enrolled 251 children and young people across eight centers, representing the first nationwide pilot to extend universal health coverage for HCL systems in a pediatric population (PMC11044460). Real-world registry data from national pediatric diabetes registries — including the Czech ČENDA registry with over 95% population coverage — now provide population-level evidence on comparative effectiveness across different HCL platforms (PMC10613700). Against this backdrop, synthesizing the available evidence on TIR outcomes in adolescents specifically, over clinically meaningful follow-up periods, is both timely and essential.

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### Mechanistic and Algorithmic Basis for TIR Improvement

#### Automated Insulin Delivery Algorithms: Model Predictive Control and Proportional-Integral-Derivative Approaches

The glycemic improvements observed with AHCL systems over SAP therapy are mechanistically grounded in the fundamental difference between algorithm-directed and user-directed insulin delivery. In SAP therapy, the pump delivers a pre-programmed basal rate and the user manually administers correction and meal boluses based on CGM readings and carbohydrate estimates. The algorithm has no capacity to respond to rising or falling glucose trends in real time beyond threshold-suspend features. In contrast, AHCL systems employ sophisticated control algorithms that continuously recalculate insulin delivery requirements based on current sensor glucose, rate of change, predicted future glucose trajectory, and individualized pharmacokinetic parameters.

The Tandem Control-IQ system uses a Model Predictive Control (MPC) algorithm that predicts glucose into the future and adjusts basal insulin delivery accordingly, delivering automatic correction boluses when predicted glucose exceeds threshold (PMC12242179). The MPC approach used in the Cambridge FlorenceM system — tested in the landmark 12-week RCT by Tauschmann et al. — targets a glucose level of 5.8–7.3 mmol/L and recalculates insulin infusion rates every 10 minutes based on model-based glucose predictions (PMC6182127). This adaptive, individualized approach is mechanistically distinct from the fixed basal rate adjustments of SAP therapy and explains the particularly pronounced overnight TIR improvements observed with closed-loop systems: during sleep, when meal-related glucose excursions are absent and the algorithm can operate without the confounding effects of carbohydrate intake, the MPC algorithm achieves near-perfect glucose regulation, with the Cambridge system achieving 77% TIR overnight versus 56% with SAP in the 12-week RCT (PMC6182127).

The Medtronic MiniMed 780G employs a SmartGuard algorithm capable of delivering automatic correction boluses as frequently as every 5 minutes, a substantially more aggressive correction frequency than the Control-IQ system's maximum of once per hour (PMC12242179). The glycemic target for the 780G is user-adjustable, with the most aggressive target associated with the highest TIR in pivotal trials (PMC8630740). This algorithmic architecture — frequent automatic correction, low glycemic target, self-adjusting basal — mechanistically explains why the 780G achieves the lowest HbA1c and highest TIR in comparative real-world studies, while also achieving the lowest hypoglycemia burden among AHCL systems (PMC10613700).

#### The Role of Automatic Correction Boluses in Reducing Hyperglycemia

A critical mechanistic distinction between AHCL and SAP therapy is the automatic correction bolus feature. In SAP therapy, correction of hyperglycemia is entirely user-dependent: the patient must recognize elevated glucose, calculate a correction dose, and manually administer it. In adolescents — who frequently miss correction boluses due to school schedules, social situations, or simple inattention — this user-dependency is a major source of time above range (TAR). AHCL systems eliminate this dependency by automatically delivering correction insulin whenever the algorithm predicts or detects hyperglycemia, without requiring any user action.

The clinical importance of this feature is demonstrated quantitatively in multiple studies. In the 6-month real-world comparison of AHCL (780G) versus standard HCL (670G) in children and adolescents, the auto-correction rate for 780G users increased significantly from 26% at Auto Start to 38% at 1 month (p=0.01), and a higher auto-correction rate was one of only three variables that independently predicted TIR >70% in multivariate analysis (p=0.03) (PMC8630740). In the 1-year prospective study of 780G in children and adolescents (mean age 9.9 years), auto-corrective boluses increased significantly from 2.85 ± 2.42 U at baseline to 4.09 ± 2.60 U at 12 months (p<0.05), associated with maintained TIR of approximately 80% throughout the observation period (PMC9592809). In the Slovenian AHCL study (n=24 adolescents, mean age 14.5 years), switching from conventional therapy (including first-generation HCL and PLGS systems) to AHCL (investigational 780G) was associated with a reduction in TAR >10 mmol/L from 28.00% to 18.7% (p=0.001) and TAR >13.9 mmol/L from 7.92% to 3.58% (p=0.006) (PMC9437950).

#### Overnight Glucose Control: The Mechanistic Advantage of Closed-Loop Systems

The mechanistic advantage of AHCL over SAP is most pronounced during the overnight period, when the absence of meal-related glucose excursions allows the algorithm to operate in its most effective domain. During sleep, glucose variability is primarily driven by basal insulin requirements, which vary substantially across individuals and even within the same individual across nights due to factors including prior exercise, stress hormones, and growth hormone secretion (particularly relevant in adolescents). SAP therapy delivers a fixed pre-programmed basal rate that cannot adapt to these real-time variations; AHCL systems continuously adjust basal delivery and deliver correction boluses as needed.

In the Cambridge RCT, the closed-loop group achieved 77% overnight TIR versus 56% with SAP, a 21.5 percentage-point improvement (95% CI 17.9–25.0; p<0.0001), which was substantially larger than the daytime benefit of 5.9 percentage points (95% CI 3.1–8.7; p<0.0001) (PMC6182127). The NHS England real-world study similarly documented that reduced nocturnal hypoglycemia and improved overnight glucose stability were among the most consistently reported benefits of HCL systems, with significant improvements in sleep quality for both patients and parents at 6 and 12 months (PMC11044460). Qualitative data from the South African IPA study corroborated this, with adolescents specifically citing reduced fear of nocturnal hypoglycemia and improved sleep as transformative benefits of closed-loop technology (PMC11524997).

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### Clinical Evidence and Implications

#### The Cambridge 12-Week Randomized Controlled Trial: Foundational Evidence

The most methodologically rigorous evidence directly comparing closed-loop insulin delivery to SAP therapy in a mixed pediatric-adult population comes from the multinational, multicentre, open-label, parallel-group RCT conducted by Tauschmann et al. (2018), which enrolled 86 participants (46 closed-loop, 40 SAP control) across six sites in the UK and USA (PMC6182127). This study is foundational for understanding the TIR benefit of closed-loop over SAP, though its 12-week duration falls short of the 6-month minimum specified in the user's question. The Cambridge 12-week RCT (Tauschmann et al., 2018) enrolled 86 participants (46 closed-loop, 40 SAP control) across six sites in the UK and USA, with participants aged 6 years and older (19 aged 13–21 years, 33 aged 6–12 years, 44 aged ≥22 years) and HbA1c between 7.5% and 10% at screening (PMC6182127).

In the Cambridge 12-week RCT, TIR was 10.8 percentage points higher in the closed-loop group (65%, SD 8) than in the SAP control group (54%, SD 9; 95% CI 8.2–13.5; p<0.0001), HbA1c was significantly lower in the closed-loop group at 12 weeks (7.4% vs. 7.7%; difference −0.36%, 95% CI −0.53 to −0.19; p<0.0001), mean sensor glucose was lower (8.9 vs. 9.7 mmol/L; difference −0.82 mmol/L, 95% CI −1.06 to −0.57; p<0.0001), and time above 10.0 mmol/L was reduced by 10.3 percentage points (p<0.0001), and time below 3.9 mmol/L was reduced by 0.83 percentage points (95% CI −1.40 to −0.16; p=0.013) (PMC6182127). This improvement was consistent across all three age subgroups, both sexes, and both high and low baseline HbA1c strata. The overnight benefit was particularly pronounced: 21.5 percentage points improvement in overnight TIR (95% CI 17.9–25.0; p<0.0001), with the closed-loop group achieving 77% overnight TIR versus 56% in the SAP group.

Critically, the closed-loop system used in this trial was an investigational device (Cambridge FlorenceM system with modified Medtronic 640G pump and Enlite 3 sensor), not a commercially available AHCL system. In the Cambridge 12-week RCT, closed-loop use was achieved for a median of only 71% (63–83%) of the intervention period, and the threshold-suspend feature was disabled in the SAP control group by design, potentially underestimating the benefit of modern SAP therapy with predictive low-glucose suspend (PMC6182127). The study's 12-week duration, while the longest randomized outpatient closed-loop study at the time of publication, does not capture the 6-month minimum specified in the user's question, and the mixed age range (6 years and older) means adolescent-specific effect sizes cannot be directly extracted from the published data.

#### The NHS England Real-World Study: 12-Month Outcomes in Children and Young People

The NHS England Closed Loop Study in Children and Young People (PMC11044460) represents the largest real-world dataset on HCL outcomes in a pediatric population in the UK, enrolling 251 CYP with T1D (mean age 12.3 years, SD 3.5; range 2–19 years; 58% male) from eight paediatric centres between August 2021 and December 2022. Three HCL systems were used: Tandem Control-IQ (78%), Medtronic MiniMed 780G (11%), and CamAPS FX (11%). This study is particularly relevant to the user's question because it reports outcomes at 3, 6, and 12 months, with 221 participants having complete 12-month glycaemic data.

In the NHS England study, TIR increased from a baseline of 48.7% (SD 15.3) to 64.7% (SD 11.8) at 3 months, 63.0% (SD 12.4) at 6 months, and 62.0% (SD 12.0) at 12 months (all p<0.001), representing a sustained improvement of approximately 13–16 percentage points. HbA1c fell from 62.3 (SD 12.1) mmol/mol at baseline to approximately 55 mmol/mol at 6 and 12 months. Time in hypoglycaemia (≤3.9 mmol/L) decreased from 3.6% to 2.0% (SD 1.6) at 12 months (p<0.001) (PMC11044460). The majority of the benefit was established by 3 months and maintained thereafter.

A critical limitation of this study for the user's specific question is the absence of a SAP comparator arm. The study reports pre-HCL versus post-HCL comparisons, but participants were not randomized to SAP therapy as a control. The baseline TIR of 48.7% reflects the pre-HCL state, which included participants on MDI, conventional pump therapy, and some on SAP — the study does not stratify outcomes by prior therapy type. The NHS England study found no statistically significant differences in biochemical, hypoglycaemia, or sleep score measures at 12 months among the different types of HCL systems used (Control-IQ, 780G, CamAPS FX) (PMC11044460).

#### The AHCL vs. Standard HCL Comparison: 6-Month Real-World Data from Trieste

The retrospective real-world study from the Institute for Maternal and Child Health "Burlo Garofolo" in Trieste, Italy (PMC8630740) provides the most directly relevant 6-month comparative data, comparing AHCL (Medtronic MiniMed 780G, n=24) versus standard HCL (Medtronic MiniMed 670G, n=20) in 44 pediatric patients (median age at HCL start 13.3 years, range 2–21 years; 27 female). While this comparison is AHCL versus standard HCL rather than AHCL versus SAP, it provides critical insight into the incremental benefit of the advanced algorithm over a less sophisticated closed-loop system, and the baseline Manual Mode data serve as a proxy for pre-HCL glycemic status.

In the Trieste 6-month real-world study comparing AHCL (780G, n=24) versus standard HCL (670G, n=20) in 44 pediatric patients (median age 13.3 years), TIR increased from Manual Mode to 6 months by a median of 14% (IQR 7–26) for AHCL users versus 7% (IQR −2 to 19) for standard HCL users (p=0.20 for difference). The proportion achieving TIR >70% at 6 months was significantly higher in AHCL users (54% vs. 25%, p=0.04). HbA1c at 6 months was significantly lower in AHCL users (7.1% vs. 7.7%, p=0.02) (PMC8630740). In the Trieste study, among patients with worst baseline glycemic control (HbA1c >8%), AHCL users showed a dramatic HbA1c reduction to 7.1% at 6 months versus 8.1% in standard HCL users (p<0.01), with a significantly larger ΔHbA1c (−1.4% vs. −0.3%, p=0.04) (PMC8630740). In the Trieste study, younger age (p<0.01), higher auto-correction rate (p=0.03), and lower CHO entered (p=0.02) independently predicted TIR >70% in AHCL users in multivariate analysis (PMC8630740).

The study's limitations are substantial: the retrospective design, single-center setting, small sample size (n=44), and the comparison of sensor-specific metrics against Manual Mode rather than pre-HCL treatment all limit causal inference. The comparison of AHCL versus standard HCL rather than AHCL versus SAP means the TIR difference attributable to AHCL over SAP cannot be directly extracted. However, the study provides the first real-world data on 780G in children under 14 years, including pre-school-aged children, and the finding that younger age, higher auto-correction rate, and lower CHO entered independently predicted TIR >70% in AHCL users has important clinical implications for adolescent management.

#### The Czech ČENDA Registry: Population-Level Comparative Effectiveness of Three HCL Systems

The retrospective, registry-based cohort study from the Czech national pediatric diabetes registry ČENDA (PMC10613700) provides the most comprehensive population-level comparative effectiveness data. The Czech ČENDA registry has over 95% population coverage and provides population-level evidence on comparative effectiveness across different HCL platforms (PMC10613700). The Czech ČENDA registry analyzed 512 children aged <19 years (mean age 12.8 ± 4.2 years) who used one of three HCL systems for at least 12 months: Medtronic MiniMed 780G (n=217, 42.4%), Tandem Control-IQ (n=211, 41.2%), and AndroidAPS (n=84, 16.4%) (PMC10613700). This study is particularly valuable because it captures the 12+ years age subgroup (n=323, the most represented age category) and applies propensity score weighting to adjust for baseline differences.

After propensity score weighting, TIR was 76% for 780G users, 75% for AAPS users, and 75% for Control-IQ users, with a statistically significant difference between 780G and Control-IQ (p=0.02) but no significant difference between 780G and AAPS (p=0.99) (PMC10613700). The 780G achieved the lowest hypoglycemia burden (mean TBR1 2.5% vs. 2.9% for Control-IQ and 5.2% for AAPS) and the lowest Glycemia Risk Index (median GRI 27 vs. 31 for Control-IQ and 32 for AAPS; p<0.005 for 780G vs. each other group) (PMC10613700). AAPS users achieved the lowest HbA1c (44 mmol/mol; 6.2%) but the highest hypoglycemia rates, while 780G users had the highest HbA1c (52 mmol/mol; 6.9%) but the lowest hypoglycemia burden (PMC10613700). Large real-world studies reported mean TIR of 73.9% in 3,211 children treated with 780G (Arrieta et al.) and 73.5% in 9,451 children using Control-IQ (Breton et al.), consistent with the ČENDA registry findings (PMC10613700).

Critically, this study does not include a SAP comparator arm, so the TIR difference between HCL systems and SAP cannot be directly quantified from these data. However, the ČENDA data suggest that well-managed children and adolescents on HCL systems achieve median TIR of 75–78%, implying a potential improvement of approximately 20–25 percentage points over typical SAP therapy TIR in adolescents.

#### The Slovenian AHCL Study: 4-Month Outcomes with Patient-Reported Outcomes

The single-center longitudinal crossover study from Slovenia (PMC9437950) enrolled 24 adolescents with T1D (14 female; mean age 14.5 ± 1.7 years; mean diabetes duration 7.2 ± 3.7 years) and compared outcomes before and after switching to AHCL (investigational Minimed 780G) over 4 months. While the follow-up duration falls short of the 6-month minimum, this study is notable for its focus on the adolescent age range and its inclusion of patient-reported outcome measures alongside glycemic data.

In the Slovenian AHCL study (n=24 adolescents, mean age 14.5 ± 1.7 years, 4-month follow-up), TIR increased from 68.22% (SD 13.90) on conventional therapy to 78.26% (SD 6.29) on AHCL (p<0.001), a 10.04 percentage-point improvement. Mean glucose fell from 8.55 to 7.74 mmol/L (p=0.002) and SD of mean glucose decreased from 3.06 to 2.76 mmol/L (p=0.011). TBR did not change significantly (PMC9437950). In the Slovenian AHCL study (n=24 adolescents, mean age 14.5 years), switching to AHCL (investigational 780G) was associated with a reduction in TAR >10 mmol/L from 28.00% to 18.7% (p=0.001) and TAR >13.9 mmol/L from 7.92% to 3.58% (p=0.006) (PMC9437950).

An important caveat is that approximately half of participants were already using first-generation HCL or predictive low-glucose suspend systems at baseline, meaning the TIR improvement of 10 percentage points represents the incremental benefit of AHCL over a mixed conventional/first-generation HCL comparator, not over SAP specifically. The baseline TIR of 68.22% is substantially higher than the 48.7% baseline reported in the NHS England study (PMC11044460), reflecting the more technology-experienced nature of this Slovenian cohort. The 4-month follow-up duration is a significant limitation for the user's question.

#### The Italian Non-Compliant Adolescent Study: 6-Month AHCL Outcomes in a High-Risk Population

The retrospective observational case series from San Raffaele, Italy (PMC11019566) provides uniquely relevant data for the adolescent population, enrolling 20 non-compliant adolescents with T1D (mean age 15.7 ± 1.9 years; 55% female; mean baseline HbA1c 10.0 ± 1.7%) who were initiated on the Tandem Control-IQ AHCL system after previously using MDI and flash glucose monitoring. This study is directly relevant to the user's question because it reports 6-month outcomes in adolescents aged 12–18 years, though it lacks a SAP comparator arm.

In the Italian non-compliant adolescent study (n=20, mean age 15.7 ± 1.9 years, mean baseline HbA1c 10.0 ± 1.7%, previously on MDI and flash CGM), TIR increased from 27.1% ± 13.7 at baseline to 60.4% ± 13.3 at 6 months (p<0.001) after initiation of Tandem Control-IQ. HbA1c improved from 10.0 ± 1.7% to 7.0 ± 0.7% at 6 months (p<0.001). TAR >250 mg/dL fell from 46.1% ± 23.8 to 15.5% ± 10.5 (p<0.001). No severe hypoglycemia occurred; two patients experienced moderate DKA due to infusion set occlusion (PMC11019566). In the Italian non-compliant adolescent study, TIR peaked at 68.6% ± 14.2 at 2 weeks and declined to 60.4% ± 13.3 at 6 months, a non-statistically significant worsening over time likely attributable to ongoing poor adherence, particularly missed meal boluses (PMC11019566).

The study's limitations are significant: the small sample size (n=20), absence of a control group, single-center design, and the extremely poor baseline glycemic control mean that the 33 percentage-point TIR improvement cannot be generalized to the broader adolescent T1D population. Nevertheless, the study demonstrates that even in the most challenging adolescent subgroup — those with documented non-compliance and HbA1c >8.5% — AHCL systems can achieve TIR approaching 60% at 6 months, a clinically meaningful improvement from a baseline of 27%.

#### The 1-Year Prospective Polish Study: Sustained AHCL Outcomes in Children and Adolescents

The 1-year prospective, two-center observational study from Poland (PMC9592809) enrolled 50 children and adolescents with T1D (mean age 9.9 ± 2.4 years; 48% male; mean T1D duration 3.9 ± 2.6 years) using the MiniMed 780G AHCL system. While the mean age of 9.9 years is below the 12–18 year range specified in the user's question, the study includes participants up to 16.8 years of age and provides the longest prospective follow-up data for the 780G system in a pediatric population.

In the 1-year prospective Polish study of 780G (n=50, mean age 9.9 ± 2.4 years), TIR was stable at approximately 80% throughout: 79.28% ± 8.12 at baseline, 81.16% ± 7.83 at 6 months, and 80.40% ± 8.25 at 12 months (no statistically significant changes). Auto-mode use increased from 92.32% at baseline to 97.56% at 12 months (p<0.05). Total daily insulin increased from 0.67 ± 0.21 U/kg to 0.80 ± 0.21 U/kg at 12 months (p<0.001) (PMC9592809). In the Polish 1-year study, time below 54 mg/dL and between 54–70 mg/dL was significantly reduced at 6 months (p<0.05) but returned toward baseline values at 12 months, suggesting the hypoglycemia-protective effect of AHCL may be partially attenuated over time (PMC9592809).

The study's primary limitation for the user's question is the younger mean age (9.9 years) and the exceptionally high baseline TIR (79%), which leaves little room for further improvement and means the study cannot quantify the TIR benefit of AHCL over SAP in adolescents with typical glycemic control. The absence of a SAP comparator arm is also a significant limitation.

#### The AHCL Study in Very Young Children: Extrapolation to Adolescent Populations

The retrospective single-center study from the IRCCS Giannina Gaslini Institute in Genoa, Italy (PMC12242179) evaluated AHCL systems (MiniMed 780G, n=23; Tandem Control-IQ, n=18) in 41 very young children (median age 4.41 ± 1.61 years) over 12 months. While this population is substantially younger than the 12–18 year range specified in the user's question, the study provides important mechanistic and effectiveness data that contextualizes AHCL performance across the pediatric age spectrum.

In the Gaslini Institute study of very young children (n=41, median age 4.41 ± 1.61 years, 780G n=23 and Control-IQ n=18), TIR improved from 55.50 ± 13.20% at baseline to 65.71 ± 9.14% at 12 months (+10.21%, p<0.001). HbA1c fell from 7.50 ± 1.14% to 6.59 ± 0.52% (p<0.001). The percentage of patients achieving HbA1c <7% more than doubled (36.1% to 86.2%), and those achieving TIR ≥70% increased from 8.6% to 38.1%. No severe hypoglycemia occurred (PMC12242179). The 10.21 percentage-point TIR improvement in this very young cohort is consistent with the improvements observed in older pediatric populations, suggesting that the mechanistic benefits of AHCL are age-independent, though the absolute TIR achieved (65.71%) is lower than that reported in older children and adolescents, reflecting the greater glycemic variability and unpredictability of very young children.

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### Comparative Effectiveness: AHCL vs. SAP — Synthesizing the TIR Difference

#### Quantitative Synthesis of Available Evidence

Drawing together the available evidence, the mean difference in TIR between AHCL systems and SAP therapy in adolescents with T1D over a minimum 6-month period can be estimated from multiple converging lines of evidence, though no single study provides a direct head-to-head randomized comparison of AHCL versus SAP specifically in adolescents aged 12–18 years over ≥6 months.

No published randomized controlled trial has directly compared AHCL systems to SAP therapy specifically in adolescents aged 12–18 years over a minimum 6-month period; the Cambridge 12-week RCT is the closest available evidence but has a 12-week duration and a mixed age range with adolescent-specific effect sizes not separately reported with confidence intervals (PMC6182127). The most direct evidence comes from the Cambridge RCT (PMC6182127), which demonstrated a 10.8 percentage-point TIR improvement (95% CI 8.2–13.5; p<0.0001) for closed-loop versus SAP in a mixed pediatric-adult population. The NHS England real-world study (PMC11044460) demonstrated a 13.3 percentage-point TIR improvement at 12 months in a predominantly adolescent and child population (mean age 12.3 years), though without a SAP comparator arm. The Slovenian AHCL study (PMC9437950) demonstrated a 10.04 percentage-point TIR improvement in adolescents (mean age 14.5 years) over 4 months, from a mixed conventional/first-generation HCL baseline. The Italian non-compliant adolescent study (PMC11019566) demonstrated a 33.3 percentage-point TIR improvement at 6 months in adolescents (mean age 15.7 years) from an MDI/flash CGM baseline, though the extreme baseline TIR of 27.1% makes this an outlier.

Synthesizing these data, the available evidence points to a mean TIR improvement of approximately **10–15 percentage points** with AHCL systems compared to pre-AHCL therapy in adolescents with T1D, as reflected in the Cambridge RCT (10.8 percentage points, 95% CI 8.2–13.5; p<0.0001) (PMC6182127), the NHS England 12-month real-world study (approximately 13–16 percentage points) (PMC11044460), and the Slovenian 4-month study (10.04 percentage points) (PMC9437950). This estimate is most applicable to adolescents with moderate baseline glycemic control (TIR approximately 50–70%). In adolescents with very poor baseline glycemic control — such as the non-compliant cohort in the Italian study with baseline TIR of 27.1% — improvements substantially exceeding this range have been documented, reaching 33 percentage points at 6 months (PMC11019566). Conversely, in adolescents with already-high baseline TIR (approaching 80%), ceiling effects limit further improvement, as demonstrated in the Polish cohort (PMC9592809). These estimates should be interpreted with caution given the absence of dedicated long-term RCTs comparing AHCL to SAP specifically in the 12–18 year age group.

#### Absolute TIR Achieved on AHCL in Adolescents

The absolute TIR achieved on AHCL systems in adolescents is a critical complement to the relative improvement. The ČENDA registry data (PMC10613700) — the largest population-level dataset with >12 months of HCL use — reports median TIR of 76% for 780G users and 75% for Control-IQ users in a pediatric population with mean age 12.8 ± 4.2 years. The NHS England study (PMC11044460) reports mean TIR of 62.0% (SD 12.0) at 12 months in a population with mean age 12.3 years and baseline TIR of 48.7%. The Slovenian study (PMC9437950) reports TIR of 78.26% at 4 months in adolescents with mean age 14.5 years. The Italian non-compliant adolescent study (PMC11019566) reports TIR of 60.4% at 6 months in adolescents with mean age 15.7 years and very poor baseline control. The Polish 1-year study (PMC9592809) reports TIR of 80.40% at 12 months in children with mean age 9.9 years and excellent baseline control.

These data suggest that adolescents on AHCL systems typically achieve TIR in the range of 60–78%, depending on baseline glycemic control, age, adherence, and the specific AHCL system used. The international consensus target of TIR ≥70% is achievable in the majority of adolescents on AHCL systems, with the ČENDA registry showing 74.2% of 780G users and 65.9% of Control-IQ users achieving this target (PMC10613700). Studies vary substantially in the nature of the comparator arm: some compare AHCL to standard HCL (PMC8630740), others to a mixed conventional/first-generation HCL baseline (PMC9437950), others to MDI/flash CGM (PMC11019566), and others to pre-HCL usual care without specification (PMC11044460), making cross-study comparisons of TIR improvement difficult.

#### Head-to-Head Comparison of AHCL Systems in Adolescents

The ČENDA registry (PMC10613700) provides the most robust head-to-head comparison of AHCL systems in a pediatric population with ≥12 months of use. After propensity score weighting, TIR was 76% for 780G users, 75% for AAPS users, and 75% for Control-IQ users, with a statistically significant difference between 780G and Control-IQ (p=0.02) but no significant difference between 780G and AAPS (p=0.99) (PMC10613700). The 780G achieved the lowest hypoglycemia burden (mean TBR1 2.5% vs. 2.9% for Control-IQ and 5.2% for AAPS) and the lowest Glycemia Risk Index (median GRI 27 vs. 31 for Control-IQ and 32 for AAPS; p<0.005 for 780G vs. each other group), while AAPS users achieved the lowest HbA1c (44 mmol/mol; 6.2%) but the highest hypoglycemia rates (PMC10613700).

The 6-month real-world comparison from Trieste (PMC8630740) found that AHCL (780G) achieved a median TIR increase of 14% from Manual Mode versus 7% for standard HCL (670G), with 54% of AHCL users achieving TIR >70% at 6 months versus 25% of standard HCL users (p=0.04). These data collectively suggest that while all AHCL systems improve TIR substantially over SAP, the 780G may offer a modest advantage in TIR and a more substantial advantage in hypoglycemia reduction compared to Control-IQ, while AAPS achieves the lowest HbA1c at the cost of higher hypoglycemia rates. A 1-month real-life observational study of 31 children found no significant differences in CGM-derived parameters between Control-IQ and 780G (mean TIR 70.5% vs. 70.1%), while a 1-year retrospective study by Bassi et al. found significant superiority of 780G over Control-IQ in TIR (71% vs. 68%, p=0.001), reflecting conflicting findings likely due to differences in study duration and population characteristics (PMC10613700).

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### Safety Profile and Adverse Events

#### Hypoglycemia: The Critical Safety Metric

One of the most clinically important findings across all studies is that AHCL systems improve TIR without increasing — and in many cases while reducing — time below range (TBR). This is mechanistically explained by the algorithm's ability to suspend or reduce insulin delivery when glucose is predicted to fall below target, preventing hypoglycemia before it occurs. In the Cambridge 12-week RCT (PMC6182127), time below 3.9 mmol/L was significantly reduced in the closed-loop group compared to SAP (difference −0.83 percentage points, 95% CI −1.40 to −0.16; p=0.013), and no severe hypoglycemia occurred in either group. In the NHS England study (PMC11044460), time in hypoglycaemia (≤3.9 mmol/L) decreased from 3.6% at baseline to 2.0% (SD 1.6) at 12 months (p<0.001). In the Slovenian AHCL study (PMC9437950), TBR <3.0 mmol/L did not change significantly (0.84% vs. 0.73%, p=0.577), and no severe hypoglycemia or DKA occurred. In the Italian non-compliant adolescent study (PMC11019566), no severe hypoglycemia occurred over 6 months. In the Gaslini Institute study of very young children (PMC12242179), no episodes of severe hypoglycemia occurred over 12 months.

The ČENDA registry data (PMC10613700) provide important nuance: while all three HCL systems maintained TBR within acceptable ranges, AAPS users had substantially higher hypoglycemia rates (mean TBR1 5.2% vs. 2.9% for Control-IQ and 2.5% for 780G), reflecting the greater flexibility of the DIY system and the potentially higher motivation of AAPS users to achieve the lowest possible HbA1c at the cost of increased hypoglycemia risk. The 780G system's self-adjusting algorithm appears to be the primary driver of its superior hypoglycemia profile. In the Polish 1-year study, time below 54 mg/dL and between 54–70 mg/dL was significantly reduced at 6 months (p<0.05) but returned toward baseline values at 12 months, suggesting the hypoglycemia-protective effect of AHCL may be partially attenuated over time as the algorithm adapts to higher insulin requirements (PMC9592809).

#### Diabetic Ketoacidosis: A Persistent Risk with Insulin Pump Therapy

DKA rates in the ČENDA registry were 3.3 events per 100 patient-years for 780G users, 2.0 for Control-IQ users, and 0.0 for AAPS users, with no statistically significant differences between groups. In the Gaslini Institute study, 3 of 41 patients (7.3%) experienced DKA due to infusion set occlusion over 12 months. In the Italian non-compliant adolescent study, 2 of 20 patients (10%) experienced moderate DKA attributed to infusion set occlusion over 6 months (PMC10613700, PMC12242179, PMC11019566). In the Cambridge 12-week RCT (PMC6182127), one DKA event occurred in the closed-loop group due to infusion set failure, deemed unrelated to the algorithm. The NHS England study (PMC11044460) did not report DKA rates separately.

These data suggest that DKA risk with AHCL systems is primarily driven by infusion set failure rather than algorithmic errors, and that the DKA rate is comparable to or lower than that observed with conventional insulin pump therapy. Education of patients and families on infusion set management and early recognition of occlusion signals is essential, particularly in younger patients and those with higher insulin requirements (PMC12242179).

#### Skin Reactions and Device-Related Adverse Events

Skin reactions to CGM sensors and insulin pump infusion sets represent an emerging safety concern with AHCL systems, particularly as longer-lasting devices increase cumulative skin contact time. In the Gaslini Institute study (PMC12242179), one patient required switching AHCL systems due to a significant skin reaction to the adhesive device over 12 months. The NHS England study (PMC11044460) noted that non-completion reasons included cessation of HCL due to skin allergies, though the specific rate was not reported. The ČENDA registry (PMC10613700) did not report skin reaction rates. These data suggest that skin reactions are a clinically relevant but relatively uncommon reason for AHCL discontinuation, and that future studies should systematically collect and report skin reaction data.

#### Nausea and Side Effects with Dual-Hormone Systems

The Danish dual-hormone crossover trial (PMC9899880) provides important safety data for the specific context of glucagon-augmented closed-loop systems in adolescents. Three participants (27%) reported a clinically significant measure of nausea during the dual-hormone arm compared with none in the single-hormone arm (PMC9899880), representing a meaningful safety signal for glucagon-based systems. All reported side effects were mild and self-limiting, but nausea remains a significant limitation of dual-hormone closed-loop use and a major consideration for future development of these systems in adolescents.

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### Unresolved Controversies and Disagreements

#### The Magnitude of TIR Improvement: RCT vs. Real-World Estimates

A significant controversy in the literature concerns the magnitude of TIR improvement attributable to AHCL systems over SAP therapy, with estimates varying substantially across study designs and populations. The Cambridge 12-week RCT (PMC6182127) reported a 10.8 percentage-point improvement (95% CI 8.2–13.5), while the NHS England real-world study (PMC11044460) reported a 13.3 percentage-point improvement at 12 months. The Slovenian study (PMC9437950) reported a 10.04 percentage-point improvement at 4 months. However, the Italian non-compliant adolescent study (PMC11019566) reported a 33.3 percentage-point improvement at 6 months, and the Gaslini Institute study of very young children (PMC12242179) reported a 10.21 percentage-point improvement at 12 months.

The discrepancy between these estimates is primarily explained by differences in baseline TIR: populations with lower baseline TIR (e.g., non-compliant adolescents with TIR of 27.1%) show larger absolute improvements, while populations with higher baseline TIR (e.g., the Polish cohort with TIR of 79.28%) show minimal further improvement. This baseline-dependence of TIR improvement is a fundamental statistical and clinical reality that complicates cross-study comparisons and means that a single "mean difference" estimate is inherently population-specific. The NHS England study documented a linear relationship between baseline HbA1c and HbA1c reduction at 12 months (r=0.60; p<0.001; equation: Change in HbA1c at 12 months = −0.50 × Pre-HCL HbA1c + 24.3) (PMC11044460) confirms this baseline-dependence and suggests that adolescents with higher baseline HbA1c derive greater absolute benefit from AHCL systems.

#### AHCL vs. Standard HCL: Is the Incremental Benefit Clinically Meaningful?

A second controversy concerns whether the incremental benefit of AHCL over standard HCL (670G) justifies the additional cost and complexity. The Trieste study (PMC8630740) found a statistically significant difference in HbA1c at 6 months (7.1% vs. 7.7%, p=0.02) and in the proportion achieving TIR >70% (54% vs. 25%, p=0.04), suggesting clinically meaningful superiority of AHCL. However, the median TIR increase from Manual Mode was not statistically significantly different between AHCL and standard HCL (14% vs. 7%, p=0.20), and the ČENDA registry (PMC10613700) found a statistically significant but numerically modest difference in TIR between 780G and Control-IQ after propensity score weighting (76% vs. 75%, p=0.02). The 1-month real-life observational study of 31 children cited in the ČENDA paper found no significant differences in CGM-derived parameters between Control-IQ and 780G (mean TIR 70.5% vs. 70.1%), while the 1-year retrospective study by Bassi et al. (cited in PMC10613700) found significant superiority of 780G over Control-IQ in TIR (71% vs. 68%, p=0.001). These conflicting findings likely reflect differences in study duration, population characteristics, and the degree to which participants optimized device settings.

#### The Role of Baseline Glycemic Control in Predicting AHCL Benefit

A third controversy concerns whether AHCL systems are more beneficial for adolescents with poor baseline glycemic control or those with already-good control. The Trieste study (PMC8630740) found that individuals with HbA1c >8% at baseline derived the greatest benefit from AHCL (ΔHbA1c −1.4% vs. −0.3% for standard HCL, p=0.04), while those with HbA1c <7% at baseline actually showed a slight worsening of HbA1c with both AHCL and standard HCL. In the Trieste study, adolescents with HbA1c <7% at baseline showed a paradoxical slight worsening of HbA1c with AHCL (from 6.7% to 7.3%, p=0.04), suggesting that AHCL systems may not be universally beneficial for already well-controlled patients because the algorithm targets 100–120 mg/dL, which may be higher than the target maintained by highly motivated patients (PMC8630740). The NHS England study (PMC11044460) similarly found that patients with initially optimal HbA1c values showed a slight decrease in TIR over the 12-month period, while those with higher baseline HbA1c showed the greatest improvements. These findings suggest that AHCL systems may not be universally beneficial for all adolescents and that individualized target setting is important.

#### Differential Hypoglycemia Profiles Across AHCL Systems

The ČENDA registry data (PMC10613700) reveal an important clinical trade-off between TIR and hypoglycemia risk across AHCL platforms. After propensity score weighting, the 780G achieved a statistically significant TIR advantage over Control-IQ (76% vs. 75%, p=0.02) while simultaneously achieving lower hypoglycemia rates (mean TBR1 2.5% vs. 2.9%) and the lowest Glycemia Risk Index of all three systems studied (median GRI 27 vs. 31 for Control-IQ). These data suggest that for adolescents with hypoglycemia unawareness or recurrent hypoglycemia, the 780G's algorithmic profile may offer a clinically meaningful safety advantage, though the absolute TIR difference between systems is modest and the cross-sectional observational design precludes causal inference (PMC10613700).

#### Dual-Hormone vs. Single-Hormone Closed-Loop: Unresolved in Adolescents

The Danish crossover trial (PMC9899880) raises an important unresolved controversy: whether adding glucagon to a closed-loop system improves outcomes in adolescents. The trial was stopped early after an interim analysis found the dual-hormone (DH) configuration to be inferior to the single-hormone (SH) configuration for TIR and TAR, and non-superior for TBR. Over the entire 26-hour period, TIRSG was 68.4% for DH versus 75.7% for SH (p=0.09), and during the overnight period, SH achieved significantly higher TIRSG (96.5% vs. 73.0%, p=0.02) and lower TARSG (0% vs. 27.0%, p=0.02). These findings contradict the meta-analytic evidence suggesting DH superiority over SH for TIR and TBR, and the authors attribute the discrepancy to the use of generic rather than individualized glucagon algorithm parameters, technical issues with glucagon pump occlusions, and pressure-induced sensor attenuation. Whether improved DH algorithms with stable glucagon formulations would demonstrate superiority in adolescents remains an open question.

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### Limitations of the Evidence Base

The evidence base for AHCL versus SAP therapy in adolescents aged 12–18 years over a minimum 6-month period has several important methodological limitations that must be acknowledged when interpreting the available data.

**Absence of direct head-to-head RCTs in adolescents over ≥6 months.** No published randomized controlled trial has directly compared AHCL systems to SAP therapy specifically in adolescents aged 12–18 years over a minimum 6-month period. The Cambridge 12-week RCT (PMC6182127) is the closest available evidence but has a 12-week duration and a mixed age range (6 years and older), with adolescent-specific effect sizes not separately reported with confidence intervals. This is the single most important gap in the evidence base.

**Predominance of single-arm, before-after study designs.** The majority of studies reporting 6-month or longer outcomes in adolescents use single-arm, before-after designs without SAP comparator arms (PMC11044460, PMC9437950, PMC11019566, PMC9592809, PMC12242179). These designs are susceptible to regression to the mean and observer bias. The NHS England study (PMC11044460) explicitly addressed regression to the mean using the Oldham method and found no evidence that it was the primary driver of HbA1c change, and the consistency of glycaemic improvements at 3, 6, and 12 months in that study was interpreted by the authors as evidence against a Hawthorne effect. Nonetheless, the absence of concurrent SAP control arms in most studies means that the contribution of increased clinical engagement and monitoring to observed improvements cannot be fully excluded.

**Small sample sizes in most studies.** The majority of studies in this review enrolled fewer than 50 participants (PMC8630740, n=44; PMC9437950, n=24; PMC11019566, n=20; PMC12242179, n=41; PMC9592809, n=50), limiting statistical power for subgroup analyses and increasing the risk of type I and type II errors. Only the ČENDA registry (PMC10613700, n=512) and the NHS England study (PMC11044460, n=251) provide adequately powered population-level estimates.

**Heterogeneity of comparator arms.** Studies vary substantially in the nature of the comparator arm: some compare AHCL to standard HCL (PMC8630740), others to a mixed conventional/first-generation HCL baseline (PMC9437950), others to MDI/flash CGM (PMC11019566), and others to pre-HCL usual care without specification (PMC11044460). This heterogeneity makes cross-study comparisons of TIR improvement difficult and means that the "SAP comparator" is not consistently defined across the literature.

**Short follow-up duration in many studies.** Several studies report outcomes over 4 months (PMC9437950) or 12 weeks (PMC6182127), falling short of the 6-month minimum specified in the user's question. The durability of TIR improvements beyond 6 months is documented in the NHS England study (PMC11044460) and the Polish 1-year study (PMC9592809), but the evidence base for sustained ≥12-month outcomes in adolescents specifically is limited.

**Single-center designs and selection bias.** Most studies were conducted at single academic tertiary centers with highly motivated, technology-experienced patient populations and structured onboarding programs (PMC8630740, PMC9437950, PMC11019566, PMC12242179, PMC9592809). These settings may not reflect outcomes achievable in routine clinical practice, and the high baseline sensor use (>90% in most studies) and structured therapeutic contracts (PMC8630740) may inflate TIR outcomes compared to less-supported real-world settings. The Trieste study authors explicitly noted that the single high-standard academic center setting with highly motivated families who signed a therapeutic contract may limit generalizability to broader clinical contexts (PMC8630740).

**Conflicts of interest.** The Slovenian AHCL study has authors who served on advisory boards for Medtronic and received honoraria from Medtronic, the manufacturer of the study device. The Polish study has authors who received speaker honoraria from Medtronic (PMC9437950, PMC9592809). These relationships do not invalidate the findings but warrant consideration when interpreting results.

**Lack of adolescent-specific subgroup analyses.** Studies that enroll mixed pediatric-adult populations (PMC6182127) or broad pediatric age ranges (PMC11044460, PMC10613700) frequently do not report adolescent-specific (12–18 years) effect sizes with confidence intervals, making it difficult to isolate the TIR benefit specifically in this age group. The ČENDA registry reports age-stratified TIR results (0–5.99, 6–11.99, 12–18.99 years), but the primary TIR data are reported as medians without confidence intervals for the adolescent subgroup specifically (PMC10613700).

**Generalizability limitations.** The predominantly white European and North American populations in most studies limit generalizability to more ethnically diverse populations. Qualitative data from the South African IPA study (PMC11524997) highlights that access to AHCL technology is highly socioeconomically stratified, and outcomes in resource-limited settings may differ substantially from those reported in high-income healthcare systems.

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### Special Populations: Adolescents with Suboptimal Glycemic Control

The evidence consistently demonstrates that adolescents with suboptimal baseline glycemic control derive the greatest absolute TIR benefit from AHCL systems. The Italian non-compliant adolescent study (PMC11019566) — enrolling adolescents with mean baseline HbA1c of 10.0 ± 1.7% and TIR of 27.1% — demonstrated a 33.3 percentage-point TIR improvement at 6 months and an HbA1c reduction of 3.0 percentage points. The Trieste study (PMC8630740) found that adolescents with HbA1c >8% at baseline showed a ΔHbA1c of −1.4% with AHCL versus −0.3% with standard HCL (p=0.04). The NHS England study documented a linear relationship between baseline HbA1c and HbA1c reduction at 12 months (r=0.60; p<0.001; equation: Change in HbA1c at 12 months = −0.50 × Pre-HCL HbA1c + 24.3) (PMC11044460), confirming that higher baseline HbA1c predicts greater benefit.

These findings have important clinical implications: AHCL systems should be prioritized for adolescents with suboptimal glycemic control, where the potential for TIR improvement is greatest. The qualitative evidence from the South African IPA study (PMC11524997) and the Slovenian AHCL study (PMC9437950) further suggests that the psychosocial benefits of AHCL — reduced fear of hypoglycemia, improved sleep quality, reduced diabetes-related emotional distress — are also substantial in adolescents, potentially improving adherence and long-term outcomes beyond what glycemic metrics alone capture. The Slovenian study documented statistically significant reductions in C-HFS total fear-of-hypoglycemia score and in PAID diabetes-related emotional distress over 4 months of AHCL use (PMC9437950), while the NHS England study documented significant improvements in fear of hypoglycemia (total HFS score: 64.9 to 57.7 at 12 months, p<0.001) and sleep impairment (PROMIS SRI T-score: 56.6 to 53.1, p<0.001) over 12 months (PMC11044460).

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### Conclusions and Future Directions

#### What the Evidence Supports

The available evidence, while heterogeneous in design and population, consistently supports the conclusion that AHCL systems improve TIR substantially compared to SAP therapy in adolescents with type 1 diabetes. The best estimate for the mean TIR improvement with AHCL systems in adolescents over a minimum 6-month period is approximately **10–15 percentage points** in populations with moderate baseline glycemic control, as reflected in the Cambridge 12-week RCT (10.8 percentage points, 95% CI 8.2–13.5; p<0.0001) (PMC6182127), the NHS England 12-month real-world study (approximately 13–16 percentage points) (PMC11044460), and the Slovenian 4-month study (10.04 percentage points) (PMC9437950). In adolescents with very poor baseline glycemic control — such as the non-compliant cohort in the Italian study with baseline TIR of 27.1% — improvements substantially exceeding this range have been documented, reaching 33 percentage points at 6 months (PMC11019566). Across the studies reviewed, adolescents on AHCL systems typically achieve absolute TIR in the range of 60–78%, with the ČENDA registry reporting median TIR of 75–76% for 780G and Control-IQ users respectively in a pediatric population with mean age 12.8 years after ≥12 months of HCL use (PMC10613700), and the NHS England study reporting mean TIR of 62.0% at 12 months in a population with mean age 12.3 years (PMC11044460).

The evidence also supports the conclusion that AHCL systems improve TIR without increasing hypoglycemia risk — and in many cases while reducing time below range — across all adolescent subgroups studied. HbA1c reductions of 0.36–3.0 percentage points are consistently documented, with the magnitude of reduction inversely correlated with baseline HbA1c. Psychosocial benefits — including reduced fear of hypoglycemia, improved sleep quality, and reduced diabetes-related emotional distress — are documented in multiple studies and represent clinically meaningful outcomes beyond glycemic metrics (PMC9437950, PMC11044460, PMC11524997). The ČENDA registry data indicate that the 780G achieves a statistically significant, if numerically modest, TIR advantage over Control-IQ (76% vs. 75%, p=0.02) alongside the lowest hypoglycemia burden of all systems studied (mean TBR1 2.5% vs. 2.9% for Control-IQ), suggesting it may be particularly well-suited for adolescents at elevated hypoglycemia risk, though the observational design limits causal conclusions (PMC10613700).

#### What the Evidence Does NOT Support

The evidence does not support the conclusion that AHCL systems are universally superior to SAP therapy for all adolescents. Adolescents with already-excellent glycemic control (HbA1c <7%, TIR >70%) may not derive meaningful TIR benefit from AHCL systems and may even experience a slight worsening of HbA1c due to the algorithm's fixed glycemic target being higher than their manually maintained target (PMC8630740). The evidence does not support the superiority of dual-hormone (insulin + glucagon) closed-loop systems over single-hormone systems in adolescents; the available RCT evidence suggests that single-hormone systems perform at least as well as dual-hormone systems overall, and are superior overnight and around exercise (PMC9899880). The evidence does not support the conclusion that all AHCL systems are equivalent: meaningful differences in hypoglycemia rates, HbA1c, and GRI exist between 780G, Control-IQ, and AAPS, with important clinical implications for device selection (PMC10613700).

#### Future Research Directions

**1. Dedicated RCTs comparing AHCL to SAP in adolescents aged 12–18 years over ≥6 months.** The most critical gap in the evidence base is the absence of a randomized controlled trial directly comparing AHCL systems to SAP therapy specifically in adolescents over a minimum 6-month period. Such a trial should be adequately powered for adolescent-specific subgroup analyses, stratified by baseline HbA1c, and should report TIR, HbA1c, hypoglycemia rates, and patient-reported outcomes as co-primary endpoints.

**2. Long-term (≥2 year) follow-up studies in adolescents.** The durability of TIR improvements beyond 12 months in adolescents is poorly characterized. Longitudinal studies tracking glycemic outcomes, device adherence, and psychosocial outcomes through the adolescent transition to young adulthood are needed to understand whether AHCL benefits are sustained as adolescents gain independence from parental supervision.

**3. Head-to-head RCTs comparing 780G and Control-IQ in adolescents.** The ČENDA registry data (PMC10613700) suggest meaningful differences between these systems in TIR, hypoglycemia rates, and GRI, but the cross-sectional observational design precludes causal inference. A randomized crossover trial comparing these systems in adolescents would provide definitive comparative effectiveness data.

**4. Studies in ethnically diverse and socioeconomically disadvantaged adolescent populations.** The current evidence base is predominantly derived from white European populations in high-income healthcare settings. Studies in more diverse populations — including those with limited access to structured diabetes education, technology support, and healthcare resources — are essential to understand the generalizability of AHCL benefits and to identify barriers to equitable access.

**5. Investigation of optimal AHCL settings for adolescents.** The Trieste study (PMC8630740) identified younger age, higher auto-correction rate, and lower CHO entered as independent predictors of TIR >70% in AHCL users. Systematic investigation of optimal glycemic target settings, active insulin time, and algorithm parameters for adolescents — who have distinct pharmacokinetic profiles due to puberty-associated insulin resistance — is needed to maximize TIR outcomes in this population.

**6. Studies addressing the transition from adolescence to young adulthood.** The transition from pediatric to adult diabetes care is associated with deterioration in glycemic control and increased risk of complications. Studies examining whether AHCL systems mitigate this transition-related glycemic deterioration, and what support structures are needed to maintain AHCL adherence during this period, represent an important research priority.

**7. Pharmacoeconomic analyses of AHCL versus SAP in adolescents.** The cost-effectiveness of AHCL systems relative to SAP therapy in adolescents has not been systematically evaluated. Given the substantial upfront cost of AHCL systems and the potential for long-term complication prevention, formal health economic analyses are needed to inform reimbursement decisions across healthcare systems.

**8. Investigation of the role of carbohydrate counting and meal announcement in AHCL outcomes.** The Italian non-compliant adolescent study (PMC11019566) demonstrated that AHCL systems can achieve meaningful TIR improvements even without carbohydrate counting, while the Trieste study (PMC8630740) found that lower CHO entered predicted TIR >70% in AHCL users. The optimal approach to meal management with AHCL systems in adolescents — who frequently skip or underestimate meal boluses — requires further investigation.

**9. Standardized reporting of adolescent-specific outcomes in mixed-age studies.** Future studies enrolling mixed pediatric-adult populations should pre-specify and report adolescent-specific (12–18 years) effect sizes with confidence intervals for TIR and other primary outcomes, enabling more precise meta-analytic synthesis of adolescent-specific evidence.

**10. Investigation of dual-hormone closed-loop systems with stable glucagon formulations in adolescents.** The Danish crossover trial (PMC9899880) found that the dual-hormone configuration was inferior to single-hormone for TIR in adolescents, but attributed this to technical limitations of the current system rather than to glucagon per se. Future trials using stable glucagon formulations (dasiglucagon, Baqsimi) and individualized glucagon algorithm parameters should re-examine whether dual-hormone systems can improve outcomes in adolescents, particularly around exercise.

In summary, the evidence strongly supports the clinical adoption of AHCL systems over SAP therapy in adolescents with type 1 diabetes, with a mean TIR improvement of approximately 10–15 percentage points in populations with moderate baseline glycemic control, accompanied by HbA1c reductions, reduced hypoglycemia, and meaningful psychosocial benefits. The magnitude of benefit is greatest in adolescents with suboptimal baseline glycemic control, and the choice of specific AHCL system should be individualized based on the patient's hypoglycemia risk, adherence patterns, and glycemic targets. The evidence base, while growing rapidly, remains limited by the absence of dedicated long-term RCTs in adolescents and the predominance of single-arm, single-center studies in predominantly white European populations. Addressing these gaps through well-designed, adequately powered, and ethnically diverse clinical trials is the most important priority for the field.

## References

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