bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–07–05
fourteen papers selected by
Mott Given
  1. Continuous Glucose Monitoring and Hypoglycemia Detection while Driving: Results from a Cross-Sectional Survey.
  2. Continuous Glucose Monitoring and Personalized Nutrition in Type 2 Diabetes - A Scoping Review.
  3. Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.
  4. The Upfront Effectiveness of a 6-Week Continuous Glucose Monitoring Intervention for Non-Insulin-Using Individuals With Type 2 Diabetes Is No Longer Detectable at 6-12 Months: An Observational Follow-Up of a Randomized Trial Cohort.
  5. Social Determinants of Health and Continuous Glucose Monitoring Metrics in Type 1 or Type 2 Diabetes.
  6. Continuous glucose monitoring-derived time in range is associated with changes in arterial stiffness in type 2 diabetes.
  7. Prevalence, duration, and clinical implications of continuous glucose monitor measurement limit capping in type 1 diabetes.
  8. Continuous Glucose Monitoring Metrics for Predicting Adverse Neonatal Outcomes in Individuals Undergoing Gestational Diabetes Screening.
  9. Continuous Glucose Monitoring Metrics and Perinatal Outcomes in Pregnant Women with Type 2 Diabetes.
  10. An Integrated Visualization of Continuous Glucose and Insulin Pump Data for Patients.
  11. Exercise or Fasting in Individuals With Type 2 Diabetes Receiving Once-Weekly Basal Insulin Icodec.
  12. High-intensity interval training and continuous glucose monitoring-derived glycemic outcomes in adults with type 2 diabetes: a systematic review and meta-analysis.
  13. Tirzepatide Is Associated With Improved Metabolic Outcomes in People With Type 1 Diabetes and Overweight or Obesity: A Retrospective Cohort Study.
  14. Continuing automated insulin delivery systems during hospitalisation with type 1 diabetes: A thematic literature review.
  1. Diabetes Technol Ther. 2026 Jul;28(7): 746-753
    Continuous Glucose Monitoring and Hypoglycemia Detection while Driving: Results from a Cross-Sectional Survey.
    Steven L Trawley, Sybil A McAuley, Amanda N Stephens.
      Hypoglycemia is a major safety concern for drivers with diabetes. Continuous glucose monitoring (CGM) improves detection of low glucose levels while driving, yet evidence regarding real-world use remains limited. We conducted a national survey of 1209 Australian drivers with diabetes treated with glucose-lowering medication (mean age 55, standard deviation15 years; 47% using CGM; 39% with type 1 diabetes). Twenty-eight percent of participants reported hypoglycemia while driving in the past 12 months. CGM use was associated with higher odds of reporting hypoglycemia while driving (adjusted odds ratio 3.61 [95% confidence interval: 2.19-5.68]), likely reflecting greater detection. Two-thirds of CGM users relied on CGM vibration or audio alerts, and fewer than one in five adjusted alert thresholds for driving. Difficulty using CGM while driving (50%) and legal uncertainty (43%) were the most frequent barriers. Drivers expressed strong interest in safer in-car CGM integration and clearer legal guidance to support glucose monitoring while driving.
    Keywords:  continuous glucose monitoring (CGM); diabetes technology; driving safety; human factors; hypoglycemia awareness; in-vehicle integration
    DOI:  https://doi.org/10.1177/15209156251408410
  2. Stud Health Technol Inform. 2026 Jun 29. 338 281-285
    Continuous Glucose Monitoring and Personalized Nutrition in Type 2 Diabetes - A Scoping Review.
    Bushra Hoque, Asmaa Al-Mesaifri, Sara Suleiman, Zain Ul Abideen Tariq, Mowafa Househ.
      Continuous Glucose Monitoring (CGM) is increasingly applied to personalized nutrition in Type 2 Diabetes (T2D), yet evidence is scattered. This scoping review mapped CGM-based nutrition interventions, classified models, summarized outcomes, and identified gaps. Following JBI and PRISMA-ScR guidelines, five databases and Google Scholar were searched (2020-2025) for studies of adults with T2D using real-time or intermittently scanned CGM to guide diet. Forty-five studies were included, mostly randomized trials, with additional pilot and observational designs. Interventions included CGM-guided nutrition, AI-enabled prediction, CGM-AI hybrid/digital-twin models, and telehealth coaching. Measured outcomes focused on HbA1c, Time in Range, and weight, while behavioral, cardiovascular, and microbiome measures were rarely assessed. Overall, CGM-enabled nutrition shows promise but remains methodologically inconsistent, with gaps in participant reporting, outcome diversity, and AI-driven approaches. Larger, long-term studies are needed to advance precision nutrition in diabetes care using continuous glucose monitoring.
    Keywords:  Continuous glucose monitoring; diabetes; dietary interventions; personalized nutrition
    DOI:  https://doi.org/10.3233/SHTI260847
  3. Stat Med. 2026 Jul;45(15-17): e70646
    Beyond Fixed Thresholds: Optimizing Summaries of Wearable Device Data via Piecewise Linearization of Quantile Functions.
    Junyoung Park, Neo Kok, Irina Gaynanova.
      Wearable devices, such as actigraphy monitors and continuous glucose monitors (CGMs), capture high-frequency data, which are often summarized by the percentages of time spent within fixed thresholds. For example, actigraphy data are categorized into sedentary, light, and moderate-to-vigorous activity, while CGM data are divided into hypoglycemia, normoglycemia, and hyperglycemia based on a standard glucose range of 70-180 mg/dL. Although scientific and clinical guidelines inform the choice of thresholds, it remains unclear whether this choice is optimal and whether the same thresholds should be applied across different populations. In this work, we define threshold optimality with loss functions that quantify discrepancies between the full empirical distributions of wearable device measurements and their discretizations based on specific thresholds. We introduce two loss functions: one that aims to accurately reconstruct the original distributions and another that preserves the pairwise sample distances. Using the Wasserstein distance as the base measure, we reformulate the loss minimization as optimal piecewise linearization of quantile functions. We solve this optimization via stepwise algorithms and differential evolution. We also formulate semi-supervised approaches where some thresholds are predefined based on scientific rationale. Applications to CGM datasets from diverse populations, including individuals with type 1 diabetes, type 2 diabetes, and normal glycemic control, demonstrate that data-driven thresholds vary by population, improve discriminative power, and yield stronger associations with clinical variables over fixed thresholds.
    Keywords:  Wasserstein distance; amalgamation; continuous glucose monitoring (CGM); histogram; time‐in‐range (TIR)
    DOI:  https://doi.org/10.1002/sim.70646
  4. Diabetes Obes Metab. 2026 Jun 30.
    The Upfront Effectiveness of a 6-Week Continuous Glucose Monitoring Intervention for Non-Insulin-Using Individuals With Type 2 Diabetes Is No Longer Detectable at 6-12 Months: An Observational Follow-Up of a Randomized Trial Cohort.
    Jiawei Ryan Zhang, Roseanne O Yeung, Donna P Manca, Pratima Singh, Inga Olu-Jordan, Tawnya Perry, Gulelala Rahim, Evan M Hagen, Darren Lau.
      
    Keywords:  continuous glucose monitoring (CGM); glycaemic control; observational study; type 2 diabetes
    DOI:  https://doi.org/10.1111/dom.71048
  5. JAMA Netw Open. 2026 Jul 01. 9(7): e2621290
    Social Determinants of Health and Continuous Glucose Monitoring Metrics in Type 1 or Type 2 Diabetes.
    Walter T Williamson, Neo Kok, Joyce M Lee, Jenna Wiens, Irina Gaynanova.
       Importance: Race, ethnicity, and social determinants of health (SDOH) contribute to disparities in diabetes outcomes, particularly hemoglobin A1c (HbA1c). Although continuous glucose monitoring (CGM) improves glycemic management, it remains unclear whether associations persist between SDOH and CGM metrics, as prior research has focused solely on HbA1c.
    Objective: To examine the associations of race, ethnicity, and SDOH with glycemic metrics among patients with type 1 or type 2 diabetes who use CGMs.
    Design, Settings, and Participants: This retrospective cross-sectional study evaluated CGM profiles paired with demographic data from individuals receiving outpatient care at a single-center academic health system between October 1, 2017, and February 28, 2025. The cohort included pediatric (aged <18 years) and adult (aged ≥18 years) patients with type 1 or type 2 diabetes who met CGM data sufficiency criteria.
    Exposures: Race and ethnicity category, individual-level SDOH (eg, insurance type), and neighborhood-level socioeconomic status.
    Main Outcomes and Measures: Glycemic outcomes included HbA1c, mean glucose, time in range, time above range, glycemic risk index, coefficient of variation, and extended hypoglycemic episodes. Inverse probability weighting and mixed-effects models were used to examine associations between exposures and outcomes.
    Results: The study included 1743 participants with 3296 CGM profiles (mean [SD] age, 38.8 [20.8] years; 926 female [53.1%]; 86 identifying as Black [4.9%], 56 as Hispanic [3.2%], 1508 as White [86.5%], and 93 as other [5.3%] race and ethnicity). Black race and public health insurance were associated with higher HbA1c (estimate, 0.55%; 95% CI, 0.27%-0.82%) and mean glucose (estimate, 17.88 mg/dL; 95% CI, 3.69-32.07 mg/dL). Public insurance was also associated with higher time in range (estimate, -3.56%; 95% CI, -5.45% to -1.66%), time above range (estimate, 3.49%; 95% CI, 1.53%-5.46%), and glycemic risk index (estimate, 4.50; 95% CI, 2.13-6.87). Socioeconomic disadvantage was associated with an increase in coefficient of variation (estimate, 3.26; 95% CI, 0.81-5.70). Associations were most pronounced among children experiencing more socioeconomic disadvantage and Black children across metrics. These associations persisted after adjusting for insulin pump use.
    Conclusions and Relevance: This cross-sectional study of adult and pediatric CGM users with type 1 or type 2 diabetes found that CGM and insulin pump use alone did not eliminate associations between SDOH and glycemic outcomes. These findings highlight the need for interventions beyond technology, such as diabetes education and behavioral support, to promote equity in diabetes care.
    DOI:  https://doi.org/10.1001/jamanetworkopen.2026.21290
  6. J Clin Endocrinol Metab. 2026 Jun 30. pii: dgag261. [Epub ahead of print]
    Continuous glucose monitoring-derived time in range is associated with changes in arterial stiffness in type 2 diabetes.
    Fumiya Sato, Tomoya Mita, Naoto Katakami, Yosuke Okada, Hidenori Yoshii, Takeshi Osonoi, Keiko Nishida, Toshihiko Shiraiwa, Ryota Ishii, Masahiko Gosho, Iichiro Shimomura, Hirotaka Watada.
       BACKGROUND: Current guidelines recommend continuous glucose monitoring (CGM) to complement HbA1c in glycemic assessment. While cross-sectional studies have reported associations between CGM-derived metrics and arterial stiffness in type 2 diabetes (T2D), longitudinal evidence remains limited.
    OBJECTIVE: This study aimed to investigate the longitudinal associations of CGM metrics, particularly time in range (TIR) and coefficient of variation (CV), with changes in brachial-ankle pulse wave velocity (baPWV).
    METHODS: This exploratory study analyzed data collected over 260 weeks from an ongoing prospective, multicenter, observational cohort. A total of 348 participants with type 2 diabetes and no history of symptomatic cardiovascular disease underwent baPWV measurements at baseline, 104 weeks, and/or 260 weeks. Participants were divided into two groups based on the median values of CGM-derived metrics and HbA1c at baseline, and the associations between each baseline value and longitudinal changes in baPWV were evaluated using mixed-effects models for repeated measures, adjusting for conventional atherosclerotic risk factors.
    RESULTS: The median change in baPWV from baseline was 60.1 cm/s (95% CI: 34.6 to 85.6) at 104 weeks and 130.3 cm/s (95% CI: 98.6 to 162.1) at 260 weeks (p < 0.001). The change over time in baPWV differed between the higher and lower TIR groups, with a significant interaction between group and time (p = 0.013) in the multivariable-adjusted model. This interaction remained significant even after further adjustment for HbA1c (p = 0.013). In contrast, baseline CV, other CGM-derived metrics, and HbA1c were not associated with longitudinal changes in baPWV.
    CONCLUSIONS: TIR was significantly associated with longitudinal changes in arterial stiffness in participants with type 2 diabetes, independent of HbA1c.
    Keywords:  Arterial stiffness; Continuous glucose monitoring; Glucose variability; brachial-ankle pulse wave velocity
    DOI:  https://doi.org/10.1210/clinem/dgag261
  7. Diabet Med. 2026 Jul 02. e70412
    Prevalence, duration, and clinical implications of continuous glucose monitor measurement limit capping in type 1 diabetes.
    John F Mulley.
       AIMS: CGM devices report glucose only within fixed limits (typically 40-400 mg/dL; 2.2-22.2 mmol/L), truncating extreme values to a boundary ('capping'). We characterised prevalence, duration, and consequences of capping in type 1 diabetes trial data.
    METHODS: We analysed 46,990,617 CGM readings from 948 participants across four publicly available clinical trial datasets (Dexcom G4 Platinum or G6 sensors). Capping prevalence, run duration, and associations with age, HbA1c, and sex were characterised across all datasets. In the 77 participants of the Replace-BG trial, CGM-plus-blood glucose monitor (BGM) arm, CGM-derived metrics were compared with contemporaneous BGM measurements across 1162 non-overlapping 14-day windows.
    RESULTS: Between 93.5% and 100% of participants had at least one capped reading, and capped values comprised 0.47-0.98% of all readings. In the three datasets for which duration could be calculated, over 70% of upper-cap runs exceeded 15 min and over one third exceeded 60 min. Upper-limit capping was inversely associated with age (Spearman ρ -0.20 to -0.47, p ≤ 0.002) in three of the datasets, and positively associated with baseline HbA1c (ρ 0.39-0.62, p < 0.001) in all four datasets. A within-participant analysis showed that capping burden did not predict CGM-BGM divergence in any summary metric (all p > 0.2), and a systematic CGM-BGM offset in mean glucose and time in range (TIR) reflected the physiological lag between blood and interstitial fluid rather than capping artefact.
    CONCLUSIONS: Sensor limit capping is near-universal in type 1 diabetes, produces sustained periods of right-censored glucose data disproportionately affecting younger participants, and does not substantially distort standard summary metrics at the population level. Clinicians and trialists should be aware that CGM data can confirm extreme glucose events but cannot quantify their severity.
    Keywords:  continuous glucose monitoring; hyperglycaemia; sensor measurement limits; time in range; type 1 diabetes
    DOI:  https://doi.org/10.1111/dme.70412
  8. J Diabetes Sci Technol. 2026 Jul 01. 19322968261461603
    Continuous Glucose Monitoring Metrics for Predicting Adverse Neonatal Outcomes in Individuals Undergoing Gestational Diabetes Screening.
    Caleb Griffiths, Rafael Bravo Santos, Sarah A Wernimont, Julie Anderson, Megan Kristan, Erika S Helgeson, Lisa S Chow, Michal Fishel Bartal.
       OBJECTIVES: This study evaluates whether continuous glucose monitoring (CGM) metrics predict adverse neonatal outcomes among individuals undergoing gestational diabetes screening. Building on findings by Fishel Bartal et al, who reported an association between ≥10% time above 140 mg/dL and a composite neonatal outcome, this analysis examines 13 additional CGM-derived measures reflecting glycemic variability (GV) and glycemic extremes.
    METHODS: Eighty-four pregnant individuals wore CGM devices for 10 days following a 1-hour 50 g glucose challenge test. Generalized estimating equation logistic regression models assessed associations between CGM metrics and a composite neonatal outcome consisting of large-for-gestational-age birth, need for intravenous glucose treatment, or shoulder dystocia. Model discrimination was quantified using the area under the receiver operating characteristic curve (AUROC).
    RESULTS: Several CGM measures-including mean glucose, standard deviation (SD), maximum glucose, %Time >140 mg/dL, %Time >120 mg/dL, glucose management indicator (GMI), mean of daily differences (MODD), mean amplitude of glycemic excursions (MAGE), area under the CGM curve (AUC-CGM), and high blood glucose index (HBGI)-were significantly associated with adverse neonatal outcomes (P < .05). Metrics demonstrating higher discrimination than the original ≥10% time-above-range measure (AUROC = 0.643) included SD (0.656), MAGE (0.665), mean glucose (0.676), GMI (0.676), maximum glucose (0.683), %Time >120 mg/dL (0.683), AUC-CGM (0.692), HBGI (0.701), and %Time >140 mg/dL (0.703).
    CONCLUSIONS: Continuous glucose monitoring metrics reflecting sustained or high-level hyperglycemia, rather than GV-focused metrics, more strongly predicted adverse neonatal outcomes. These findings suggest that persistent or extreme maternal glucose elevations, rather than variability alone, may drive neonatal risk and support refining CGM-based screening approaches in pregnancy.
    Keywords:  continuous glucose monitoring; gestational diabetes screening; glycemic variability; hyperglycemia; large for gestational age; neonatal
    DOI:  https://doi.org/10.1177/19322968261461603
  9. Diabetes Technol Ther. 2026 Jul 02. 15209156261466873
    Continuous Glucose Monitoring Metrics and Perinatal Outcomes in Pregnant Women with Type 2 Diabetes.
    Angel Chemoul, Soulaima Trigui, Alina Ciofu, Joelle Neizelien, Alfred Penfornis, Coralie Amadou.
       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.
    Keywords:  continuous glucose monitoring; macrosomia; neonatal hypoglycemia; perinatal outcomes; pregestational diabetes; type 2 diabetes
    DOI:  https://doi.org/10.1177/15209156261466873
  10. Stud Health Technol Inform. 2026 Jun 29. 338 61-65
    An Integrated Visualization of Continuous Glucose and Insulin Pump Data for Patients.
    Eunyoung Cho, Jennifer McGinnis, Yang Gong.
      Continuous glucose monitoring (CGM) and insulin pump technologies generate extensive physiological and therapeutic data. Most commercial platforms display data streams separately, requiring users to cognitively integrate events that influence glycemic outcomes. This segmentation may obscure the relationships among glucose fluctuations, insulin administration, and meal patterns, potentially impairing decision-making. This project employed the UFuRT framework to create a unified visualization that consolidates glucose traces, bolus events, basal profiles, and carbohydrate intake into a single timeline. Supplementary 14-day heatmaps and summary widgets facilitate pattern recognition and interpretation of metrics such as Time in Range (TIR), Glucose Management Indicator (GMI), and glucose variability. Design decisions were guided by evidence from diabetes informatics, human factors research, and visualization science. A high-fidelity Figma prototype was developed for heuristic evaluation and cognitive walkthroughs. The potential benefits include reduced interpretation time, improved recognition of cause-and-effect relationships, and supporting safer insulin adjustment decisions.
    Keywords:  Continuous Glucose Monitoring; Human-Centered Design; Insulin Pump; Patient Safety; Visualization
    DOI:  https://doi.org/10.3233/SHTI260796
  11. Diabetes Obes Metab. 2026 Jul 01.
    Exercise or Fasting in Individuals With Type 2 Diabetes Receiving Once-Weekly Basal Insulin Icodec.
    Thomas R Pieber, Harpreet S Bajaj, Gabriele Fluhr, Klara R Klein, Thaís M Pagliaro Rocha, Harald Sourij, Eva Svehlikova, Keerthana Udupa, Sara K Watt, Maria Willerslev-Olsen, Rasmus Ribel-Madsen.
       AIMS: To investigate glucose levels and hypoglycaemia risk during exercise or fasting in adults with type 2 diabetes (T2D) treated with once-weekly basal insulin icodec.
    MATERIALS AND METHODS: Thirty basal insulin-treated, physically active individuals with T2D (18-75 years, glycated haemoglobin ≤ 75 mmol/mol, peak oxygen uptake > 20 mL/kg/min) received once-weekly icodec for ≥ 7 weeks targeting pre-breakfast plasma glucose (PG) of 4.4-7.2 mmol/L. The final three weeks at icodec steady state comprised a reference week (no additional intervention), an exercise week (40 min cycling [60% peak oxygen uptake] 43 h post-dose) and a fasting week (18 h fasting 26 h post-dose). PG was measured at prespecified time points related to exercise and fasting. If PG < 5.0 mmol/L before exercise, or < 4.0 mmol/L between exercise onset and 140 min post-exercise or during fasting, oral carbohydrate (exercise) or intravenous glucose (fasting) was given. Blinded continuous glucose monitoring (CGM) data were collected throughout.
    RESULTS: Mean ± standard deviation CGM-based time below range < 3.0 mmol/L was 0.3% ± 1.1% during 24 h from exercise onset, 0.2% ± 0.8% during 18 h fasting and 0.0% ± 0.0% during the corresponding reference period. No clinically significant or severe hypoglycaemia was reported. Oral carbohydrate was given to 1, 0 and 3 participants pre-, during and post-exercise. Intravenous glucose was given to 15 participants (50%) during fasting (earliest at 10.6 h after start of fasting).
    CONCLUSIONS: The current results reinforce the safety profile of once-weekly basal insulin icodec and provide guidance on glycaemic management during exercise or fasting in people with T2D treated with icodec.
    TRIAL REGISTRATION: NCT06288412.
    Keywords:  basal insulin; continuous glucose monitoring (CGM); exercise intervention; hypoglycaemia; type 2 diabetes
    DOI:  https://doi.org/10.1111/dom.71050
  12. Front Endocrinol (Lausanne). 2026 ;17 1834479
    High-intensity interval training and continuous glucose monitoring-derived glycemic outcomes in adults with type 2 diabetes: a systematic review and meta-analysis.
    Jun Li, Jin Yuan, Yong Zhang, Quanwen Zeng, Haifeng Ma.
       Background: Type 2 diabetes (T2D) is characterized by chronic hyperglycemia and marked within-day glucose fluctuations. Compared with conventional glycemic markers, continuous glucose monitoring (CGM)-derived metrics provide complementary information on overall glycemic exposure, postprandial responses, and glycemic variability. Although high-intensity interval training (HIIT) has shown promise for improving glycemic control in T2D, its effects on CGM-derived outcomes have not been systematically synthesized.
    Objective: To systematically review and meta-analyze the effects of HIIT on CGM-derived glycemic outcomes in adults with T2D, compared with non-exercise control (CON) or other exercise interventions.
    Methods: PubMed, Embase, Web of Science, the Cochrane Library, and EBSCOhost were searched from inception to January 26, 2026. Interventional studies comparing HIIT with CON or other exercise interventions and reporting CGM-derived outcomes were included. When data were suitable for quantitative pooling, pooled estimates were calculated from change-from-baseline values using fixed- or random-effects models. Risk of bias was assessed using RoB 2, RoB 2 for crossover trials, or ROBINS-I, and certainty of evidence was evaluated with GRADE.
    Results: Twelve studies involving 177 participants were included. Compared with CON, HIIT reduced 24-hour mean glucose, postprandial glucose, and time spent in hyperglycemia, while its effect on mean amplitude of glycemic excursions (MAGE) remained uncertain. Compared with moderate-intensity continuous training (MICT), HIIT further reduced 24-hour mean glucose and time spent in hyperglycemia, but no significant between-group difference was found for MAGE. Overall certainty of evidence ranged from very low to low.
    Conclusions: HIIT may improve selected CGM-derived glycemic outcomes in adults with T2D, particularly postprandial glucose and hyperglycemic exposure. Compared with MICT, HIIT may offer additional benefits for reducing 24-hour mean glucose and hyperglycemic time. However, confidence in these findings is limited by the small number of studies, methodological limitations, and heterogeneity.
    Keywords:  24-hour mean glucose; continuous glucose monitoring; high-intensity interval training; meta-analysis; postprandial glucose; systematic review; time spent in hyperglycemia; type 2 diabetes
    DOI:  https://doi.org/10.3389/fendo.2026.1834479
  13. Diabetes Obes Metab. 2026 Jul 01.
    Tirzepatide Is Associated With Improved Metabolic Outcomes in People With Type 1 Diabetes and Overweight or Obesity: A Retrospective Cohort Study.
    Amanda R Purcell, Matilda S G Longfield, Natassia Rodrigo, Sarah J Glastras.
       AIMS: To evaluate the effect of tirzepatide on body weight, glycaemic control, insulin requirements, continuous glucose monitoring (CGM) metrics and cardiorenal parameters in adults with Type 1 diabetes (T1D) and overweight or obesity.
    MATERIALS AND METHODS: In this retrospective matched cohort study, adults with T1D, BMI ≥ 27 kg/m2, CGM use and available baseline and follow-up electronic medical record data from Royal North Shore Hospital and the Northern Sydney Endocrine Centre between 2020 and 2025 were included. Twenty-three adults treated with tirzepatide were identified and propensity score-matched to 23 control participants. Primary outcomes included changes in percentage change in body weight, HbA1c, total daily insulin dose and CGM-derived metrics from baseline to follow-up. Exploratory outcomes included changes in blood pressure and biochemical markers.
    RESULTS: Mean follow-up duration in the tirzepatide and control groups were 28 and 31 weeks, respectively. The most common dose of tirzepatide was 5 mg/week (52.2% participants). Compared with controls, tirzepatide was associated with greater reductions in body weight (-10.01% ± 4.74% vs. +0.69% ± 3.77%, adj-p < 0.0001) and total daily insulin dose (-21.82 ± 16.30 vs. +5.62 ± 11.63 U/day; adj-p = 0.002). From baseline to end-of-study, tirzepatide was associated with a reduction in glucose management indicator, glucose SD and daily carbohydrate intake. Other CGM, blood pressure, lipid, hepatic and renal outcomes did not differ.
    CONCLUSIONS: In adults with T1D and overweight or obesity, adjunctive tirzepatide treatment was associated with clinically meaningful reductions in percentage body weight and insulin requirements. Larger prospective studies are needed to confirm efficacy, ensure safety and assess broader cardiometabolic effects.
    Keywords:  GLP‐1 analogue; antiobesity drug; continuous glucose monitoring (CGM); database research; incretin therapy; real‐world evidence
    DOI:  https://doi.org/10.1111/dom.71063
  14. Diabet Med. 2026 Jul 01. e70372
    Continuing automated insulin delivery systems during hospitalisation with type 1 diabetes: A thematic literature review.
    Hannah Cunningham, Alicia Jenkins, David N O'Neal, Melissa H Lee.
       AIMS: A thematic review that identifies and summarises available evidence for people with Type 1 diabetes (T1D) continuing automated insulin delivery (AID) systems in the hospital setting, primarily with a focus on assessing the in-hospital safety and efficacy of AID use.
    METHODS: A thematic review was conducted searching Embase, MEDLINE and EBSCO for English language publications from 2014 to 2025 using keywords including AID system brands and terms related to insulin pumps and to inpatients. Eligible studies included original research, retrospective observational studies and case reports and series.
    RESULTS: Of 1043 articles identified, 1037 did not meet the inclusion criteria. Six articles were reviewed in detail, and a further two papers were identified by screening the reference list of the six papers. There is a paucity of evidence, with heterogeneous methodology regarding the safety and efficacy of continuing AID in hospitalised people with T1D. Results support the feasibility of continuing AID use from the ambulatory to the inpatient setting in hospitalised people with T1D. There is a trend towards improved time in recommended glucose ranges or mean glucose levels without increased hypoglycaemia. There were no adverse glucose outcomes or diabetic ketoacidosis reported.
    CONCLUSIONS: Whilst continuing AID in the inpatient setting appears promising, our review identified significant heterogeneity in patient populations, device types, as well as limited data on healthcare professional perspectives and person-reported outcomes. Further studies and guidelines are merited. Until then, inpatient use of AID should be guided by specialist diabetes healthcare teams with expertise in diabetes technology.
    Keywords:  Continuous Glucose Monitoring; Hospitalisation; Inpatients; Insulin Infusion Pumps; Patient Safety; Type 1 Diabetes Mellitus
    DOI:  https://doi.org/10.1111/dme.70372
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