bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–08–09
twenty-one papers selected by
Mott Given



  1. J Paediatr Child Health. 2026 Aug 04.
       AIM: Continuous glucose monitoring (CGM) has well-established benefits in Type 1 diabetes; however, evidence in paediatric Type 2 diabetes (T2D) remains limited, and CGM is not currently publicly funded for this group in Australia. This review aimed to evaluate the impact of CGM use in adolescents with T2D.
    METHODS: A systematic search of Ovid Medline, Embase, CINAHL and Emcare was conducted for studies published from database inception to 18 November 2025 that evaluated CGM use in children and adolescents with T2D. Outcomes included glycaemic measures (HbA1c and time in range [TIR]), patient-reported benefits and barriers and psychological outcomes.
    RESULTS: Of 1019 manuscripts identified, eight studies met inclusion criteria. Study designs were longitudinal or cross-sectional, with relatively small sample sizes (7-41 participants). Five studies assessed HbA1c and TIR, two demonstrating short-term improvements that were not consistently sustained over time. Reported benefits included improved lifestyle behaviours, greater ease of diabetes management and increased frequency of glucose monitoring. Common barriers were sensor adhesion issues, connectivity challenges and concerns regarding wearability. Psychological outcomes were variable across studies.
    CONCLUSIONS: CGM use in children and adolescents with T2D is associated with transient improvements in glycaemic control and perceived benefits in daily diabetes management; however, technical and usability barriers limit sustained effectiveness. Structured education for children and families is essential to overcome these barriers and optimise long-term outcomes. Current evidence supports consideration of CGM funding for children and adolescents with T2D in Australia, alongside implementation of education programs to maximise benefit.
    Keywords:  adolescents; children; continuous glucose monitoring; type 2 diabetes
    DOI:  https://doi.org/10.1111/jpc.70525
  2. Cureus. 2026 Jul;18(7): e112200
      Continuous glucose monitoring (CGM) measures interstitial glucose over time and is increasingly used beyond intensive insulin therapy in type 2 diabetes. In routine care, CGM is useful when pattern information can improve management, not simply because more glucose data are available. This structured narrative review summarizes evidence, device categories, over-the-counter (OTC) systems, equity considerations, and practical implementation for adults with type 2 diabetes who are not receiving intensive insulin therapy, with particular focus on non-insulin-treated adults and those treated with basal insulin without prandial insulin. In non-insulin-treated adults, CGM may help identify fasting or postprandial hyperglycemia, support lifestyle and adherence discussions, and clarify discordance between hemoglobin A1c (HbA1c) and daily glucose patterns, although evidence remains stronger for glycemic metrics than for long-term outcomes. In adults treated with basal insulin without prandial insulin, randomized trial evidence supports CGM for glycemic assessment and safer treatment review. Systems cleared by the US Food and Drug Administration (FDA) for OTC CGM use and consumer-facing glucose biosensors may increase access to glucose feedback, but intended use, diabetes-specific clinical evidence, and broader wellness use should be distinguished. This review presents a practical implementation framework that begins with patient selection, followed by education, structured interpretation of CGM data, and integration of findings into lifestyle counselling, medication review, and shared clinical decision-making while accounting for coverage, digital access, language-sensitive support, and safety risks. CGM should function as structured decision support, not passive surveillance or consumer data collection.
    Keywords:  ambulatory glucose profile; basal insulin; cgm; continuous glucose monitoring; diabetes technology; health equity; primary care implementation; type 2 diabetes
    DOI:  https://doi.org/10.7759/cureus.112200
  3. Br J Nurs. 2026 Aug 06. 35(15): 760-764
      As the global incidence of diabetes and its associated treatment costs rise, continuous glucose monitors (CGMs) constitute a valuable tool for patient self-monitoring. However, market dominance of a few well-known brands, predominantly in populations with type 1 diabetes, limits the adoption of more cost-effective alternatives that might offer improved clinical outcomes. To address this, an expert roundtable evaluated barriers to efficient CGM use, identifying challenges such as regional care board variations, lack of patient-centred prescribing and insufficient training for both patients and healthcare professionals (HCPs). The panel suggested implementing more individualised prescribing, such as accessible readers for elderly patients, and expanding HCP education. Moreover, more streamlined integration of CGM data into electronic health records would reduce admin burden, while helping to facilitate remote monitoring to encourage patient self-management. Individualised CGM prescription, alongside improved workflows for HCPs around prescribing and addressing patient queries, could significantly lower healthcare costs while improving diabetes care in the UK.
    Keywords:  Blood sugar; Continuous glucose monitor; Diabetes; Health care; Patient
    DOI:  https://doi.org/10.12968/bjon.2026.0316
  4. AIDS Patient Care STDS. 2026 Aug 05. 10872914261473699
      People with HIV (PWH) have an increased risk of diabetes, and glycemic markers may underestimate glycemic burden in this population. This study prospectively evaluated the accuracy of continuous glucose monitor (CGM) derived Glucose Management Indicator (GMI) compared with A1C and fructosamine in PWH with type 2 diabetes and assessed patient satisfaction with CGM use. In this prospective observational study conducted between September 2024 and September 2025, adults with HIV and type 2 diabetes were recruited from two outpatient clinics in New York City and followed for 12 weeks using a Dexcom G7 CGM. Participants were required to maintain ≥70% CGM active time. A1C and fructosamine were obtained at study completion. Agreement between GMI, A1C, and fructosamine-derived A1C was assessed using correlation analyses and Bland-Altman plots. Patient satisfaction was evaluated using a Likert-scale survey. Forty-eight participants completed the study. GMI demonstrated strong correlation with A1C (r = 0.84, p < 0.001) and moderate correlation with fructosamine-derived A1C (r = 0.77, p < 0.001). Bland-Altman analysis showed minimal bias between GMI and A1C (MD = -0.07%), but greater systematic and proportional bias between GMI and fructosamine (MD = 0.70%). CGM utilization was high, and most participants reported improved understanding of glucose patterns and increased confidence in diabetes self-management. In PWH and type 2 diabetes, CGM-derived GMI demonstrates strong agreement with A1C and less agreement with fructosamine. CGM use was feasible and well accepted, providing important insights into glycemic patterns. These findings support CGM as a valuable adjunct to traditional glycemic markers in PWH.
    Keywords:  HIV; continuous glucose monitoring; diabetes
    DOI:  https://doi.org/10.1177/10872914261473699
  5. Diabetes Care. 2026 Aug 06. pii: dc261042. [Epub ahead of print]
       OBJECTIVE: To investigate the link between continuous glucose monitoring (CGM) metrics and risk of severe hypoglycemia and diabetic ketoacidosis (DKA) in individuals of type 1 diabetes.
    RESEARCH DESIGN AND METHODS: We pooled individual-level data from 10 studies of type 1 diabetes. From a 14-day baseline period, we derived CGM metrics (time in range [TIR] 70-180 mg/dL, time above range [TAR], time below range [TBR], sensor mean glucose, SD, and percent coefficient of variation [%CV]) and CGM-defined hypo- and hyperglycemic episodes. We used Cox regression to evaluate associations with severe hypoglycemia and diabetic ketoacidosis, with and without adjustment for HbA1c.
    RESULTS: Among 1,550 participants, 65 severe hypoglycemia and 163 DKA events occurred over a median follow-up of 16 weeks. Higher TBR <70 and <54 mg/dL, SD, %CV, and CGM-defined hypoglycemic episodes were associated with greater risk of severe hypoglycemia independent of HbA1c (e.g., hazard ratio [HR] 1.52 [1.29-1.79] per 1-SD higher TBR <70). Lower TIR and higher mean glucose, SD, %CV, TAR, and hyperglycemic episodes were associated with higher DKA risk; these associations were attenuated after HbA1c adjustment, but TIR, sensor mean glucose, and SD remained statistically and clinically significant (e.g., HR 0.76, 95% CI 0.60-0.97 per 1-SD higher TIR).
    CONCLUSIONS: CGM hypoglycemic and glycemic variability metrics were associated with severe hypoglycemia risk independent of HbA1c, whereas TIR, mean glucose, and SD provided information for DKA risk beyond HbA1c. This supports the complementary value of CGM and HbA1c in risk assessment for severe hypoglycemia and DKA.
    DOI:  https://doi.org/10.2337/dc26-1042
  6. JAMA Intern Med. 2026 Aug 03.
       Importance: Continuous glucose monitoring (CGM), initially recommended primarily for people with type 1 diabetes, has rapidly expanded to patients with type 2 diabetes and, more recently, even to individuals without diabetes. This broadening use underscores the importance of critically examining the evidence supporting CGM across populations, clarifying where benefits are established, where they are modest, and where they remain uncertain.
    Observations: We reviewed systematic reviews and meta-analyses of randomized trials and clinical guidelines evaluating CGM use beyond type 1 diabetes, with particular attention to glycemic outcomes, hypoglycemia, patient-reported outcomes, and potential unintended consequences in nonpregnant adults. In adults with type 2 diabetes, evidence from randomized trials consistently demonstrated that CGM use was associated, on average, with a modest yet consistent reduction in hemoglobin A1c of approximately 0.3% compared with finger-stick monitoring or usual care; some patients benefited considerably more. Only limited and indirect evidence supported the adoption of CGM in people with type 2 diabetes not receiving glucose-lowering therapy or in those with prediabetes or obesity.
    Conclusions and Relevance: CGM should be deployed in response to a specific patient problem rather than as a default intervention. Deliberate, equitable deployment of CGM that is aligned with patient goals, clinical context, and system capacity will be necessary to ensure that those most likely to benefit are not left behind, while avoiding overuse in populations for whom benefit remains unproven.
    DOI:  https://doi.org/10.1001/jamainternmed.2026.2772
  7. Diabetes Ther. 2026 Aug 05.
       INTRODUCTION: Hypoglycemia is a common complication in people with type 2 diabetes mellitus (T2DM) treated with basal insulin, yet its true prevalence in real-world primary care remains underexplored. This study used blinded continuous glucose monitoring (CGM) to assess glycemic patterns in patients with T2DM on basal insulin-supported oral therapy (BOT) with insulin glargine 100 U/mL (Gla-100) in Spain.
    METHODS: GPDetect was a prospective, multicenter, observational study in adults with T2DM treated with Gla-100 for ≥ 6 months in primary care. Participants underwent 14 days of blinded CGM (FreeStyle Libre® Pro iQ®). The primary objective of the present study was to estimate the proportion of patients with T2DM treated with Gla-100 whose TBR (glucose < 70 mg/dL) exceeded the internationally recommended threshold of 4%. Secondary endpoints included time in range (TIR), time above range (TAR), episodes of clinically significant hypoglycemia (< 54 mg/dL), cognitive function (MMSE), and fear of hypoglycemia (EsHFS).
    RESULTS: Among 136 patients (mean age 69 years), 16.9% had TBR > 4%, with a higher prevalence at night (23.5%) than during the day (12.5%). Clinically significant hypoglycemia (< 54 mg/dL > 1%) occurred in 8.8% of patients. Hyperglycemia was common: 46.3% spent > 25% of the day between 181-250 mg/dL, and 28.7% spent time > 250 mg/dL. Only 55.9% achieved TIR ≥ 70%. Patients receiving SGLT2i had lower mean glucose and EsHFS scores. Cognitive impairment (MMSE < 23) was associated with longer hypoglycemia duration.
    CONCLUSIONS: Blinded CGM revealed a relevant burden of unrecognized hypoglycemia-particularly nocturnal-as well as daytime hyperglycemia in patients with T2DM treated with Gla-100 in primary care. These results support the clinical value of CGM in informing treatment decisions and improving individualized diabetes management.
    Keywords:  Continuous glucose monitoring; Hypoglycemia; Insulin glargine; Time below range; Type 2 diabetes mellitus
    DOI:  https://doi.org/10.1007/s13300-026-01903-2
  8. Diabetes Res Clin Pract. 2026 Aug 03. pii: S0168-8227(26)00391-8. [Epub ahead of print] 113471
       AIMS: Continuous glucose monitoring (CGM) is now standard of care for insulin-treated people with diabetes (PwD) and expanding to broader patient groups. Barriers to CGM-related training and awareness among healthcare professionals (HCPs) in different roles should be removed to allow broader access to CGM. We developed a role-based competency framework that stratifies CGM-related knowledge and skills for HCPs interacting with PwD who use CGM.
    METHODS: A multidisciplinary, international panel of CGM-experienced clinicians and diabetes educators developed the competence framework. Draft competencies were derived from published guidance, reviewed and refined, then organized into domains and mapped to four responsibility levels.
    RESULTS: The framework comprises four levels (awareness, competence, expertise, leadership) across the domains of system knowledge, clinical application, special situations and leadership. Levels are defined by a HCP's role rather than professional title. For each level, the framework specifies core knowledge, skills and appropriate referral strategies. The resulting structure helps to reduce implementation barriers and aligns level-specific training with defined clinical responsibilities and tailored referral pathways.
    CONCLUSIONS: This consensus-driven, role-oriented framework offers a pragmatic structure for CGM-related education by mapping competencies to different roles and skills, thus enabling HCPs to introduce CGM as a meaningful benefit for both themselves and PwD.
    Keywords:  Care models; Continuous glucose monitoring; Diabetes education; Diabetes technology; Healthcare professional roles
    DOI:  https://doi.org/10.1016/j.diabres.2026.113471
  9. Curr Diab Rep. 2026 Aug 06. pii: 24. [Epub ahead of print]26(1):
       PURPOSE OF REVIEW: Continuous glucose monitoring (CGM) has increasingly been incorporated into studies examining cognitive function in people with diabetes. This scoping review systematically maps how CGM has been applied in cognitive research among individuals with diabetes to characterize current methodological approaches, identify key knowledge gaps, and inform future research.
    RECENT FINDINGS: A scoping review was conducted following Arksey and O'Malley's framework. A systematic search of five electronic databases (PubMed, CINAHL, Cochrane Library, EMBASE, PsycINFO) was performed. Cognitive outcomes were extracted and mapped to the International Classification of Functioning, Disability and Health framework. Twenty-one studies met the inclusion criteria. CGM data completeness was consistently high, with 84-100% of expected CGM data captured, supporting the feasibility of intensive glucose monitoring in cognitive research in diabetes. Considerable heterogeneity was observed in cognitive domains and assessment tools. Most studies evaluated executive function, memory, and attention, whereas psychomotor, language, and perceived cognitive functions were less frequently assessed. More than 10 distinct instruments were used to assess memory and executive function. Across studies, similar cognitive domains were examined regardless of the specific CGM metrics employed. Research examining CGM and cognitive function in diabetes is characterized by substantial methodological variability in both CGM metrics and cognitive assessments. These findings underscore the need for greater standardization to improve cross-study comparability and to advance CGM-informed cognitive research, including the development of personalized interventions to support cognitive health through optimized glucose management in people with diabetes.
    Keywords:  Cognitive function; Continuous glucose monitoring; Diabetes; Scoping review
    DOI:  https://doi.org/10.1007/s11892-026-01638-1
  10. J Assoc Physicians India. 2026 Jun;74(6E): e39-e41
       BACKGROUND: Time in range (TIR) is now widely adopted as a metric in diabetes management, offering a dynamic improvement over HbA1c alone. However, TIR does not capture the clinically relevant burden of glucose oscillations-rhythmic, intrarange fluctuations that independently drive oxidative stress, endothelial dysfunction, and inflammation, even when mean glucose remains well-controlled.
    OBJECTIVE: We propose oscillatory burden as a measurable, actionable dimension of glycemic risk. This review synthesizes mechanistic and clinical evidence linking oscillations to vascular complications and outlines a conceptual oscillatory burden index (OBI) that combines amplitude and frequency metrics using continuous glucose monitoring (CGM) data.
    METHODS: We reviewed studies published from 2002 to 2024 examining postprandial and intraday glucose dynamics, oxidative and inflammatory biomarkers, endothelial dysfunction, and real-world CGM applications.
    RESULTS: Intermittent glucose swings increase mitochondrial ROS generation, activate NF-κB, and impair nitric oxide availability-mechanisms confirmed by translational studies. Patients with comparable TIR (70-80%) but high oscillatory burden showed 2-3 times higher CRP and ICAM-1 levels compared to low-burden peers (p < 0.05). Practical strategies-precision meal timing, low-GI diets, gut microbiota modulation, and advanced CGM-driven insulin titration-can reduce oscillatory burden by up to 30%.
    CONCLUSION: Achieving TIR must not mask hidden glucose instability. Integrating oscillatory metrics into routine practice, supported by modern CGM analytics and patient-specific coaching, offers a new frontier for protecting vascular health in diabetes.
    DOI:  https://doi.org/10.59556/japi.74.1501
  11. Am J Clin Nutr. 2026 Aug;pii: S0002-9165(26)00197-8. [Epub ahead of print]124(2): 101388
      
    DOI:  https://doi.org/10.1016/j.ajcnut.2026.101388
  12. Endocrine. 2026 Aug 03. pii: 248. [Epub ahead of print]91(1):
       AIM: Time in Tight Range (TITR) is physiologically closer to normoglycemia than time in range (TIR) and has been linked to microvascular risk. We aimed to evaluate associations of TITR with diabetic retinopathy (DR) and optical coherence tomography angiography (OCTA)-derived retinal parameters in adults with type 1 diabetes (T1D) and to compare its performance with TIR.
    METHODS: We retrospectively included adults with T1D who underwent continuous glucose monitoring (CGM) and OCTA. TITR-DR associations were tested using multivariable logistic regression with restricted cubic splines. Linear mixed-effects models assessed TITR/TIR associations with OCTA-derived parameters, followed by exploratory threshold-based comparisons. DR discrimination of TITR versus TIR was assessed using ROC analysis.
    RESULTS: We analyzed 259,568 glucose readings from 153 participants. Each 10-percentage-point increase in TITR was associated with 29.5% lower odds of DR (adjusted OR 0.705; p = 0.004), without evidence of nonlinearity. In continuous analyses, both TITR and TIR were positively associated with deep vascular complex (DVC) vessel density and perfusion area; in exploratory threshold-based analyses, the TITR 50% cutoff showed significant DVC differences, whereas the TIR 70% cutoff showed no consistent differences. DR discrimination was similar for TITR and TIR (p = 0.635), whereas TITR was more closely related to hypoglycemia exposure (p < 0.01).
    CONCLUSIONS: Higher TITR was associated with lower odds of DR and more favorable DVC vessel density and perfusion area in hospitalized adults with T1D. TITR showed DR discrimination comparable to TIR but may provide complementary information on hypoglycemia exposure and DVC differences in threshold-based analyses.
    Keywords:  Continuous Glucose Monitoring; Diabetic Retinopathy; Optical Coherence Tomography Angiography; Time in Range; Time in Tight Range; Type 1 Diabetes Mellitus
    DOI:  https://doi.org/10.1007/s12020-026-04735-z
  13. Front Endocrinol (Lausanne). 2026 ;17 1884596
       Background: The rising prevalence of early-onset type 2 diabetes (T2DM) has become a major public health concern, with these patients facing a particularly high risk of early diabetic kidney disease (DKD). Although continuous glucose monitoring (CGM)-derived metrics have shown promise in predicting complications in later-onset T2DM, their utility in early-onset T2DM, a more aggressive phenotype characterized by rapid β-cell decline and heightened complication risk, remains unclear. Moreover, the relationship between glycemic variability and renal injury, as well as the mechanisms underlying the associations between CGM metrics and DKD, have not been fully elucidated. This study aimed to evaluate the associations of time in range (TIR), coefficient of variation (CV), and glycemic risk index (GRI) with early DKD in Chinese patients with early-onset T2DM, and to explore the potential mediating role of triglycerides.
    Methods: This cross-sectional study included 810 individuals with early-onset T2DM, defined as diagnosis before age 40. All participants underwent ≥7 days of CGM. Early DKD was defined as a urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g with an estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73m². Multivariable logistic regression, restricted cubic splines, and mediation analysis were used to evaluate independent associations, nonlinear relationships, and the mediating role of triglycerides (TG), respectively.
    Results: Among the participants, 183 (22.59%) had early DKD. After full adjustment including HbA1c, higher TIR was associated with lower odds of early DKD (per 1% increase: OR 0.99, 95% CI 0.98-0.99, P < 0.001), whereas higher GRI was associated with increased odds (per 1-unit increase: OR 1.01, 95% CI 1.01-1.02, P < 0.001). A U-shaped relationship was observed between CV and early DKD risk, with the nadir observed at approximately 20-30% CV. In mediation analysis, TG statistically accounted for 13.01% of the association between TIR and early DKD, and 11.92% of the association between GRI and early DKD.
    Conclusions: In Chinese patients with early-onset T2DM, CGM-derived metrics are independently associated with early DKD, with TIR and GRI showing opposite associations and CV exhibiting a U-shaped relationship. The observed association involving triglycerides suggests that lipid metabolism may be a correlate of glycemic control in relation to renal injury. These findings support a multidimensional strategy integrating glucose control, glycemic stability, and lipid management for renal protection in this high-risk population.
    Keywords:  continuous glucose monitoring; diabetes mellitus; diabetic nephropathies; early-onset; mediation analysis; type 2
    DOI:  https://doi.org/10.3389/fendo.2026.1884596
  14. J Diabetes. 2026 Aug;18(8): e70260
       BACKGROUND: The combined prognostic value of continuous glucose monitoring (CGM) metrics and circulating glucose biomarkers for predicting mortality in type 2 diabetes has not been fully established, particularly regarding residual risk in patients achieving glycemic targets.
    METHODS: This cohort study included 3677 patients with type 2 diabetes for a median of 7.4 years follow-up. Cox proportional hazards models evaluated the associations of baseline CGM-derived time in range (TIR) (target 70%) and serum 1,5-anhydroglucitol (1,5-AG) (threshold 6.0 μg/mL) with all-cause and cardiovascular mortality in the overall population. We further examined the relationship between 1,5-AG and mortality within TIR subgroups and compared its performance with metrics of glycemic variability derived from CGM.
    RESULTS: During follow-up, 522 all-cause deaths and 181 cardiovascular deaths occurred. TIR and 1,5-AG were moderately correlated and independently predicted mortality, with concurrent low TIR (≤ 70%) and low 1,5-AG (< 6.0 μg/mL) yielding the highest risk (hazard ratio [HR] 1.82, 95% CI 1.40-2.37). In stratified analyses, reduced 1,5-AG was significantly associated with increased mortality risk in patients with TIR > 70% (HR 1.69, 95% CI 1.25-2.28), whereas no significant association was observed in those with TIR ≤ 70%. Adding 1,5-AG improved traditional risk prediction in the former subgroup. Compared with 1,5-AG, CGM-derived glycemic variability indices such as mean amplitude of glycemic excursions, coefficient of variation, and standard deviation of glucose showed no significant association with mortality.
    CONCLUSIONS: TIR and serum 1,5-AG offer independent and complementary value, with low 1,5-AG identifying residual mortality risk despite achieving TIR targets.
    Keywords:  1,5‐anhydroglucitol; all‐cause mortality; continuous glucose monitoring; time in range; type 2 diabetes
    DOI:  https://doi.org/10.1111/1753-0407.70260
  15. J Med Internet Res. 2026 Jul 31. 28 e98519
       Background: Continuous glucose monitoring (CGM) is central to diabetes care, but explaining CGM patterns consistently and empathetically remains time-intensive in clinical practice. Large language model (LLM)-based systems may support patient-facing interpretation of CGM data, but evidence remains limited for retrieval-grounded tools evaluated against clinician-authored responses in counseling scenarios. The system was intended for CGM interpretation and communication support rather than autonomous therapeutic decision-making.
    Objective: This study aimed to evaluate whether a retrieval-grounded LLM-based conversational agent (CA) could support patient understanding of CGM data and preparation for diabetes consultations by generating responses to questions arising during CGM-informed diabetes counseling, with quality comparable to clinician-authored responses.
    Methods: We developed a scaffolded LLM-based CA for CGM interpretation and diabetes counseling support. The system was designed to provide plain-language explanations of CGM patterns and responses to diabetes management questions while avoiding directive or individualized medical advice, such as recommending medication initiation, dose adjustment, or regimen changes. Around 12 CGM-informed cases, each comprising a deidentified CGM trace, a synthetic patient vignette, and accompanying CGM visual materials, were constructed from using available clinical datasets. Between October 2025 and February 2026, 6 senior UK diabetes clinicians each reviewed 2 assigned cases and answered 24 questions (12 per case). In a source-masked multirater evaluation, each CA-generated and clinician-authored response was independently rated by 3 clinicians on 6 quality dimensions, including clinical accuracy, guideline adherence, actionability, personalization, communication clarity, and empathy. Safety flags and perceived source labels were also recorded. The primary analysis used linear mixed effects models with random intercepts for case and rater.
    Results: A total of 288 unique responses (144 CA and 144 clinician responses) were evaluated, generating 864 ratings. CA-generated responses received higher quality scores than clinician-authored responses under controlled vignette-based conditions, with mean scores of 4.37 (SD 0.57) versus 3.58 (SD 0.90) and an estimated mean difference of 0.782 points on a 5-point scale (95% CI 0.692-0.872; P<.001). This pattern was observed across all 6 categories of patient questions. The largest estimated differences were for empathy (mean difference 1.062, 95% CI 0.948-1.177) and actionability (0.992, 95% CI 0.877-1.106). Safety flag distributions were similar between CA and clinician responses, with major concerns rare in both groups (n=3, 0.7% each). Although CA responses were longer, additional analyses adjusting for word count did not indicate that response length explained the overall quality difference.
    Conclusions: Scaffolded LLM-based systems may have value as adjunct tools for CGM review, patient education, and preconsultation preparation by supporting standardized explanatory tasks. However, these findings should be interpreted in light of the vignette-based design, restricted datasets, and a small clinician panel, and they do not establish suitability for autonomous therapeutic decision-making, medication adjustment, or unsupervised real-world use. Prospective validation in clinical workflows is needed before implementation.
    Keywords:  clinical evaluation; continuous glucose monitoring; conversational agent; diabetes care; large language model; patient-facing AI; retrieval augmented generation
    DOI:  https://doi.org/10.2196/98519
  16. J Assoc Physicians India. 2026 Jul;74(7): 70-72
      One of the global epicenters of the diabetes mellitus pandemic is India. Over the past 40 years, there has been a sharp rise in the prevalence of diabetes mellitus in India due to rapid socioeconomic development, demographic shifts, and increasing susceptibility in the Indian population. Diabetes affects 74.2 million individuals in India, which places a significant strain on the country's economy and healthcare system. A patient's diet, lifestyle, medication, and glucose monitoring must all be customized for optimal diabetes control. The rates of glucose monitoring in India are abysmal. Most of the monitoring methods currently in use are based on single-point-in-time readings, which may not be totally indicative of the state of diabetes control. This presents problems. With advancements in technology, the new monitoring tool-continuous glucose monitoring (CGM)-provides visibility into the glycemic profile 24 × 7 with user-friendly reports that provide information much beyond glycated hemoglobin (HbA1c) and self-monitoring of blood glucose. This device also detects the time spent in range by the individual with diabetes. This review article discusses CGM in terms of its purposes, technologies, accuracy, clinical indications, benefits, and problems associated with it.
    DOI:  https://doi.org/10.59556/japi.74.1615
  17. Nephrol Dial Transplant. 2026 Aug 03. pii: gfag168. [Epub ahead of print]
       AIMS: To compare biochemical risk factors for cardiovascular disease (CVD) in kidney transplant recipients (KTx) with type 1 diabetes (T1D) who used continuous glucose monitoring (CGM) devices or underwent simultaneous kidney and pancreas (SPK) transplantation during long-term follow-up.
    MATERIALS AND METHODS: 22 graft recipients with T1D using CGM (KTx CGM) and 22 patients with T1D after SPK were included in the study. Study groups were matched for age and diabetes duration at the time of transplantation, age at the time of the study, sex, body mass index (BMI), total duration of dialysis therapy, dialysis modality, pretransplant CVD, and rates of kidney re-transplantation. Biochemical markers of glycemic control and risk for CVD were assessed over a 9-11 year follow up period.
    RESULTS: Fasting plasma glucose (FPG) and HbA1c were higher in the KTx CGM versus SPK group (6.5 [4.9; 7.8] vs 4.7 [4.4; 5.6] mmol/L, p<0.01, and 6.7 [5.9; 7.5] vs 5.2 [5.1; 5.4]%, p<0.001, respectively). Total cholesterol (TC) and high-density lipoprotein (HDL) did not differ between groups. Low-density lipoprotein (LDL) concentrations were lower in the KTx CGM vs the SPK group (2.35 ± 0.66 vs 2.96 ± 1.13 mmol/L, p=0.056). Triglyceride values were higher in the KTx CGM vs SPK group (1.29 ± 0.45 mmol/L vs 1.02 ± 0.39 mmo/L, p<0.05). Serum creatinine was higher (122.7 μmol/L vs 87.2 μmol/L, p< 0.01), and estimated glomerular filtration rates (eGFR) were lower (73.8 ± 25.0 vs 51.3 ± 18.6 ml/min.1.73 m2, p< 0.01) in the KTx CGM vs the SPK group.
    CONCLUSIONS: Application of CGM technology in kidney graft recipients with T1D enabled good control of glucose levels and allowed for normalization of a number of biochemical risk factors for CVD. Pancreas transplantation remains the optimal procedure in achieving physiological blood glucose levels in T1D kidney recipients.
    DOI:  https://doi.org/10.1093/ndt/gfag168
  18. Front Endocrinol (Lausanne). 2026 ;17 1933440
      
    Keywords:  clinical decision support; continuous glucose monitoring; diabetes mellitus; digital health; implementation science; machine learning; telemedicine
    DOI:  https://doi.org/10.3389/fendo.2026.1933440
  19. Prim Care Diabetes. 2026 Aug 07. pii: S1751-9918(26)00146-4. [Epub ahead of print]
      The aim of this study was to evaluate the long-term effectiveness of the FreeStyle Libre 2 device in reducing time below range levels 1 (TBR-1) and 2 (TBR-2), compared with the first-generation FreeStyle Libre device without alarms, in people with type 1 diabetes mellitus. A longitudinal observational pre-post study of a single cohort was conducted in a cohort of 93 people with type 1 diabetes mellitus who switched from FreeStyle Libre to FreeStyle Libre 2 in routine clinical practice. At 24 months post-switch, significant improvements were observed in TBR-1 (p = 0.001) and TBR-2 (p < 0.001). A significant direct association was identified between years with diabetes mellitus and change in total basal insulin dose from T0 to T1, with a coefficient of 0.14. Additionally, a significant inverse association was found between annual income and coefficient of variation, with a coefficient of -6.3, as well as between annual income and TBR-2, with a coefficient of -2.45. Switching to a flash glucose monitoring system with alarms was associated with improvements at 24 months in time below range, coefficient of variation, and HbA1c in individuals with type 1 diabetes mellitus.
    Keywords:  Continuous glucose monitoring; Glycaemic control; Real-world evidence; Type 1 diabetes
    DOI:  https://doi.org/10.1016/j.pcd.2026.07.014
  20. Cochrane Database Syst Rev. 2026 Aug 06. 8 CD016263
       RATIONALE: Evidence guiding how often adults with type 1 diabetes mellitus should self-monitor blood glucose, when to monitor, and which glycaemic targets to use is limited and inconsistent. The available research has not clearly linked different self-monitoring strategies to meaningful clinical outcomes, and evidence is particularly scarce for low-resource settings. Clarifying these uncertainties is important to support informed decision-making and equitable diabetes care worldwide.
    OBJECTIVES: To assess the effects of different timing, frequency, and glycaemic target values for self-monitoring of blood glucose (SMBG) in adults with type 1 diabetes mellitus.
    SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Science Citation Index Expanded and Emerging Sources Citation Index (Web of Science), ClinicalTrials.gov, and the WHO ICTRP, without language restrictions. The date of the last search across all databases was 7 January 2026.
    ELIGIBILITY CRITERIA: We included randomised controlled trials and eligible non-randomised comparative studies with a minimum duration of 24 weeks that evaluated different timing, frequency, or glycaemic target values for SMBG in adults with type 1 diabetes mellitus. We excluded cross-over and cluster-randomised trials, modelling studies, studies of pregnant individuals, and studies focused solely on self-monitoring in the context of insulin pump use.
    OUTCOMES: Our critical outcomes were glycaemic control (haemoglobin A1c and fasting blood glucose), hypoglycaemia (mild or moderate, severe, and nocturnal), diabetic ketoacidosis, microvascular and macrovascular complications, and quality of life.
    RISK OF BIAS: We assessed the risk of bias in included studies using the Cochrane RoB 2 tool for randomised controlled trials and the ROBINS-I tool for non-randomised comparative studies.
    SYNTHESIS METHODS: We did not conduct a meta-analysis, as effect measures and outcome reporting varied across the included studies and only three studies met the eligibility criteria. Instead, we followed Cochrane guidance on Synthesis Without Meta-analysis (SWiM) and summarised findings through structured tabulation of study characteristics and results, complemented by visual presentation of individual study effect estimates without statistical pooling. We did not use vote counting based on statistical significance. We assessed the certainty of the evidence using GRADE.
    INCLUDED STUDIES: We included three studies conducted in Europe and North America, involving a total of 16,481 adults with type 1 diabetes mellitus. One study was a randomised controlled trial, and two studies were observational comparative studies. All studies evaluated the frequency of SMBG; none reported eligible data on timing or glycaemic target values. Follow-up durations ranged from 9 to 24 months.
    SYNTHESIS OF RESULTS: Timing of SMBG No eligible studies investigating the timing of SMBG were identified. Frequency of SMBG Three studies involving a total of 16,481 adults investigated the frequency of SMBG in adults with type 1 diabetes mellitus. Overall, more frequent self-monitoring may be associated with lower haemoglobin A1c levels, although the evidence is very uncertain. In the randomised controlled trial (123 participants), the mean change in haemoglobin A1c at nine months was -0.43% in the intervention group compared with +0.23% in the control group, corresponding to approximately 0.7% lower haemoglobin A1c with more structured and frequent monitoring (mean difference (MD) -0.66, 95% confidence interval (CI) -0.94 to -0.38). The certainty of the evidence for this outcome was very low. In one observational study (1159 participants), adherence to self-monitoring guidelines may be associated with a 1.0% lower adjusted mean haemoglobin A1c (MD -1.00, 95% CI -1.21 to -0.79) compared with non-adherence. The third study (15,199 participants) reported lower haemoglobin A1c values with increasing monitoring frequency (P < 0.001), with the lowest values among those monitoring more than six times per day. Across both studies, the certainty of the evidence was very low. No included study reported effects on hypoglycaemia, diabetic ketoacidosis, microvascular or macrovascular complications, or quality of life. Glycaemic target values for SMBG No eligible studies investigating glycaemic target values for SMBG were identified.
    AUTHORS' CONCLUSIONS: No studies evaluated different timings of self-monitoring or different glycaemic target values. Three studies (one randomised controlled trial and two observational studies) assessed the frequency of self-monitoring and haemoglobin A1c. More frequent self-monitoring may be associated with lower haemoglobin A1c, although the evidence is sparse, frequency categories were inconsistent across studies, and the included studies had methodological limitations. The certainty of the evidence was very low for all outcomes, driven by risk of bias, imprecision, and inconsistency across studies. No studies reported hypoglycaemia, diabetic ketoacidosis, quality of life, or other critical outcomes. The evidence is insufficient to draw any firm conclusions about the effects of different self-monitoring strategies in adults with type 1 diabetes mellitus.
    FUNDING: This review was funded by the World Health Organization through an Agreement for Performance of Work (APW 203512799).
    REGISTRATION: The review was registered in PROSPERO (CRD42025639736) in February 2025.
    DOI:  https://doi.org/10.1002/14651858.CD016263