Journal of Diabetes Science and Technology最新文献

{"title":"Adherence and Clinical Effectiveness of a Subcutaneous Insulin Clinical Decision Support Tool in Hospitalized Patients.","authors":"Benjamin Lalani, Mohammed S Abusamaan, Andrew P Demidowich, Mihail Zilbermint, Sudipa Sarkar, Nestoras Mathioudakis","doi":"10.1177/19322968261468379","DOIUrl":"10.1177/19322968261468379","url":null,"abstract":"<p><strong>Background: </strong>Inpatient hyperglycemia is common and associated with adverse outcomes. Subcutaneous insulin remains the mainstay of treatment for most non-critically ill patients, yet appropriate dosing is complex and prone to variation. Clinical decision support (CDS) tools may improve insulin prescribing, but few have been evaluated in real-world settings.</p><p><strong>Methods: </strong>We conducted a retrospective cohort study of adult inpatients with diabetes and hyperglycemia admitted to 2 academic medical centers between December 1, 2015, and July 30, 2018. We assessed uptake, effectiveness, and adherence to an optional subcutaneous insulin CDS tool embedded in the Epic electronic medical record (EMR). Propensity score matching with Crump trimming and 1:3 nearest-neighbor matching was used to compare glycemic outcomes between patients who used the tool within 24 hours of admission and matched controls.</p><p><strong>Results: </strong>Of 5485 eligible admissions, 662 (12.1%) involved tool use on day 1. Tool use was more common among patients with type 1 diabetes, chronic kidney disease, or higher baseline glucose and varied by diagnosis and provider type. Among matched patients (n = 1750), tool use was associated with greater odds of any euglycemia (70-180 mg/dL) on day 2 (75.1% vs 69.8%; odds ratio [OR] = 1.30, 95% CI = 1.04-1.63; <i>P</i> = .02). Mean glucose levels, hypoglycemia, and hyperglycemia did not differ significantly. Only 43.7% of patients for whom the tool was used received a total daily insulin dose within 20% of the user-selected dose.</p><p><strong>Conclusion: </strong>Use of an EMR-integrated insulin CDS tool was associated with modest glycemic improvements. Low adherence may have attenuated its clinical impact.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261468379"},"PeriodicalIF":4.9,"publicationDate":"2026-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13427947/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148630635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A First Exploratory Study of Glycemic Outcomes During Normobaric Hypoxia Simulating Moderate-Altitude Conditions in Men With Type 1 Diabetes Using Automated Insulin Delivery, With Biochemical Comparison to Healthy Individuals.","authors":"Łukasz Tota, Małgorzata Morawska-Tota, Sandra Mrozińska, Anna Juza, Katarzyna Cyranka, Tomasz Klupa, Bartłomiej Matejko","doi":"10.1177/19322968261464595","DOIUrl":"10.1177/19322968261464595","url":null,"abstract":"<p><strong>Background: </strong>Physical activity is essential in type 1 diabetes mellitus (T1DM) management, and hybrid closed-loop (HCL) insulin systems are now a preferred therapy. Data on the short-term metabolic effects of hypoxia remain limited.</p><p><strong>Methods: </strong>This study evaluated the MiniMed 780G (MM780G) system in 12 men with T1DM (mean age 40.2 ± 3.9 years; diabetes duration 22.3 ± 8.7 years; glycated hemoglobin 6.4 ± 0.6%) before, during, and after 48 hours of simulated normobaric hypoxia, with a secondary aim of comparing selected biochemical markers with 13 age- and body mass index-matched healthy men. All participants underwent a 48-hour exposure to normobaric hypoxia in a normobaric chamber, simulating an altitude of up to 3500 m a.s.l. while maintaining normal barometric pressure. A broad panel of endocrine, immunological, vascular, neurotrophic, gastrointestinal, and oxidative biomarkers was assessed to characterize whole-body adaptation to hypoxia.</p><p><strong>Results: </strong>Across the three study periods, a numerical difference was observed only for SD, which was higher after the test compared with the hypoxia period itself in this exploratory analysis. No significant differences were found in other glycemic indices, daily carbohydrate intake, total insulin delivery, or the proportion of insulin administered as boluses (borderline significance); however, all changes remained within recommended glycemic thresholds. Insulin-like growth factor 1 (IGF-1) levels, at both baseline and delta, tended to be higher in the T1DM group, while changes in E-selectin were more pronounced than in controls.</p><p><strong>Conclusions: </strong>In this exploratory study, 48-hour exposure to normobaric hypoxia simulating an altitude of 3500 m a.s.l. was not associated with statistically significant deterioration in glycemic control in men with well-controlled T1D treated with the MM780G system, with the exception of SD, suggesting that the recovery phase rather than the exposure period may represent the higher-risk window. However, this change did not translate into deviations from recommended glycemic ranges and warrants further investigation. Biomarker profiles revealed no significant differences in inflammation, stress response, or oxidative damage compared with healthy participants. Alterations in IGF-1 and E-selectin may indicate effective compensatory and adaptive mechanisms to moderate hypoxia in people with T1DM.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261464595"},"PeriodicalIF":4.9,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13420116/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148603477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"INSIGHT: Ingest and Standardize Glucose Harmonization Tool.","authors":"Ben Ehlert, Krish Shah, Dev Katarya, Yue Wu, Tao Wang, Michael P Snyder","doi":"10.1177/19322968261467778","DOIUrl":"10.1177/19322968261467778","url":null,"abstract":"<p><strong>Background: </strong>Publicly available continuous glucose monitoring (CGM) datasets are fragmented across schemas, limiting reuse, pooling, and machine learning development. Although large biobanks provide harmonized resources, many smaller CGM studies remain difficult to access because ingestion and standardization require substantial manual effort.</p><p><strong>Methods: </strong>We developed INSIGHT (Ingest and Standardize Glucose Harmonization Tool), an open-source large language model (LLM)-assisted harmonization pipeline that standardizes public CGM datasets into a minimal common schema: Subject_ID, Timestamp, and Glucose. INSIGHT combines deterministic rules with structured LLM assistance to identify CGM files, classify file roles, generate schema-specific read plans, normalize timestamps and glucose units, resolve subject identifiers, detect overlapping exports, merge outputs, and retain auditable JSON artifacts. We evaluated INSIGHT on 14 public CGM datasets with curated reference outputs using pre-specified training and held-out testing partitions. Performance was assessed using file-level precision/recall, subject recovery, temporal alignment, glucose fidelity, scalar CGM feature accuracy, and composite INSIGHT scores.</p><p><strong>Results: </strong>INSIGHT is open-source at https://github.com/benehlert/CGMHarmonization. Across 90 model-dataset evaluations spanning 9 model variants and 10 datasets, top configurations achieved near-perfect held-out harmonization fidelity. GPT-5.4 and Gemini 3.1 Pro Preview achieved mean INSIGHT scores of 0.990, with glucose mean absolute error (MAE) below 0.03 mg/dL and within 5 mg/dL agreement of 0.9996. Errors primarily reflected complex subject-timestamp recovery rather than glucose conversion, with failures concentrated in deeply nested datasets containing overlapping or co-located non-CGM exports.</p><p><strong>Conclusion: </strong>INSIGHT demonstrates that LLM-assisted code generation can generalize CGM harmonization across heterogeneous datasets while producing auditable loaders. By reducing reuse costs, INSIGHT complements curated repositories and supports large-scale pooled analyses and foundation model development for glycemic physiology.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261467778"},"PeriodicalIF":4.9,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13415626/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148603421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-World Walking Patterns From Wrist-Worn Wearables Predict Incident Type 2 Diabetes: A UK Biobank WatchWalk Study.","authors":"Carlota Lisset Toapanta Gaibor, Silvia Bellés Andreu, Stephen R Lord, Lloyd L Y Chan","doi":"10.1177/19322968261464535","DOIUrl":"10.1177/19322968261464535","url":null,"abstract":"<p><strong>Aims: </strong>Digital gait biomarkers derived from wearable devices may capture early functional changes relevant to type 2 diabetes (T2D) risk. We investigated the associations between real-world gait characteristics and incident T2D and their contribution to risk discrimination beyond established risk factors.</p><p><strong>Methods: </strong>We analysed data from 71 618 UK Biobank participants without diabetes at baseline who wore a wrist accelerometer for seven days. Multiple digital gait biomarkers capturing walking speed, quality and distribution patterns were derived. Incident T2D was ascertained from linked health records. Cox proportional hazards models were fitted, adjusting for traditional T2D risk factors. Model discrimination was assessed using Harrell's C-index.</p><p><strong>Results: </strong>During follow-up, 2577 participants (3.6%) developed T2D. Several digital gait biomarkers were significantly associated with T2D in minimally adjusted analyses, and of these, slower walking speed, shorter maximum walking bouts and lower daily running duration remained independently associated with higher T2D risk after multivariable adjustment. A streamlined model including digital gait biomarkers and established risk factors showed good discrimination (C-index 0.80), outperforming models based on traditional risk factors and step counts alone.</p><p><strong>Conclusions: </strong>In this large population-based cohort, real-world walking patterns measured using wrist-worn devices were independently associated with incident T2D and enabled more accurate identification of at-risk individuals. Digital gait biomarkers may reflect early metabolic and functional vulnerability preceding the clinical diagnosis of T2D and may facilitate risk stratification in clinical practice and prevention initiatives.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261464535"},"PeriodicalIF":4.9,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13415623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148603450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Glycemic Ratio Is a Superior Predictor of Mortality Compared With Stress Hyperglycemia Ratio in Critically Ill Patients.","authors":"James S Krinsley, Gregory Roberts, Jan Gunst, Jean-Charles Preiser, Peter R Rule, Guillermo Umpierrez, Irl B Hirsch","doi":"10.1177/19322968261464561","DOIUrl":"10.1177/19322968261464561","url":null,"abstract":"<p><strong>Background: </strong>The glycemic ratio (GR), defined as the ratio of mean intensive care unit (ICU) blood glucose (BG) to estimated preadmission BG (EPBG), may provide superior prognostic insight compared with the single admission snapshot represented by the stress hyperglycemia ratio (SHR, the ratio of ICU admission BG to EPAG).</p><p><strong>Methods: </strong>This retrospective study included 4148 patients treated in a university-affiliated medical-surgical ICU from 2019 to 2023 who had >4 ICU BG measurements and a glycated hemoglobin (HbA1c) measured at admission. We compared SHR and GR prognostic ability for mortality, analyzed across prespecified GR and SHR bands, and calculated observed:expected mortality ratios (OEMRs).</p><p><strong>Results: </strong>We observed a more sharply defined J-shaped relationship between GR and mortality compared with that generated by SHR. Mortality in the reference band of 0.8 to <1.0 for GR and SHR mortality was 7.5% vs 10.9%, respectively (<i>P</i> = .0087), and for the strata ≥1.4, mortality was 25.6% vs 20.5% (<i>P</i> = .0376). Compared with the reference band, GR < 0.8 and GR > 1.0 had higher OEMR (<i>P</i> < .0001 for each), but the OEMR for SHR <0.8 and >1.0 compared with the reference band was not significantly different.</p><p><strong>Conclusions: </strong>Glycemic ratio was superior to SHR as a predictor of mortality. This study demonstrates that a mean ICU BG level representing 80% to 100% of the patient's EPBG was associated with the lowest mortality rate in a heterogeneous cohort of critically ill patients. These results may inform current BG management strategies and should be considered when designing future interventional trials in the critically ill.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261464561"},"PeriodicalIF":4.9,"publicationDate":"2026-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13400703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148578836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in Glycemia Risk Index Over Time in Patients With Diabetes and Cancer Undergoing Remote Continuous Glucose Monitoring.","authors":"Deborah A Osafehinti, Sonali Thosani, Steven P Weitzman","doi":"10.1177/19322968261470745","DOIUrl":"10.1177/19322968261470745","url":null,"abstract":"<p><strong>Background: </strong>Continuous glucose monitoring (CGM) is increasingly used in patients with cancer, a population in whom HbA1c may be unreliable. The Glycemia Risk Index (GRI) is a CGM-derived measure integrating hypoglycemia and hyperglycemia risk. We evaluated trends in GRI and other CGM metrics among adults followed in a remote CGM (RCGM) clinic.</p><p><strong>Methods: </strong>Retrospective chart review of adults (≥18 years) with diabetes and cancer seen at a comprehensive cancer center in 2024. Eligible patients had ≥2 CGM assessments (≥1 RCGM) and a baseline glucose management indicator (GMI) or HbA1c ≥8.0%. Generalized linear mixed models examined the effects of visit sequence (time) and RCGM use on GRI, GMI, average glucose, time in range (TIR), time above range (TAR), and time below range (TBR). Pre-specified conservative and liberal noninferiority margins were applied to the remote-use effect.</p><p><strong>Results: </strong>Forty-two patients (mean age 60.2 ± 10.6 years; 95% type 2 diabetes) were included. At baseline, mean GRI was 70 ± 27, GMI 8.5% ± 1.1%, average glucose 214 ± 46 mg/dL, TIR 38% ± 21%, TAR 61% ± 21%, and TBR 1% ± 1%. Across sequential assessments, GRI, GMI, average glucose, and TAR decreased, whereas TIR increased (all <i>P</i> < .05). Remote CGM did not predict any glycemic outcome. Under liberal margins, RCGM was noninferior to nonremote review for GRI, GMI, TIR, and TAR, and noninferior for TBR under both conservative and liberal margins.</p><p><strong>Conclusions: </strong>Sequential CGM review was associated with improved glycemic quality in adults with diabetes and cancer. Remote CGM achieved glycemic outcomes comparable with nonremote review, supporting its use as a viable adjunct to in-person visits in the oncology setting.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261470745"},"PeriodicalIF":4.9,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13395960/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148578767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Piloting a Postdischarge Virtual Glucose Monitoring Program for Patients With Diabetic Foot Wound in a Safety-Net Health System.","authors":"Felona Gunawan, Blessing Johnny, Binsy Easow, Smitha Mathew, Jacqueline N McNulty, Kristie Adame, Kaely Jackson, Larry S Brown, Peter A Crisologo, Uma Gunasekaran","doi":"10.1177/19322968261469513","DOIUrl":"10.1177/19322968261469513","url":null,"abstract":"<p><strong>Background: </strong>Diabetic foot wounds disproportionately affect patients from ethnic minorities and lower-socioeconomic status, many of whom face barriers to accessing diabetes technology. To evaluate whether short-term virtual glucose monitoring (VGM) has the potential to improve clinical outcomes in this high-risk population, we implemented a pilot VGM program within a safety-net health system.</p><p><strong>Method: </strong>We enrolled 40 hospitalized patients with diabetic foot wounds into a 3-month postdischarge VGM program that included 2 clinic visits and remote glucose monitoring every 1 to 2 weeks. Clinical outcomes were compared with a retrospective preintervention cohort of 78 similar patients.</p><p><strong>Results: </strong>Although both groups had similar HgbA1c at diagnosis (VGM 10.6 ± 1.8% vs preintervention 11.1 ± 2.0%, <i>P</i> = .20), the HgbA1c at 3 to 6 months was lower in the VGM cohort (7.6 ± 1.1% vs 8.5 ± 2.0%, <i>P</i> < .01). Wound healing occurred more frequently in the VGM participants, with 68% achieving wound closure by 3-4 months versus only 47% in the preintervention cohort (<i>P</i> = .04). Nonsignificant reductions in emergency department visits and hospital readmissions for wound complications or hypoglycemia were observed in the VGM versus the preintervention cohort. The VGM program allowed for more timely and frequent opportunities to adjust diabetes medications and address social barriers to care.</p><p><strong>Conclusions: </strong>A short-term postdischarge VGM program has the potential to not only increase access to diabetes technology but also meaningfully improve clinical outcomes among patients with diabetic foot wounds in a safety-net health setting. Such program may offer a scalable strategy to reduce rates of complications and lower healthcare costs in a safety-net health system.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261469513"},"PeriodicalIF":4.9,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13388485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148536190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term Performance of a Dynamic Clinical Decision Support System for Intravenous Insulin Therapy: A Retrospective Cohort Study in Patients With and Without Diabetes.","authors":"Benjamin Lalani, Ruth Penno, Curt Bay, Atul Lalani","doi":"10.1177/19322968261467050","DOIUrl":"10.1177/19322968261467050","url":null,"abstract":"<p><strong>Objective: </strong>To report and analyze the long-term performance of Glucopilot, a clinical decision support system for intravenous (IV) insulin therapy.</p><p><strong>Methods: </strong>This retrospective cohort study included adult patients across 9 hospitals who received IV insulin guided by Glucopilot between August 18, 2020 and May 30, 2025. Admissions with fewer than 10 hours of IV insulin or insufficient glucose monitoring were excluded. Using point-of-care glucose data from the electronic health record, we evaluated time to euglycemia, time in glycemic ranges, and severe dysglycemic events, with subgroup analyses (eg, diabetes type, diabetic ketoacidosis, sepsis, and steroid use) and multivariable models to assess glycemic performance and factors associated with sustained euglycemia (ie, 100% time in euglycemia after initial attainment) and severe hyperglycemia (ie, ≥300 mg/dL).</p><p><strong>Results: </strong>There were 1239 admissions included. All patients presenting with hyperglycemia achieved euglycemia, with a median time to euglycemia of 174 minutes. Thereafter, median time in euglycemia was 96%, with 4% median time in hyperglycemia, and 0% median time in hypoglycemia. Sustained euglycemia was observed in 43.4% of admissions, and steroid use was not associated with reduced likelihood of achieving sustained euglycemia. Baseline glucose was strongly associated with time to euglycemia but not with subsequent time in euglycemia after attainment. Glycemic control was consistent across subgroups.</p><p><strong>Conclusions: </strong>Use of Glucopilot, an electronic medical record-integrated adaptive insulin dosing software, was associated with timely attainment of euglycemia and sustained glycemic control with a median of 0% time in hypoglycemia in real-world practice.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261467050"},"PeriodicalIF":4.9,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13388501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148536121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpreting Glucose Management Indicator and Point-of-Care Hemoglobin A1c Discrepancies in Pediatric Patients with Islet Autotransplantation and Hemoglobin A1c Under 6.5%: A Guide for TPIAT Providers.","authors":"Bella London, Lindsey Hornung, Deborah Elder, Siobhan Tellez","doi":"10.1177/19322968261465344","DOIUrl":"10.1177/19322968261465344","url":null,"abstract":"<p><strong>Background: </strong>Glucose management indicator (GMI) value is often used without a paired hemoglobin A1c (A1c) during telehealth encounters. There are known discrepancies between GMI and A1c that have the potential to influence decision-making regarding weaning off insulin in the post-total pancreatectomy with islet auto transplantation (TPIAT) population. Our objective was to compare point-of-care (POC) A1c with 14-day GMI levels, 1-year post-TPIAT, and to consider its impact on insulin management.</p><p><strong>Methods: </strong>We reviewed the medical records of 59 patients who underwent TPIAT surgery at Cincinnati Children's Hospital 1-year post-TPIAT. Patients who had a POC A1c result and continuous glucose monitoring (CGM) data 12 months post-TPIAT were included in this analysis and were stratified into 2 groups based on POC A1c above or below 6.5%.</p><p><strong>Results: </strong>A total of 33 patients, 1-year post-TPIAT, were included in this study. Median POC A1c was 6% (interquartile range [IQR] = 5.7 to 6.8), while median 14-day GMI was significantly higher at 6.5% (IQR = 6.2 to 6.8) (<i>P</i> < .0001). The GMI median was 0.5% (IQR = 0.3 to 0.7) higher in the POC A1c <6.5% group, compared to 0.0% (IQR: -0.2 to 0.1) in the POC A1c ≥6.5% group (<i>P</i> < .0001).</p><p><strong>Conclusion: </strong>Our data demonstrate a significant discordance between 14-day GMI and POC A1c values, particularly when A1c falls below 6.5%, in patients 1-year post-TPIAT. This threshold is critical for patients post-TPIAT, as an A1c of 6.5% or lower is commonly used to wean insulin therapy. Discordance in GMI at this level, if used independently, may therefore directly impact clinical decision-making regarding insulin management in this population.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261465344"},"PeriodicalIF":4.9,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13385151/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148520463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance, Safety and Usability of a Third-Generation Continuous Glucose Monitoring System in a Pediatric Population: Results From a Prospective, Multicenter Study.","authors":"Fengyun Wang, Frank Flacke, Shuxia Ding, Wenxian Oyang, Haiying Wu","doi":"10.1177/19322968261463536","DOIUrl":"10.1177/19322968261463536","url":null,"abstract":"<p><strong>Background: </strong>A proprietary continuous glucose monitoring (CGM) system that uses third-generation sensor technology has previously been shown to exhibit stable, single-digit mean absolute relative difference (MARD) and 15-day wear life in adults with diabetes.</p><p><strong>Method: </strong>This was a prospective, single-arm study of pediatric participants aged 2 to 17 years that were enrolled at 3 clinical centers. Participants wore 2 sensors, one on each side of the abdomen, and were randomized to assessment of device performance on days 1 and 2, days 7 to 9 or days 15 and 16. Device performance across a range of metrics was assessed by comparison with venous blood glucose values obtained using a laboratory reference device. Per-protocol results are reported for the sensor with the inferior MARD.</p><p><strong>Results: </strong>The per-protocol set comprised 75 participants, of whom 16 were aged 2 to 5 years. The overall MARD was 8.89%, and MARDs at days 1 and 2, 7 to 9 and 15 and 16 were 8.65%, 8.70% and 9.30%, respectively. DTS error grid analyses showed that 100.0% of data pairs fell in clinically acceptable zones A+B. True alarm rates for hypoglycemia and hyperglycemia were high, at 98.6% and 98.8%, respectively. Mean sensor wear life was 14.4 days, and participant/guardian assessments of sensor usability revealed high satisfaction with respect to system assembly, sensor insertion and overall comfort. No device-related or skin-related adverse events were reported.</p><p><strong>Conclusions: </strong>In a pediatric population, the novel CGM system demonstrated accurate and stable performance across its 15-day wear life and showed high usability.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261463536"},"PeriodicalIF":4.9,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13385147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148520496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}