bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2025–07–20
nineteen papers selected by
Mott Given



  1. Sci Rep. 2025 Jul 12. 15(1): 25215
      Elucidating the outcomes of patients using continuous glucose monitoring (continuous glucose monitoring) in day-to-day clinical practice could help expand optimal practice guidelines in prevention and mitigation of diabetic retinopathy (DR). Retrospective cohort study. Subjects, Participants, and/or Controls: 13,302 patients with NPDR initiated on continuous glucose monitoring, compared with 179,079 patients with NPDR not initiated on continuous glucose monitoring before propensity score matching (propensity score matching) at one year. TriNetX (Cambridge, MA, USA), was used to identify patients diagnosed with NPDR stratified by initiation of continuous glucose monitoring or not with at least six months of follow-up. propensity score matching controlled for baseline demographics and medical comorbidities. After propensity score matching, 12,730 patients were subsequently analyzed in each cohort. Use of continuous glucose monitoring was associated with lower risk of vision threatening complications (DME: hazards ratio [HR], 0.87, 95% CI, 0.82-0.93; P < .001; PDR: HR, 0.74, 95% CI, 0.66-0.82; P < .001; VH: HR, 0.55, 95% CI, 0.47-0.66; P < .001; TRD: HR, 0.42, 95% CI, 0.27-0.68; P = .027), and need for ocular intervention (anti-VEGF injection: HR, 0.72, 95% CI, 0.65-0.80; P < .001; PRP: HR, 0.53, 95% CI, 0.44-0.64; P < .001; PPV: HR, 0.37, 95% CI, 0.26-0.51; P < .001) among patients with NPDR when compared with matched patients not using continuous glucose monitoring at 1 year. Similar associations at two years were found. continuous glucose monitoring use in patients with NPDR without prior ocular therapy was associated with lower risk of progression to vision threatening complications as well as need for ocular intervention at one year and two years, highlighting that glycemic variability and time in range are important factors influencing the risk of complications from diabetic eye disease.
    Keywords:  Continuous glucose monitoring; Diabetic macular edema; Panretinal photocoagulation; Pars plan vitrectomy; Proliferative diabetic retinopathy; Vascular endothelial growth factor
    DOI:  https://doi.org/10.1038/s41598-025-08971-7
  2. JCEM Case Rep. 2025 Aug;3(8): luaf147
      Management of hyperglycemia in glucokinase-maturity-onset diabetes of the young (GCK-MODY) pregnancies is dependent on whether the fetus inherits the mutant GCK allele. Current recommendations include frequent ultrasounds in the third trimester to detect excessive fetal growth, which points toward an unaffected fetus who is at risk of macrosomia and could benefit from treatment with insulin. We present a case of continuous glucose monitoring (CGM) use in GCK-MODY pregnancy, in whom insulin treatment was initiated early. We discuss the CGM-glucometrics that associate with pregestational diabetes and how these could apply in the setting of GCK-MODY pregnancies to guide the need for insulin treatment when the fetal genotype is unknown. There remains a need to establish CGM thresholds for insulin initiation and glycemic targets in GCK-MODY pregnancies.
    Keywords:  continuous glucose monitoring; fetal macrosomia; glucokinase; maturity onset diabetes of the young; pregnancy
    DOI:  https://doi.org/10.1210/jcemcr/luaf147
  3. Am J Physiol Endocrinol Metab. 2025 Jul 12.
      Disposition Index (DI), defined as the product of insulin sensitivity and beta-cell responsivity, is the best measure of beta-cell function. This is usually assessed from plasma glucose and insulin, and sometimes C-peptide, data either from surrogate indices or model-based methods. However, the recent advent of continuous glucose monitoring (CGM) systems in non-insulin-treated individuals, raises the possibility of its quantification in outpatients. As a first step, we propose a method to assess DI from glucose concentration data only and validated it against the oral minimal model (OMM). To do so, we used data from two clinical mixed meal tolerance test (MTT) studies in non-insulin-treated individuals: the first consisted of 14 individuals with type 2 diabetes studied twice, either after receiving a DPP-4 inhibitor or a placebo before the meal, while the second consisted of 62 individuals, with and without pre- or type 2 diabetes. A third, simulated, dataset consisted of 100 virtual subjects from the Padova Type 2 Diabetes Simulator was used for additional tests. Plasma glucose, insulin and C-peptide concentrations were used to estimate the reference DI from the OMM (DIMM), while glucose data only were used to calculate the proposed DI (DIG). DIG was well correlated with DIMM in both the clinical and simulated datasets (R between 0.88 and 0.79, p<0.001), and exhibited the same between-visit or between-group pattern. DIG can be used to assess therapy effectiveness and degree of glucose tolerance using glucose data only, paving the way to potentially assess beta-cell function in real-life conditions using CGM.
    Keywords:  CGM; decision support system; mathematical modeling; non-insulin-treated; outpatient
    DOI:  https://doi.org/10.1152/ajpendo.00407.2024
  4. Diabetes Obes Metab. 2025 Jul 15.
      
    Keywords:  continuous glucose monitoring (CGM); effectiveness; type 1 diabetes; type 2 diabetes
    DOI:  https://doi.org/10.1111/dom.16624
  5. Diabetol Metab Syndr. 2025 Jul 16. 17(1): 276
      Attaining an adequate glycemic control has been associated with a better prognosis and with a reduction in the risk of developing long-term microvascular and macrovascular diabetic complications. Continuous glucose monitoring (CGM) has been shown to improve glycemic control and reduce blood glucose variability. Furthermore, CGM is associated with greater treatment adherence and higher satisfaction. Hypoglycemia is the most frequent acute complication in individuals with insulin treated diabetes and may limit the achievement of glycemic control. Furthermore, repeated episodes of hypoglycemia, particularly when a severe hypoglycemia event occurs are associated with adverse outcomes. The introduction of glucose alarms improves not only safety of subjects, but also contributes to improve glycemic control. However, depending on the glycemic thresholds, the frequency of alarms could be perceived as excessive, leading to a state of 'alarm fatigue', limiting the effective response to the alarms by the individual. The optimization of alarm thresholds tailored to individual needs and preferences can enhance the clinical utility of CGM while minimizing alarm fatigue. When alarms occur, their underlying causes should be investigated to enable appropriate corrections and adjustments. CGM systems equipped with alarms, such as FreeStyle Libre 2, have demonstrated efficacy in reducing hyperglycemia and severe hypoglycemic events, leading to improvements in time in range and quality of life of people with diabetes.
    Keywords:  Diabetes; Flash continuous glucose monitoring; Glucose alarm; Hyperglycemia; Hypoglycemia
    DOI:  https://doi.org/10.1186/s13098-025-01797-3
  6. CPT Pharmacometrics Syst Pharmacol. 2025 Jul 16.
      For the treatment of Type 2 Diabetes, high efficacy approaches such as Glucagon-like peptide 1 (GLP-1)-based therapies are recommended for glucose control. Prediction of the clinical outcome of these therapies on glucose and hemoglobin A1c (HbA1c), using early available pharmacokinetic and in vitro efficacy information, can be a valuable tool for compound selection and supporting drug development. Our previously developed glucose homeostasis model (the 4GI model) is a systems model that is able to quantify drug effects on glucose based on in vitro potency and PK information. In this research, the model was coupled to an existing integrated glucose-red blood cell-HbA1c (IGRH) model for predicting the effects of GLP-1 and GLP-1/glucagon (dual) receptor agonists, liraglutide and cotadutide, on glucose and HbA1c. The 4GI model was validated for predicting 24-h glucose (Cglc,av) with minimal model calibration using short-term Ph2a continuous glucose monitoring (CGM) data. Subsequently, the predicted Cglc,av served as input for the HbA1c model to assess the predictiveness of the combined 4GI-HbA1c model on HbA1c. The resulting combined model was used in cotadutide's clinical development by providing predictive insights into the 26 weeks glucose and HbA1c dynamics of the Ph2b study prior to its initiation. Retrospective analysis showed that the model adequately predicted the effect of cotadutide and liraglutide on fasting plasma glucose and HbA1c (Root Means Square Percent Error (RMSPE) 5.9% and 13%, respectively). This demonstrates the potential of the 4GI-HbA1c systems model as a valuable tool in supporting the clinical development of novel GLP-1 and/or glucagon agonists.
    Keywords:  4GI; GLP‐1R agonists; QSP; cotadutide; diabetes; systems pharmacology
    DOI:  https://doi.org/10.1002/psp4.70074
  7. Sci Rep. 2025 Jul 17. 15(1): 25920
      Elevated postprandial glucose levels present a global epidemic and a major challenge in type-2 diabetes (T2D) management. A key barrier to developing effective dietary interventions for T2D management is the wide inter-individual variation in glycemic and behavioral responses, which limits the impact of one-size-fits-all recommendations. To enable personalized dietary prompts for glycemic control, it is critical to first predict an individual's susceptibility to elevated postprandial (PPG) levels-or state of momentary vulnerability to PPG excursions. We examined the feasibility of personalized models to predict PPG excursions,and their associated vulnerability states, in the daily lives of 67 Chinese adults with T2D (Mage = 61.39; median = 63.00; 35 women; 2,463 glucose observations). We developed machine learning models trained on past individual observations to predict the next-in-time PPG excursion, using continuous glucose monitoring (CGM) data or CGM data combined with manually-logged meals and glucose-lowering agent intake. On average, personalized models predicted PPG excursions (F1-score: M = 75.88%; median = 78.26%), with substantial variation in predictability across individuals. Notably, no two individuals shared the same dietary and temporal predictors of PPG excursions. This study is the first to predict individual vulnerability states to glucose responses among adults with T2D in China. Findings can help personalize just-in-time adaptive interventions by tailoring dietary prompts based on individuals' unique vulnerability states to PPG excursions. This approach can inform the development of digital dietary interventions in mHealth apps and clinical decision support tools, thereby helping optimize glycemic control and patient-centered T2D lifestyle management..
    Keywords:  Dietary interventions; Just-in-time-adaptive interventions (JITAIs); Machine learning; Nutrition; Personalized nutrition; Type-2 diabetes management
    DOI:  https://doi.org/10.1038/s41598-025-08003-4
  8. J Am Geriatr Soc. 2025 Jul 12.
       BACKGROUND: Diabetes is common among older adults. While most cases are type 2, treatment advances and more adult-onset cases have led to more individuals living with type 1 diabetes. All older adults with diabetes are at an increased risk for hypoglycemia, yet this risk is especially high among those with type 1 diabetes due to the lifelong requirement for insulin. Advanced diabetes technologies-such as continuous glucose monitoring (CGM) and automated insulin delivery systems (AID)-can improve glycemic management, enhance safety, and reduce complications in insulin-requiring individuals.
    AIMS: We aimed to review randomized controlled trials that tested the feasibility and effectiveness of diabetes technology in older adult populations.
    METHODS: We conducted a searchfrom 08/15/2024-09/15/2024 that was updated 01/15/2025. We selected six studies testing CGM and AID use in adults ≥ 60 with diabetes, ≥ 3 months follow-up, ≥ 30 participants, and primary glycemic outcomes, prioritizing methodological rigor and clinical relevance.
    RESULTS: The selected studies demonstrated that CGM reduces hypoglycemia and increases time spent in the target glucose range (70-180 mg/dL) compared to blood glucose monitoring in older adults, with benefits seen across insulin regimens and diabetes types. AID systems reduce both hypoglycemia and hyperglycemia in older adults with type 1 diabetes. Participant adherence and acceptability measures were consistantly high.
    DISCUSSION: These trials suggest that diabetes technology is feasible to implement in older adult populations and can reduce hypoglycemia without increasing hyperglycemia.
    CONCLUSIONS: Additional research testing these technologies among populations with age-related impairments is necessary, as are efforts to implement and ensure broad accessibility of these technologies across diverse care settings, including primary and geriatrics care.
    Keywords:  automated insulin delivery; continuous glucose monitoring; older adults; technology; type 1 diabetes; type 2 diabetes
    DOI:  https://doi.org/10.1111/jgs.19595
  9. J Clin Endocrinol Metab. 2025 Jul 13. pii: dgaf289. [Epub ahead of print]
       CONTEXT: Women with preexisting diabetes mellitus (PDM) are at increased risk of pregnancy-related complications.
    OBJECTIVE: To summarize the available supporting evidence for the Endocrine Society guidelines about management of PDM in pregnancy.
    DATA SOURCES: MEDLINE, EMBASE, Scopus, and other sources through February 2025.
    STUDY SELECTION: Studies were selected by pairs of independent reviewers.
    DATA EXTRACTION: Data were extracted by pairs of independent reviewers.
    DATA SYNTHESIS: We included 17 studies. Meta-analysis showed no significant difference between hybrid closed-loop insulin pump (HCL) and standard of care regarding time in range (TIR), time above range (TAR), and time below range (TBR). HCL had better overnight TIR and TBR. For women with type 2 diabetes mellitus (T2DM), intermittent use of continuous glucose monitoring (CGM) was not associated with a significant change in the risk of large for gestational age (LGA) neonates (2 randomized controlled trials [RCTs], 102 patients). Adding metformin to insulin was associated with a lower risk of LGA (2 RCTs, 1126 patients). Three retrospective studies (1724 patients) suggested increased neonatal complications when delivery was induced before 39 weeks of gestation (particularly before 38 weeks) in women with preexisting type 1 (T1DM) and T2DM, although this evidence was subject to likely confounding. One retrospective study showed no increase in neonatal complications with periconceptional exposure to glucagon-like peptide-1 receptor agonists. We could not identify comparative studies assessing a screening question about the possibility of pregnancy or a carbohydrate restrictive diet.
    CONCLUSION: This systematic review addresses various aspects of managing PDM in pregnancy and will support the development of the Endocrine Society guidelines.
    Keywords:  hybrid closed-loop insulin pump; preexisting diabetes mellitus; pregnancy; systematic review
    DOI:  https://doi.org/10.1210/clinem/dgaf289
  10. Diabetes Res Clin Pract. 2025 Jul 09. pii: S0168-8227(25)00386-9. [Epub ahead of print]226 112372
       AIMS: This study analyzed the impact of implementing intermittently scanned continuous glucose monitoring (isCGM) on hospitalization rates for diabetic ketoacidosis (DKA) among adults with type 1 diabetes mellitus (T1DM). Additionally, it assessed the direct costs and savings associated with these hospital admissions.
    METHODS: A comprehensive regional dataset from Andalusia, Spain, was used to extract emergency care codes for DKA in individuals with T1DM who started using isCGM between January 1, 2020, and December 31, 2021. Hospitalization rates for DKA were compared during the 12 months before and after isCGM implementation to determine population-level incidence rates.
    RESULTS: The study included 13,616 individuals with T1DM (mean age: 43.7 ± 13.5 years, 46.9 % women). The incidence rate of DKA hospitalizations decreased from 79.26 to 40.28 admissions per 10,000 person-years (rate ratio [RR]: 0.5 [0.40-0.63]). The most significant reduction was observed in patients with HbA1c ≥ 10 %, with 136 fewer events per 10,000 person-years. This reduction resulted in an estimated cost saving of €782,836.81.
    CONCLUSION: The implementation of isCGM significantly reduced DKA hospital admissions in adults with T1DM, leading to substantial cost savings. These findings highlight the clinical and economic benefits of isCGM in improving patient outcomes and optimizing healthcare resources.
    Keywords:  Acute diabetes complications; Diabetic ketoacidosis; Hyperglycemia; Public health system; Type 1 diabetes; intermittently-scanned Continuous Glucose Monitoring
    DOI:  https://doi.org/10.1016/j.diabres.2025.112372
  11. Front Endocrinol (Lausanne). 2025 ;16 1536292
       Objective: This study evaluated the performance of the SiJoy GS1 Continuous Glucose Monitor (CGM) system by analyzing the time lag between plasma glucose (PG) and CGM measurements during an Oral Glucose Tolerance Test (OGTT) in healthy adults. This investigation would elucidate the implications of physiological delay time and optimize technical delays in populations.
    Research design and methods: A total of 129 participants wore SiJoy GS1 sensors on their posterior upper arms for at least 48 hours before undergoing an OGTT.
    Results: To minimize the Mean Absolute Relative Difference (MARD), two approaches were tested: MARD minimization and minimum deviation match. The demographic characteristics of the participants included a mean age of 37.62 (± 11.21) years, height of 169.84 (± 7.81) cm, and weight of 71.86 (± 18.0) kg. Among them 69.0% were healthy. SiJoy GS1 sensors exhibit an excellent performance of consistency with 96.6% at 20/20% and MARD of 8.01(± 4.9) % at the fasting phase. The consensus error grid results showed 89.22% of all values fell within Zone A, and 100% of values were in Zone A+B collectively. In terms of minimizing Mean Absolute Relative Difference (MARD), at 30 minutes of OGTT, the first method suggested a 15-minute delay while the second proposed a 10-minute average delay time. The latter approach was more suitable due to the less variability in the timing of glucose peaks during the OGTT.
    Conclusions: In the study, the SiJoy GS1 sensor exhibited consistent performance. Its accuracy was unaffected by subject characteristics. The application of the minimum deviation match method proved advantageous in reducing the CGM delay time.
    Keywords:  accuracy; analytical bias; continuous glucose monitoring (CGM); glucose control; plasma glucose
    DOI:  https://doi.org/10.3389/fendo.2025.1536292
  12. J Clin Endocrinol Metab. 2025 Jul 13. pii: dgaf288. [Epub ahead of print]
       BACKGROUND: Preexisting diabetes (PDM) increases the risk of maternal and perinatal mortality and morbidity. Reduction of maternal hyperglycemia prior to and during pregnancy can reduce these risks. Despite compelling evidence that preconception care (PCC), which includes achieving strict glycemic goals, reduces the risk of congenital malformations and other adverse pregnancy outcomes, only a minority of individuals receive PCC. Suboptimal pregnancy outcomes demonstrated in real-world data highlight the need to further optimize prenatal glycemia. New evolving technology shows promise in helping to achieve that goal. Dysglycemia is not the only driver of poor pregnancy outcomes in PDM. The increasing impact of obesity on pregnancy outcomes underscores the importance of optimal nutrition and management of insulin sensitizing medications during prenatal care for PDM.
    OBJECTIVE: To provide recommendations for the care of individuals with PDM that lead to a reduction in maternal and neonatal adverse outcomes.
    METHODS: The Guideline Development Panel (GDP) composed of a multidisciplinary panel of clinical experts, along with experts in guideline methodology and systematic literature review, identified and prioritized 10 clinically relevant questions related to the care of individuals with diabetes before, during and after pregnancy. The GDP prioritized randomized controlled trials (RCTs) evaluating the effects of different interventions (eg, PCC, nutrition, treatment options, delivery) during the reproductive life cycle of individuals with diabetes, including type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Systematic reviews queried electronic databases for publications related to these 10 clinical questions. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence and develop recommendations. The approach incorporated perspectives from 2 patient representatives and considered patient values, costs and resources required, acceptability and feasibility, and impact on health equity of the proposed recommendations.
    RESULTS: In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest asking a screening question about pregnancy intention at every reproductive, diabetes, and primary care visit. Screening for pregnancy intent is also suggested at urgent care/emergency room visits when clinically appropriate (2 | ⊕OOO). This was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced glycated hemoglobin (HbA1c) at the first prenatal visit and congenital malformations.In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest use of contraception when pregnancy is not desired (2 | ⊕⊕OO). This was suggested based on indirect evidence in women with diabetes, where PCC-including contraception as a key component-showed a clinically significant association with improvements in first-trimester HbA1c and the rate of congenital malformations, together with indirect evidence from the general population regarding the reduction of unplanned pregnancies and pregnancy terminations with the use of contraception.In individuals with T2DM, we suggest discontinuation of glucagon-like peptide-1 receptor agonist (GLP-1RA) before conception rather than discontinuation between the start of pregnancy and the end of the first trimester (2 | ⊕OOO). This was suggested based on limited data on risk of exposure to GLP-1RA receptor agonists during pregnancy.In pregnant individuals with T2DM already on insulin, we suggest against routine addition of metformin (2 | ⊕OOO). This was suggested based on the GDP judgment that the benefit of adding metformin to insulin to achieve decrease in rates of large for gestational age infants did not outweigh the potential harm of increasing the risk of small for gestational age infants or adverse childhood outcomes related to changes in body composition.In individuals with PDM, we suggest either a carbohydrate-restricted diet (<175 g/day) or usual diet (>175 g/day) during pregnancy (2 | ⊕OOO). This was suggested based on the GDP judgment that the available evidence was limited and very indirect, resulting in significant uncertainty about the net benefits or harms. As such, the evidence was insufficient to support a recommendation either for or against a carbohydrate intake cutoff of 175 g/day.In pregnant individuals with T2DM, we suggest either the use of a continuous glucose monitor (CGM) or self-monitoring of blood glucose (SMBG) (2 | ⊕OOO). There is lack of direct evidence supporting superiority of CGM use over SMBG for T2DM during pregnancy. There is indirect evidence supporting improved glucometrics with the use of CGM for individuals with T2DM outside of pregnancy, substantial improvements in neonatal outcomes for individuals with T1DM using CGM during pregnancy and the potential for decreasing adverse pregnancy outcomes with improved glucometrics in individuals with T2DM.In individuals with PDM using a CGM, we suggest against the use of a single 24-hour CGM target <140 mg/dL (7.8 mmol/L) in place of standard-of-care pregnancy glucose targets of fasting <95 mg/dL (5.3 mmol/L), 1-hour postprandial <140 mg/dL (7.8 mmol/L), and 2-hour postprandial < 120 mg/dL (6.7 mmol/L) (2 | ⊕OOO). This was suggested based on indirect evidence that associated adverse pregnancy outcomes with a fasting glucose > 126 mg/dL (7 mmol/L).In individuals with T1DM who are pregnant, we suggest the use of a hybrid closed-loop pump (pump adjusting automatically based on CGM) rather than an insulin pump with CGM (without an algorithm) or multiple daily insulin injections with CGM (2 | ⊕OOO). This was suggested based on a meta-analysis of RCTs which demonstrated improvement in glucometrics with increased time in range (MD +3.81%; CI -4.24 to 11.86) and reduced time below range (MD -0.85%; CI -1.98 to 0.28) with the use of hybrid closed-loop pump technology.In individuals with PDM, we suggest early delivery based on risk assessment rather than expectant management (2 | ⊕OOO). This was suggested based on indirect evidence that risks may outweigh benefits of expectant management beyond 38 weeks gestation and that risk assessment criteria may be useful to inform ideal delivery timing.In individuals with PDM (including those with pregnancy loss or termination), we suggest postpartum endocrine care (diabetes management), in addition to usual obstetric care (2 | ⊕OOO). As the postpartum period frequently overlaps with preconception, this was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced HbA1c at the first prenatal visit and congenital malformations.
    CONCLUSION: The data supporting these recommendations were of very low to low certainty, highlighting the urgent need for research designed to provide high certainty evidence to support the care of individuals with diabetes before, during, and after pregnancy. Investment in implementation science for PCC is crucial to prevent significant mortality and morbidity for individuals with PDM and their children. RCTs to further define glycemic targets in pregnancy and refinement of emerging technology to achieve those targets can lead to significant reduction of harm and in the burden of diabetes care. Data on optimal nutrition and obesity management in pregnancy are lacking. More research on timing of delivery in women with PDM is also needed.
    Keywords:  automated insulin delivery; continuous glucose monitor (CGM); delivery timing; glucagon-like peptide -1 receptor agonist (GLP1-RA); hybrid closed loop; insulin pump; metformin; pregnancy; type 1 diabetes; type 2 diabetes
    DOI:  https://doi.org/10.1210/clinem/dgaf288
  13. Eur J Endocrinol. 2025 Jun 30. 193(1): G1-G48
       BACKGROUND: Preexisting diabetes (PDM) increases the risk of maternal and perinatal mortality and morbidity. Reduction of maternal hyperglycemia prior to and during pregnancy can reduce these risks. Despite compelling evidence that preconception care (PCC), which includes achieving strict glycemic goals, reduces the risk of congenital malformations and other adverse pregnancy outcomes, only a minority of individuals receive PCC. Suboptimal pregnancy outcomes demonstrated in real-world data highlight the need to further optimize prenatal glycemia. New evolving technology shows promise in helping to achieve that goal. Dysglycemia is not the only driver of poor pregnancy outcomes in PDM. The increasing impact of obesity on pregnancy outcomes underscores the importance of optimal nutrition and management of insulin sensitizing medications during prenatal care for PDM.
    OBJECTIVE: To provide recommendations for the care of individuals with PDM that lead to a reduction in maternal and neonatal adverse outcomes.
    METHODS: The Guideline Development Panel (GDP) composed of a multidisciplinary panel of clinical experts, along with experts in guideline methodology and systematic literature review, identified and prioritized 10 clinically relevant questions related to the care of individuals with diabetes before, during and after pregnancy. The GDP prioritized randomized controlled trials (RCTs) evaluating the effects of different interventions (eg, PCC, nutrition, treatment options, delivery) during the reproductive life cycle of individuals with diabetes, including type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). Systematic reviews queried electronic databases for publications related to these 10 clinical questions. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology was used to assess the certainty of evidence and develop recommendations. The approach incorporated perspectives from 2 patient representatives and considered patient values, costs and resources required, acceptability and feasibility, and impact on health equity of the proposed recommendations.
    RESULTS: In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest asking a screening question about pregnancy intention at every reproductive, diabetes, and primary care visit. Screening for pregnancy intent is also suggested at urgent care/emergency room visits when clinically appropriate (2 | ⊕OOO). This was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced glycated hemoglobin (HbA1c) at the first prenatal visit and congenital malformations.In individuals with diabetes mellitus who have the possibility of becoming pregnant, we suggest use of contraception when pregnancy is not desired (2 | ⊕⊕OO). This was suggested based on indirect evidence in women with diabetes, where PCC-including contraception as a key component-showed a clinically significant association with improvements in first-trimester HbA1c and the rate of congenital malformations, together with indirect evidence from the general population regarding the reduction of unplanned pregnancies and pregnancy terminations with the use of contraception.In individuals with T2DM, we suggest discontinuation of glucagon-like peptide-1 receptor agonist (GLP-1RA) before conception rather than discontinuation between the start of pregnancy and the end of the first trimester (2 | ⊕OOO). This was suggested based on limited data on risk of exposure to GLP-1RA receptor agonists during pregnancy.In pregnant individuals with T2DM already on insulin, we suggest against routine addition of metformin (2 | ⊕OOO). This was suggested based on the GDP judgment that the benefit of adding metformin to insulin to achieve decrease in rates of large for gestational age infants did not outweigh the potential harm of increasing the risk of small for gestational age infants or adverse childhood outcomes related to changes in body composition.In individuals with PDM, we suggest either a carbohydrate-restricted diet (<175 g/day) or usual diet (>175 g/day) during pregnancy (2 | ⊕OOO). This was suggested based on the GDP judgment that the available evidence was limited and very indirect, resulting in significant uncertainty about the net benefits or harms. As such, the evidence was insufficient to support a recommendation either for or against a carbohydrate intake cutoff of 175 g/day.In pregnant individuals with T2DM, we suggest either the use of a continuous glucose monitor (CGM) or self-monitoring of blood glucose (SMBG) (2 | ⊕OOO). There is lack of direct evidence supporting superiority of CGM use over SMBG for T2DM during pregnancy. There is indirect evidence supporting improved glucometrics with the use of CGM for individuals with T2DM outside of pregnancy, substantial improvements in neonatal outcomes for individuals with T1DM using CGM during pregnancy and the potential for decreasing adverse pregnancy outcomes with improved glucometrics in individuals with T2DM.In individuals with PDM using a CGM, we suggest against the use of a single 24-hour CGM target <140 mg/dL (7.8 mmol/L) in place of standard-of-care pregnancy glucose targets of fasting <95 mg/dL (5.3 mmol/L), 1-hour postprandial <140 mg/dL (7.8 mmol/L), and 2-hour postprandial < 120 mg/dL (6.7 mmol/L) (2 | ⊕OOO). This was suggested based on indirect evidence that associated adverse pregnancy outcomes with a fasting glucose > 126 mg/dL (7 mmol/L).In individuals with T1DM who are pregnant, we suggest the use of a hybrid closed-loop pump (pump adjusting automatically based on CGM) rather than an insulin pump with CGM (without an algorithm) or multiple daily insulin injections with CGM (2 | ⊕OOO). This was suggested based on a meta-analysis of RCTs which demonstrated improvement in glucometrics with increased time in range (MD +3.81%; CI -4.24 to 11.86) and reduced time below range (MD -0.85%; CI -1.98 to 0.28) with the use of hybrid closed-loop pump technology.In individuals with PDM, we suggest early delivery based on risk assessment rather than expectant management (2 | ⊕OOO). This was suggested based on indirect evidence that risks may outweigh benefits of expectant management beyond 38 weeks gestation and that risk assessment criteria may be useful to inform ideal delivery timing.In individuals with PDM (including those with pregnancy loss or termination), we suggest postpartum endocrine care (diabetes management), in addition to usual obstetric care (2 | ⊕OOO). As the postpartum period frequently overlaps with preconception, this was suggested based on indirect evidence demonstrating a strong association between PCC and both reduced HbA1c at the first prenatal visit and congenital malformations.
    CONCLUSION: The data supporting these recommendations were of very low to low certainty, highlighting the urgent need for research designed to provide high certainty evidence to support the care of individuals with diabetes before, during, and after pregnancy. Investment in implementation science for PCC is crucial to prevent significant mortality and morbidity for individuals with PDM and their children. RCTs to further define glycemic targets in pregnancy and refinement of emerging technology to achieve those targets can lead to significant reduction of harm and in the burden of diabetes care. Data on optimal nutrition and obesity management in pregnancy are lacking. More research on timing of delivery in women with PDM is also needed.
    Keywords:  automated insulin delivery; continuous glucose monitor (CGM); delivery timing; glucagon-like peptide -1 receptor agonist (GLP1-RA); hybrid closed loop; insulin pump; metformin; pregnancy; type 1 diabetes; type 2 diabetes
    DOI:  https://doi.org/10.1093/ejendo/lvaf116
  14. Endocrine. 2025 Jul 15.
       PURPOSE: Type 1 diabetes mellitus (T1D) is a chronic autoimmune disease frequently associated with other autoimmune diseases. This study aims to evaluate the prevalence of additional autoimmunity in adults with T1D and its association with glycemic control, chronic complications, and other comorbidities.
    METHODS: We performed a cross-sectional study in adult patients with T1D, followed at the Endocrinology Department of a tertiary hospital, between May 2022 and May 2024. Clinical data collected included glycemic control (HbA1c and continuous glucose monitoring [CGM] parameters), diabetes complications, and other comorbidities. These parameters were compared according to the history of autoimmune diseases. Statistical analysis was performed using parametric and non-parametric tests, ANCOVA and logistic regression models, unadjusted and adjusted for age and sex.
    RESULTS: Of the 439 participants (48.8% female and mean age 36.8 ± 14.1 years), 33.8% had at least one autoimmune disease, predominantly Hashimoto's thyroiditis (28.8%) and celiac disease (3.9%), with higher prevalence in women (p < 0.001). HbA1c (7.7 ± 1.3 vs. 7.8 ± 1.4%, p = 0.53) and CGM-derived parameters, such as glucose management indicator (7.4 ± 0.9 vs. 7.4 ± 0.8%, p = 0.44) and time in range (58.7 ± 18.9 vs. 56.6 ± 16.5%, p = 0.84), were similar in patients with and without autoimmune diseases.
    CONCLUSIONS: Over one fourth of patients with T1D had a concomitant autoimmune disease. Our results suggest that the presence of other autoimmune diseases may not preclude the attainment of similar glycemic targets. Given the high risk of autoimmunity in T1D, systematic screening and personalized treatment should be considered. Prospective studies are warranted to explore the long-term implications on metabolic control and cardiovascular outcomes.
    Keywords:  Autoimmune diseases; Celiac disease; Continuous glucose monitoring (CGM); Glycemic control; Hashimoto’s thyroiditis; Type 1 diabetes mellitus
    DOI:  https://doi.org/10.1007/s12020-025-04354-0
  15. J Clin Med. 2025 Jul 07. pii: 4782. [Epub ahead of print]14(13):
      Background: Metabolic bariatric surgery is a highly effective and long-lasting treatment for obesity and related chronic conditions. Women of reproductive age represent the largest group undergoing these procedures. Observational studies suggest an increased risk of preterm birth and impaired foetal growth in this population, though the underlying mechanisms remain unclear. A key hypothesis is that altered glucose metabolism, characterised by frequent hypoglycaemia and glycaemic fluctuations, may contribute to these adverse outcomes. While glycaemic variability following metabolic bariatric surgery has been documented, its pattern during pregnancy and impact on pregnancy outcomes are still underexplored. Methods: In this Belgian multicentre prospective cohort study, we will investigate glycaemic patterns during pregnancy in women who have undergone metabolic bariatric surgery. Women aged 18-45 years with a confirmed singleton pregnancy up to 11 weeks and 6 days and a history of Roux-en-Y gastric bypass or sleeve gastrectomy will be eligible for inclusion. Women with pregestational diabetes or those taking medication known to interfere with glucose metabolism will be excluded. All participants will receive blinded continuous glucose monitoring (Dexcom® G6) for a 10-day period at four time points throughout the pregnancy. Foetal body composition and growth will be measured during routine ultrasound; skinfolds will be measured in the neonate. The primary outcome is the association between mean glycemia and glycaemic variability on continuous glucose monitoring and birth weight. The planned sample size is ninety-five women. Linear mixed models for repeated measurements will be used for analysis. Confounders such as smoking, micronutrient deficiency, and surgery-to-conception interval will be added to the model as covariates. In a second exploratory phase, each participant in the surgical group will be matched with a control participant-without a history of metabolic bariatric surgery-based on pre-pregnancy BMI and age. Control participants will undergo the same study procedures, allowing for exploratory comparison of glycaemic patterns and other study outcomes. Discussion: This prospective longitudinal study will be the largest study using continuous glucose monitoring to investigate glucose metabolism during pregnancy after metabolic bariatric surgery and its impact on foetal growth and newborn body composition. Trial registration: ClinicalTrials.gov: NCT05084339. Registration date: 15 October 2021.
    Keywords:  Roux-en-Y gastric bypass; continuous glucose monitoring; foetal growth restriction; post bariatric hypoglycaemia; pregnancy outcome; premature birth; sleeve gastrectomy; small for gestational age
    DOI:  https://doi.org/10.3390/jcm14134782
  16. Nutr J. 2025 Jul 16. 24(1): 113
       BACKGROUND: While artificially sweetened beverages (ASBs) are widely reported to have minimal glycemic impact compared to sugar-sweetened beverages (SSBs), their effects in mixed meal conditions and individual variability in response remain poorly understood. This study aimed to evaluate postprandial glycemic response (PPGR) and individual variability in response to an SSB (regular cola) and an ASB (zero cola), both in single and mixed conditions, using continuous glucose monitoring (CGM).
    METHODS: A total of 66 healthy young adults participated in this 14-day, non-randomized crossover intervention study. Test meals included 75 g oral glucose load as a reference, muffin, regular cola, zero cola, muffin with regular cola (MRC), and muffin with zero cola (MZC). PPGR was evaluated using incremental area under the curve. The glucose dip was assessed as the minimum glucose reduction from baseline. Participants were classified as MZC-High (n = 17) if their glycemic response to MZC was higher than to MRC, and as MZC-Stable (n = 44) if MRC showed the higher response.
    RESULTS: The 75 g oral glucose load reference exhibited a typical glycemic pattern, peaking at 45 min before steadily declining. The muffin induced a moderate glycemic response, while regular cola led to a rapid glucose rise followed by a sharp decline. When combined with a muffin, MRC exhibited a slightly higher glycemic response (iAUC180:161.6 mmol∙min/L), whereas MZC showed a similar response to the muffin alone (113.3 and 111.1 mmol∙min /L, respectively). At 120 min, the glucose dip was most pronounced for regular cola, whereas oral glucose load and muffin showed smaller reductions. These patterns persisted at 180 min, with oral glucose load showing the largest drop. Mixed meals attenuated glucose dips, with MRC and MZC preventing excessive declines. Individual responses analysis revealed that while the overall iAUC was not significantly different between muffin alone and MZC, 26 participants (MZC-High Responders) exhibited a higher iAUC with MZC than with MRC, suggesting variability in glucose regulation. Comparisons between MZC-High Responders and MZC-Stable participants showed no significant differences in age or body composition.
    CONCLUSION: While zero cola alone or in combination with a muffin had a minimal overall glycemic impact, some individuals exhibited higher glycemic responses in mixed conditions. These findings suggest that individual variability and mixed condition should be considered when consuming artificially sweetened beverages.
    TRIAL REGISTRATION: Clinical Research Information Service (CRIS, cris.nih.go.kr) No. KCT0009921.
    Keywords:  Artificially sweetened beverages; Continuous glucose monitoring; Postprandial glycemic response; Sugar sweetened beverages
    DOI:  https://doi.org/10.1186/s12937-025-01181-x
  17. J Diabetes Res. 2025 ;2025 1970247
      Background: There are well-documented disparities in diabetes care outcomes and technology usage, stemming from differences in healthcare access, distrust in healthcare providers, and other factors. This study evaluated patient-level outcomes of a diabetes support coach (DSC) intervention aimed at improving underserved adults' diabetes technology use, diabetes distress, and HbA1c levels. Methods: As part of a Project Extension for Community Healthcare Outcomes (ECHO) Diabetes program, a social support intervention involving 28 DSCs was piloted at 33 Federally Qualified Health Centers (FQHCs) in Florida and California from May 2021 to May 2022. DSCs, who were adults with diabetes, served in a capacity similar to peer mentors and community health workers and received uniform training/oversight by a clinical team. Intervention participants (n = 74 adults with insulin-requiring diabetes at FQHCs) self-enrolled and engaged with DSCs via text messages, phone calls, and events. Participants' outcomes were evaluated cross-sectionally via the Diabetes Distress Scale (DDS-17) and a diabetes technology usage survey and longitudinally via HbA1c tests upon enrollment and at 6-month follow-up. A group of adults with insulin-requiring diabetes from the same FQHCs who did not receive the DSC intervention (n = 363) was used for comparison. Descriptive statistics were computed for all outcomes (n, percentage; mean, SD/95% CI). Between-group comparisons were evaluated via chi-squared and t-tests. Results: DSC intervention participants reported significantly lower diabetes distress than the comparison group (DDS-17 score mean = 1.6 vs. 2.1, p < 0.001), and significantly more participants in the DSC intervention regularly used continuous glucose monitors (CGMs) than the comparison group (69.9% vs. 38.8%, p < 0.0001). There were no significant differences in insulin pump usage or HbA1c. Conclusions: Lower diabetes distress and greater CGM usage among intervention participants suggest that the DSCs' shared lived experiences and healthcare navigation support positively influenced underserved adults' outcomes. These findings show DSCs' potential for improving diabetes care and technology equity.
    Keywords:  diabetes; health coaching; health equity; peer support; social support
    DOI:  https://doi.org/10.1155/jdr/1970247
  18. Qual Life Res. 2025 Jul 16.
       PURPOSES: Children and adolescents with type 1 diabetes (T1D) experience persistent impacts on quality of life (QoL). While most previous studies have relied on cross-sectional designs, this prospective cohort study intended to: (1) assess longitudinal changes in patient-reported QoL over a three-year period; (2) identify distinct QoL trajectory subgroups; and (3) examine demographic, physiological, psychological, and clinical determinants associated with trajectory membership and multidimensional QoL outcomes.
    METHODS: Two hundred children and adolescents with T1D from China were followed for three years in a longitudinal cohort study. QoL was measured using the Quality of Life Scale for Children and Adolescents (QLSCA) at baseline from June 2019 to May 2020, with follow-up visits at years 1, 2, and 3 thereafter. Trajectories of QoL and associations with determinants were identified via iterative estimations of group-based trajectory models and multivariable multinomial logistic regression, respectively. The specific impacts of the determinants on QoL were revealed using multiple linear regressions. Changes in QoL dimensions over time were examined using linear mixed models, while changes in determinants were analyzed using both linear mixed models and generalized estimating equations.
    RESULTS: Four QoL trajectory groups were identified (N = 200): poor (19.5%), moderate (27.5%), improving (17.5%), and good (35.5%) QoL. Improved QoL was associated with higher paternal education, greater height, lower glycosylated hemoglobin (HbA1c), fewer hypoglycemic episodes, and reduced depression levels. Furthermore, the frequency of self-monitoring of blood glucose (SMBG), Self-Management of Type 1 Diabetes for Adolescents (SMOD-A) scores, and higher parental education were positively correlated with improvements in various QoL dimensions. In contrast, higher State-Trait Anxiety Inventory-Trait (STAI-T) and Children's Depression Inventory (CDI) scores were negatively correlated with relationship between teacher and pupil, negative emotions, and other QoL aspects. Throughout the study, a significant increase in the use of continuous glucose monitoring (CGM) and insulin pumps was observed, along with improvements in SMBG and self-management ability. Notably, a reduction in the monthly frequency of hypoglycemic episodes and anxiety levels was also observed. Statistically significant improvements were found across several QoL dimensions, including companionship, self-esteem, physical feeling, activity opportunity, and physical activity ability, with the most pronounced improvement seen in physical activity ability.
    CONCLUSION: This study identified the dynamic trajectories of QoL changes in a cohort of children and adolescents with T1D and screened potential determinants that enhance QoL. These insights are valuable for developing tailored, individualized diabetes management strategies aimed at improving long-term outcomes for T1D patients.
    Keywords:  Children and adolescents; China; Group-based trajectory modeling; Quality of life; Type 1 diabetes
    DOI:  https://doi.org/10.1007/s11136-025-04025-7
  19. J Basic Clin Physiol Pharmacol. 2025 Jul 17.
       OBJECTIVES: The effectiveness of diabetes management depends significantly on patients' knowledge of key concepts such as carbohydrate counting, bolus timing, duration of insulin action, and the interpretation of trend arrows. This study aims to evaluate the understanding of these concepts among patients with type 1 diabetes who are using advanced technologies.
    METHODS: From January 2024 to July 2024, consecutive patients with type 1 diabetes who met inclusion criteria were enrolled. Participants were asked to complete a questionnaire to assess their retention of key concepts for T1D management. Each patient completed the questionnaire independently in a private room before their medical appointment.
    RESULTS: This study evaluated therapeutic education in adult T1D patients in Campania, Italy, who use advanced diabetes technologies. Despite most patients having long-term diabetes, significant knowledge gaps were found in diabetes management. Only 40 % of CGM users correctly correlated sensor data with capillary glucose, and 19 % erroneously believed they were identical. Just 25 % patients knew their insulin-to-carbohydrate ratio, and only 56 % accurately calculated carbohydrates. Even among users of advanced hybrid closed-loop systems, similar deficiencies existed.
    CONCLUSIONS: Understanding of key concepts necessary for effective management of diabetes using advanced technologies remains insufficient in a cohort of Italian patients.
    Keywords:  AHCL; CGM; diabetes education; type 1 diabetes
    DOI:  https://doi.org/10.1515/jbcpp-2025-0115