bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2025–12–21
fourteen papers selected by
Mott Given



  1. Diabetes Ther. 2025 Dec 19.
      Continuous glucose monitoring (CGM) has transformed diabetes management by providing continuous, high-resolution insight into glucose dynamics. Initially developed for type 1 diabetes, CGM now demonstrates substantial clinical and behavioral benefits for individuals with type 2 diabetes across diverse therapeutic settings. This narrative review synthesizes current evidence on the expanding role of CGM in optimizing glycemic control and promoting patient-driven lifestyle modification.Across randomized and real-world studies, CGM consistently improves glycosylated hemoglobin, increases time in range, and reduces glycemic variability, regardless of insulin use. Beyond metabolic outcomes, CGM enhances treatment satisfaction, psychological well-being, and self-efficacy, particularly when combined with structured education and feedback. By enabling individuals to visualize real-time glucose responses to daily behaviors, CGM serves as a powerful catalyst for sustained behavioral change and personalized self-management.In addition to its therapeutic applications, CGM also provides diagnostic insight by revealing unrecognized glucose excursions that conventional monitoring may miss, facilitating earlier identification of dysglycemia in at-risk individuals. Yet significant barriers persist, including device costs, limited insurance coverage, and the difficulty of translating raw data into actionable insights for patients and clinicians.In conclusion, CGM has evolved from a glucose-monitoring device to a comprehensive platform that supports both clinical decision-making and behavioral empowerment, bridging the continuum from diabetes prevention to long-term management.
    Keywords:  Continuous glucose monitoring; Digital health; Glycemic control; Type 2 diabetes
    DOI:  https://doi.org/10.1007/s13300-025-01830-8
  2. Am J Obstet Gynecol MFM. 2025 Dec 17. pii: S2589-9333(25)00276-9. [Epub ahead of print] 101878
       BACKGROUND: Gestational diabetes mellitus (GDM) - a risk factor for adverse pregnancy outcomes - is on the rise. Real-time continuous glucose monitoring (RT-CGM) may enhance glucose control during GDM and thereby improve outcomes; however, more data are needed.
    OBJECTIVE: This study aimed to determine if RT-CGM improved glycemic indices in GDM.
    STUDY DESIGN: An open-label, randomized controlled trial was conducted with GDM patients diagnosed between 14 and 30 weeks estimated gestational age (EGA), assigning them either to RT-CGM or blinded CGM in addition to self-monitoring of blood glucose (SMBG). This analysis compares CGM metrics for the study groups at EGA of 32 and 36 weeks (+/- 10 days). The primary outcome was percentage of time in range 63-140 mg/dl (TIR) over 24 hours. Secondary outcomes included mean glucose over 10 days and additional CGM indices, HbA1c, diabetes medication usage, satisfaction with CGM, and maternal and fetal outcomes.
    RESULTS: 105 participants with GDM were enrolled (RT-CGM(n=53) or blinded CGM (n=52)) Thirty-one of 52 SMBG participants withdrew, with 30 citing desiring RT-CGM. In participants who completed the study, average EGA was 29.8 weeks (SD=2.5) on their first day of CGM wear with average duration of wear of 64.4 days (SD=19.4). TIR 63-140 mg/dl (TIR) was 93.0 (SD=6.7) and 93.7 (SD=6.8) (p=0.86) while mean glucose was 106.7 mg/dL (SD=9.0) and 98.1 mg/dL (SD=13.8) for the RT-CGM and SMBG groups (p =0.02), respectively. At study completion, mean glucose and TIR were similar. Insulin and/or metformin use was 66.7% in the RT-CGM group and 33.4% in the SMBG group (p=0.02). There were no significant differences in maternal or fetal outcomes. The RT-CGM group's satisfaction with CGM was high.
    CONCLUSIONS: In this study in which CGM was initiated at about 30 weeks EGA, TIR and mean glucose were similar. However, more participants in the CGM group initiated insulin. Selection and attrition bias could have affected the results. Glycemic changes were minor, but interest in CGM was high. Further research is needed to assess if earlier implementation and use in higher risk populations may provide benefit.
    DOI:  https://doi.org/10.1016/j.ajogmf.2025.101878
  3. BMC Geriatr. 2025 Dec 15. 25(1): 1021
       PURPOSE: The purpose of this study is to explore the acceptability and usability of continuous glucose monitoring (CGM) systems as experienced by older adults aged 75 years and older with diabetes.
    METHODS: Using a qualitative research design, data were collected through semi-structured interviews with 14 older adults aged 75 years and older with diabetes who had no prior experience with CGM, following two weeks of CGM use. Transcripts were analyzed using a thematic qualitative analysis method to identify key statements related to participants' experiences with CGM, with a focus on acceptability and usability.
    RESULTS: CGM was generally perceived as acceptable and useful by participants. Four key themes emerged from the analysis: Device-related burdens, barriers to CGM use, duality of CGM impact, and reflection and empowerment, along with 9 sub-themes. While CGM significantly enhanced glucose management awareness and promoted healthier lifestyle changes, it also induced psychological stress due to constant monitoring. Participants noted several barriers such as the inconvenience of carrying and charging a mobile device, complex device operations, and difficulties using educational materials due to visual impairments. The high cost of the CGM device was seen as a substantial economic barrier, underscoring the necessity for financial interventions like broader insurance coverage for individuals with type 2 diabetes.
    CONCLUSION: This study suggests that CGM may improve health outcomes for older adults aged 75 years and older with diabetes by enhancing both its acceptability and usability. It highlights the need for comprehensive technical, educational, and financial support to facilitate effective CGM usage in older adults aged 75 years and older with diabetes. Recommendations to improve usage include the adoption of wearable devices or dedicated receivers, extended battery life, user-friendly interfaces with larger fonts and clearer visual presentations, and enhanced insurance coverage.
    Keywords:  Aged; Continuous glucose monitoring; Diabetes mellitus; Patient acceptance of health care
    DOI:  https://doi.org/10.1186/s12877-025-06575-4
  4. Endocrinol Metab (Seoul). 2025 Dec 12.
       Background: Continuous glucose monitoring (CGM) is widely applied in daily glucose management. However, its potential to categorize individuals based on glucose profiles is not fully established. This study employed CGM-based patient clustering and examined nutritional factors influencing glucose patterns.
    Methods: This prospective observational study enrolled 34 individuals with diabetes. Retrospective professional CGM was conducted over 7 days, during which food intake was recorded. K-means clustering was performed using CGM-derived coefficient of variation (CV) and time in range. Macronutrient intake and its fluctuations were compared across clusters.
    Results: Participants were grouped into cluster 1 (well-controlled), cluster 2 (highest CV), and cluster 3 (highest mean glucose). Baseline clinical characteristics, daily energy intake (kcal), and macronutrient intake did not differ significantly among clusters. However, carbohydrate intake fluctuations were greater in cluster 3 (CV 41.0%±32.1%, standard deviation [SD] 502.1±363.4 kcal) than in cluster 1 (CV 21.9%±9.0%, SD 260.2±94.1 kcal) and cluster 2 (CV 19.2%±9.1%, SD 250.2±126.1 kcal) (P=0.123 for CV; P=0.024 for SD). The SD (kcal) of carbohydrate intake was positively correlated with mean glucose levels (rho=0.88, P=0.023).
    Conclusion: CGM enables categorization of individuals based on glucose profiles, and higher carbohydrate intake fluctuations are associated with poorer glycemic control. Personalized dietary strategies, particularly stabilizing carbohydrate intake, may support better glucose management in individuals with high mean glucose and low CV.
    Keywords:  Cluster analysis; Continuous glucose monitoring; Diabetes mellitus; Dietary patterns; Prognosis
    DOI:  https://doi.org/10.3803/EnM.2025.2486
  5. J Hepatobiliary Pancreat Sci. 2025 Dec 15.
       BACKGROUND: Continuous glucose monitoring (CGM) is increasingly used for glycemic control, but its role after total pancreatectomy (TP) in pancreatogenic diabetes mellitus (PDM) is understudied. This study evaluated postoperative CGM utility in this population.
    METHODS: Thirty-seven TP patients (2022-2024) at Seoul National University Hospital were grouped by CGM use (CGM users = 11) and analyzed for baseline and perioperative diabetes-related factors. In a preoperative non-diabetic subgroup (n = 10, CGM users = 6), pre- and postoperative hemoglobin A1c (HbA1c) was compared by CGM use. For consenting CGM users, changes in time in range (TIR), time above range (TAR), and time below range (TBR) from 1 to 3 months postoperatively were analyzed.
    RESULTS: CGM users had lower postoperative HbA1c than non-users overall (6.5% vs. 8.0%; p < 0.001) and in non-diabetics (6.0% vs. 7.4%; p = 0.002). Among 80% sharing CGM data, TIR increased from 62.6% at 1 month to 71.8% at 3 months (p = 0.035), TAR decreased from 36.3% to 26.6% (p = 0.037), and TBR was unchanged.
    CONCLUSIONS: Proactive CGM use may improve postoperative glycemic management in PDM after TP by increasing awareness of glycemic patterns, resulting in lower HbA1c and greater time in the target range.
    Keywords:  continuous glucose monitoring; diabetes mellitus; hyperglycemia; pancreatectomy
    DOI:  https://doi.org/10.1002/jhbp.70050
  6. Diabetes Res Clin Pract. 2025 Dec 12. pii: S0168-8227(25)01069-1. [Epub ahead of print] 113054
      In individuals with type 2 diabetes (T2D) on insulin, continuous glucose monitoring (CGM) provides feedback on intra- and inter-day glycaemic variations that helps tailor the insulin regimen and lifestyle choices, without the pain of multiple finger pricks. However, practical guidance on the use of CGM in this cohort is limited in Asia. In this case series-based review and expert opinion paper, we aim to provide expert guidance, through a case-based approach, on the use of CGM in people with T2D on insulin therapy, primarily in three profiles: (1) individuals with no comorbidities; (2) those with comorbid cardiovascular risk factors; and (3) elderly individuals with T2D on insulin. Five anonymised demonstrative real-world cases, including ambulatory glucose profiles, have been presented. The benefits of CGM in T2D management in each profile as well as supporting literature are discussed and ten key clinical practice points are proposed to aid in optimising the use of CGM for achieving glycaemic targets, adjusting insulin therapy, motivating adherence to lifestyle intervention, reducing the risk of, or minimising the duration of, hypoglycaemia, and improving the overall quality of life and well-being in this population.
    Keywords:  Continuous glucose monitoring; Expert opinion; Glucose monitoring; Insulin; Type 2 diabetes mellitus
    DOI:  https://doi.org/10.1016/j.diabres.2025.113054
  7. BMC Nephrol. 2025 Dec 18.
      Continuous glucose monitoring (CGM) has transformed diabetes management, offering real-time and dynamic insights into glucose variability and addressing the limitations of traditional glucose assessment methods. Kidney transplantation, the most common solid organ transplant, carries a considerable burden of post-transplant diabetes mellitus (PTDM), which is linked to increased cardiovascular events, graft dysfunction, and increased mortality. This review explores the role of CGM in kidney transplant recipients, particularly its impact on glycemic profiles and its predictive value for post-transplant diabetes mellitus (PTDM). At the time of this review, CGM had not yet been incorporated into standard transplant care protocols. Evidence shows that perioperative CGM outperforms traditional tests in identifying frequent hyperglycemia and glycemic variability in the first weeks after transplantation, enabling enhanced glycemic control and improving the recipient's clinical outcome. Studies demonstrate higher glucose variability in kidney only recipients compared to other organ recipients, and in type 2 diabetes patients compared to those with PTDM. Poor perioperative glycemic control and glycemic variability detected by CGM have been linked to acute rejection and reduced graft survival. CGM-derived metrics outperform conventional glucose measures in predicting PTDM. CGM metric thresholds within the first month post-transplant achieved sensitivities above 85% and specificities up to 83% for PTDM risk. CGM-guided adjustment of immunosuppressants and steroid dosing have been shown to reduce hyperglycemia and variability. Comparative studies indicate that glycosylated hemoglobin A1c correlates poorly with CGM in the early post-transplant period, often misclassifying patients as normoglycemic. CGM appears to offer clinically relevant insights for the early detection, prediction, and management of dysglycemia in kidney transplant recipients.
    Keywords:  CGM; Continuous glucose monitoring; Glycemic variability; Graft survival; Kidney transplantation; NODAT; New-onset diabetes after transplant; PTDM; Post-transplant diabetes mellitus; Renal transplantation
    DOI:  https://doi.org/10.1186/s12882-025-04691-2
  8. Prim Care Diabetes. 2025 Dec 12. pii: S1751-9918(25)00233-5. [Epub ahead of print]
       OBJECTIVE: This study evaluated the impact of real-time continuous glucose monitoring (CGM) combined with personalized digital health coaching on glycemic control and lifestyle behaviors in individuals with type 2 diabetes (T2DM) and prediabetes.
    METHOD: A prospective cohort study was conducted involving 110 participants recruited from a chronic disease management service. The participants underwent an 8-week intervention where CGM data were used to provide real-time feedback, complemented by personalized lifestyle coaching. Baseline and post-intervention data included fasting blood glucose (FBG), glycated hemoglobin (HbA1c), body mass index (BMI), and lifestyle factors such as physical activity and eating habits. Participants were divided into tertiles based on mean amplitude of glycemic excursion (MAGE) to evaluate the effects of the intervention by glycemic variability (GV) level.
    RESULTS: Significant improvements in glycemic control were observed across all tertiles. The highest GV group (T3) showed the greatest reductions in HbA1c (7.39 % to 6.82 %, p = 0.004) and FBG. The physical activity scores significantly increased in the T3 group (p = 0.005), and all tertiles reported healthier dietary habits following the intervention.
    CONCLUSIONS: The integration of CGM with personalized digital health coaching was associated with significant short-term improvements in glycemic control and lifestyle behaviors, particularly among individuals with high GV.
    Keywords:  Continuous Glucose Monitoring (CGM); Digital Health Coaching; Glycemic Control; Glycemic Variability (GV); Type 2 Diabetes Mellitus (T2DM)
    DOI:  https://doi.org/10.1016/j.pcd.2025.12.002
  9. Ann Appl Stat. 2025 Sep;19(3): 2105-2128
      With the growing prevalence of diabetes and the associated public health burden, it is crucial to identify modifiable factors that could improve patients' glycemic control. In this work, we seek to examine associations between medication usage, concurrent comorbidities, and glycemic control, utilizing data from continuous glucose monitors (CGMs). CGMs provide high-frequency interstitial glucose measurements, but reducing data to simple statistical summaries is common in clinical studies, resulting in substantial information loss. Recent advancements in the Fréchet regression framework allow to utilize more information by treating the full distributional representation of CGM data as the response, while sparsity regularization enables variable selection. However, the methodology does not scale to large datasets. Crucially, rigorous inference is not possible because the asymptotic behavior of the underlying estimates is unknown, while the application of resampling-based inference methods is computationally infeasible. We develop a new algorithm for sparse distributional regression by deriving a new explicit characterization of the gradient and Hessian of the underlying objective function, while also utilizing rotations on the sphere to perform feasible updates. The updated method is up to 10000+ fold faster than the original approach, opening the door for applying sparse distributional regression to large-scale datasets and enabling previously unattainable resampling-based inference. We combine our algorithm with stability selection to perform variable selection inference on CGM data from patients with type 2 diabetes and obstructive sleep apnea. We find a significant association between sulfonylurea medication and glucose variability without evidence of association with glucose mean. We also find that overnight oxygen desaturation variability has a stronger association with glucose regulation than overall oxygen desaturation levels.
    Keywords:  Diabetes; Fréchet regression; Gradient descent; Optimization; Sleep apnea; Stability selection
    DOI:  https://doi.org/10.1214/25-aoas2038
  10. J Family Med Prim Care. 2025 Nov;14(11): 4879-4882
       Background: Diabetes mellitus is a prevailing health concern in rural India, with its associated complications, notably diabetic foot ulcers, contributing to significant morbidity and mortality. This journal delves into the potential of continuous glucose monitoring (CGM) technology to revolutionize the management of diabetic foot complications within the context of rural India. The resource constraints and limited access to healthcare facilities prevalent in developing countries accentuate the challenges in diabetic foot care. This article highlights how CGM technology addresses these challenges by providing real-time glucose level insights to patients and healthcare providers alike.
    Description: Our 1st case is a 62-year-old male with a non-healing diabetic foot ulcer, complicated by severe sensorimotor neuropathy owing to suboptimal glycemic control. Our second patient is a 55-year-old male tailor with poorly controlled diabetes who developed a recurrent follicular abscess despite prior antibiotic therapy. Our 3rd case features a 46-year-old male farmer with uncontrolled diabetes and persistent tinea pedis. Despite multiple antifungal treatments, the infection persisted. By using CGM to monitor blood glucose levels, and adjusting the diet regimen, alongside antidiabetic therapy, all these patients recovered completely without any surgical interventions.
    Conclusion: These cases underscore the importance of CGM in achieving tight glycemic control, improving infection resolution, and enhancing patient well-being, particularly in cases where traditional approaches may have been insufficient.
    Keywords:  CGM; diabetes; diabetic foot
    DOI:  https://doi.org/10.4103/jfmpc.jfmpc_1961_24
  11. Diabetes Obes Metab. 2025 Dec 19.
       AIMS: Real-time continuous glucose monitoring (rtCGM) is crucial to diabetes management in type 1 diabetes (T1D), but its accuracy decreases during glucose fluctuations triggered by physical activity and exercise.
    MATERIALS AND METHODS: Twenty adults with T1D (9 females; age 50 ± 12 years; HbA1c 6.6 ± 0.5%) participated in this study, which included a 3-day lab phase where three group exercise sessions (each lasting 90 min) were performed, followed by a 4-day home phase. Participants were required to wear a Dexcom G7 (Dexcom), FreeStyle Libre 3 (Abbott), and Simplera (Medtronic) rtCGM simultaneously. From 8:00 AM (initial measurement) to 10:00 PM (final measurement), duplicate capillary blood glucose measurements were taken at 2-h intervals using the Contour Next One glucometer (Ascensia Diabetes Care) and recorded in addition to the actual displayed sensor glucose values. The performance of the rtCGM systems was evaluated by means of median absolute relative difference (MedARD) and interquartile range [IQR] against the reference blood glucose. Absolute relative differences (|ARD|) of the three rtCGMs were analysed using the Kruskal-Wallis test (p < 0.05).
    RESULTS: Overall, the MedARD [IQR] for Dexcom G7 was 8.4% [3.6-14.0] (723 comparison points), for Libre 3 7.5% [3.1-13.4] (723 comparison points), and Simplera 13.8% [6.9-22.5] (719 comparison points). No significant differences were found between Libre 3 versus Dexcom G7 (p = 0.35). A significant difference was found for Dexcom G7 versus Simplera and Libre 3 versus Simplera (p < 0.0001).
    CONCLUSIONS: Dexcom G7 and FreeStyle Libre 3 showed very high accuracy, which could not be found for the Simplera rtCGM system.
    CLINICAL REGISTRATION: German Clinical Trial Register, DRKS: DRKS00035836.
    DOI:  https://doi.org/10.1111/dom.70369
  12. JMIR Diabetes. 2025 Dec 15. 10 e75672
       Background: One in 4 Veterans who receive care through the Veterans Health Administration has type 2 diabetes (T2D). Dietary carbohydrate restriction can promote weight loss and improve blood glucose control, but Veterans taking certain medications (eg, insulin) may experience serious complications (eg, hypoglycemia) without adequate support and monitoring.
    Objective: This study aims to develop and evaluate the feasibility, acceptability, and clinical effectiveness of a pilot low-carbohydrate (LC) nutrition counseling program guided by continuous glucose monitoring (CGM) for Veterans with T2D receiving insulin (ie, LC-CGM).
    Methods: This is a pragmatic, nonrandomized, pre-post quality improvement pilot program. Eligible patients were Veterans with T2D who were prescribed ≥3 daily injections of insulin. The 24-week LC-CGM program consisted of virtual visits with a registered dietitian (RD) and clinical pharmacy practitioner (CPP); CGM data were used to guide tailored nutrition counseling and de-escalation or cessation of glucose-lowering medications. To evaluate changes from baseline, intention-to-treat analyses were conducted for all enrollees, with separate analyses for program completers. Primary outcomes were program feasibility and acceptability (ie, program enrollment and completion rates and mean number of RD and CPP visits). Secondary outcomes included mean weight change, percent weight loss, achievement of ≥5% and ≥10% weight loss, change in glucose-lowering medication use, and change in laboratory measures (eg, hemoglobin A1c [HbA1c]).
    Results: Program evaluation occurred from March 19, 2021, to May 3, 2024. Among 43 Veterans referred to the LC-CGM program, 38 (88%) enrolled. Most were men (37/38, 97%), white (29/38, 76%), with an average age of 63.7 (SD 9.6) years. Mean BMI and HbA1c were 38.1 (SD 5.8) kg/m2 and 7.8% (SD 1.3). Of 38 enrollees, 27 (71%) completed the program. Enrollees averaged 9.5 (SD 3.3) RD visits and 12.8 (SD 4.7) CPP visits. In intention-to-treat analyses, mean weight change was -11.5 kilograms (SD 8.7; 95% CI -14.4 to -8.6), corresponding to 9.5% weight loss (SD 7.2; 95% CI -14.9 to -4.2), with 58% (22/38) achieving ≥5% weight loss and 32% (12/38) achieving ≥10% weight loss. Overall, use of glucose-lowering medications decreased from 3.5 (SD 0.8) per patient at baseline to 2.4 (SD 0.9) per patient at 24 weeks (P<.001), with 72% (26/36) of Veterans discontinuing short-acting insulin and 50% (18/36; P<.001) discontinuing long-acting insulin. Use of glucagon-like peptide-1 receptor agonists increased from 39% (15/38) at baseline to 61% (23/38) at 24 weeks (P=.02). Among program completers (n=27), mean percent weight loss was -11.8% (SD 6.5) and median HbA1c decreased by 0.7% (95% CI -0.9 to -0.3; P=.001).
    Conclusions: This pilot program provides preliminary evidence that supports feasibility, acceptability, and clinical effectiveness among Veterans with T2D. Additional research is needed to rigorously test longer-term clinical and cost-effectiveness among a larger cohort of eligible Veterans.
    Keywords:  behavior change; cardiometabolic health; de-prescription; digital health; low carbohydrate dietary counseling; personalized health; type 2 diabetes; veterans
    DOI:  https://doi.org/10.2196/75672
  13. BMC Geriatr. 2025 Dec 15. 25(1): 1020
       BACKGROUND: Studies have shown high rates of hypoglycaemia among home-dwelling older people receiving home care services. Hypoglycaemia can lead to severe consequences and in worst case, death. Therefore, knowledge about the factors associated with the occurrence of hypoglycaemia in this patient group is important. This study aimed to investigate the associations between hypoglycaemia and relevant diabetes and age-related factors among individuals with diabetes aged ≥ 65 years who received home care services.
    METHODS: This prospective observational study included data from blinded continuous glucose monitoring to identify hypoglycaemia and glycaemic variability. Further, data from blood tests (HbA1c, serum creatinine), medication lists, and questionnaires on cognitive function, functional status with need of assistance, and nutritional status were collected. Data analysis was performed using Fisher's exact tests and unadjusted logistic regression analyses.
    RESULTS: In total, 56 individuals participated (52% men, median age 82 years). We identified a statistically significant association between hypoglycaemia and glycaemic variability (p < 0.001). All participants with a coefficient of variation (CV) ≥ 36% had undergone at least one hypoglycaemic event during the study period. Also, participants with CV ≥ 27% had higher risk of hypoglycaemia than those with CV < 27% (OR 5.3, 95% CI 1.6, 17.7). Among the 34 participants with HbA1c ≥ 53 mmol/mol, 32% experienced hypoglycaemia. In total, 93% were treated with medications that potentially interfered with the effect of their diabetes medications, and 64% were treated with medications that potentially affected their ability to detect symptoms of hypoglycaemia. The associations between hypoglycaemia and cognitive, functional, or nutritional status is uncertain due to limitations in sample size.
    CONCLUSIONS: This study highlights a significant association between glycaemic variability and hypoglycaemia among older home-dwelling adults with diabetes receiving home care services. The prevalence of drug-drug interactions raises concerns about diabetes treatment and emphasise the need for targeted interventions to improve safety and care for this vulnerable group of patients.
    Keywords:  Continuous glucose monitoring; Diabetes; Glycaemic variability; Home care; Hypoglycaemia; Older people; Polypharmacy
    DOI:  https://doi.org/10.1186/s12877-025-06732-9
  14. J Diabetes Investig. 2025 Dec 19.
       BACKGROUND: This study investigates the impact of glycemic variability on sudomotor dysfunction in type 2 diabetes mellitus.
    METHODS: A total of 206 type 2 diabetes mellitus patients and 34 healthy controls were included. Sweat function (SF) was assessed using electrochemical conductance of hands (HESC) and feet (FESC). Type 2 diabetes mellitus patients underwent continuous glucose monitoring (CGM), and blood glucose variability was analyzed using various metrics. Type 2 diabetes mellitus patients were classified into normal, abnormal, reversible, and persistent abnormal SF groups.
    RESULTS: In healthy controls, SF showed no circadian rhythm. Type 2 diabetes mellitus patients with abnormal SF had longer diabetes duration, higher glucose variability, and greater SF impairment (P < 0.05). The reversible group exhibited the largest SF fluctuations (~26 μS) and a significant correlation between glucose variability and SF (P < 0.05). Blood glucose levels of 5-10 mmol/L were associated with improved SF in this group.
    CONCLUSIONS: The findings suggest that greater glucose variability correlates with more severe peripheral nerve damage, and controlling blood glucose within 5-10 mmol/L may improve SF, offering insights for personalized treatment strategies in diabetic peripheral neuropathy (DPN) prevention.
    Keywords:  Diabetes; Diabetic peripheral neuropathy; Glucose variability; Sudomotor function
    DOI:  https://doi.org/10.1111/jdi.70211