Yushi Hirota

Aim: The use of automated insulin delivery systems, including the MiniMed™ 780G advanced hybrid closed‐loop system, has been shown to improve glycemic management in people with type 1 diabetes (T1D). The aim was to assess the cost‐effectiveness of the MiniMed 780G system versus multiple daily injections (MDI) of insulin in combination with continuous glucose monitoring (CGM) in the management of people with T1D with elevated HbA1c levels in Japan. Methods: Modeling was performed using the IQVIA Core Diabetes Model and clinical input data were sourced from a randomized controlled trial. A time horizon of 55 years, a discount rate of 2.0% per annum, and a payer perspective were used. Sensitivity analyses were used to examine the robustness of base‐case results. Results: In the base‐case, an incremental cost‐effectiveness ratio (ICER) of JPY 4,723,991 per quality‐adjusted life year (QALY) gained was found, with an incremental benefit of 2.83 quality‐adjusted life years with the MiniMed 780G system versus MDI + CGM. The MiniMed 780G system was therefore cost‐effective, assuming a willingness‐to‐pay threshold of JPY 5,000,000 per QALY. Although treatment costs were found to be JPY 16,226,167 higher for the MiniMed 780G, costs associated with managing long‐term complications were lower. A probabilistic sensitivity analysis found the intervention to have a 76.9% probability of being cost‐effective in Japan. Conclusion: The MiniMed 780G system was projected to be cost‐effective in the management of people with T1D in Japan with HbA1c above target levels. Its use was also predicted to improve clinical outcomes when compared with MDI + CGM.

Aims/Introduction: Sensor‐augmented pump (SAP) therapy has evolved sequentially, but long‐term clinical evidence supporting these advances has remained limited. We here evaluated the impact of updates to SAP therapy on glycemic outcomes in individuals with type 1 diabetes. Methods: This retrospective observational study (SAP‐J T1D) included Japanese individuals with type 1 diabetes receiving SAP therapy. Treatment efficacy of the MiniMed 620G, 640G, and 770G systems (Medtronic) was evaluated at three predefined time points: baseline (before the switch from 620G to 640G), before the switch from 640G to 770G, and 1 year after the switch to 770G. The primary outcome was the change in time in range (TIR) for continuous glucose monitoring from baseline to 1 year after the transition to the MiniMed 770G system. Results: A total of 47 participants were included in the analysis. The median age was 45 years (interquartile range, 33–56 years), and the median body mass index was 22.3 kg/m ² (20.4–23.7 kg/m ² ). TIR increased progressively with each system update, from 69.0% (61.5–75.5%) with MiniMed 620G, to 72.0% (63.5–79.0%) with MiniMed 640G, and to 77.0% (73.0–80.5%) with MiniMed 770G. Time below range decreased after the switch to MiniMed 640G, whereas time above range decreased after that to MiniMed 770G. Time in tight range increased after the transition to the MiniMed 770G system. Conclusions: Sequential updates in SAP therapy were associated with stepwise improvements in glycemic management, reflecting the distinct functional characteristics of each system.

Aims/Introduction: Maturity‐onset diabetes of the young (MODY) accounts for at least 1%–5% of diabetes cases and is usually caused by single gene variants. Accurate diagnosis of MODY is important for effective management, especially in young individuals who are lean and lack islet autoantibodies. Only a few MODY cases associated with multiple gene variants have been reported. We here describe a rare case of MODY with a pathogenic HNF1A variant and a coexisting NEUROD1 variant. Materials and Methods: We conducted an extensive clinical analysis and explored the complex genetic architecture of the case in order to provide insight into the etiology of MODY. The candidate variants were identified by comprehensive whole‐exome and Sanger sequencing, and their functional impact was assessed by analysis of their effects on the surface charge or structural stability of HNF1A and NEUROD1. Results: The proband, a 21‐year‐old woman with early‐onset diabetes, was found to harbor a pathogenic HNF1A p.Arg159Trp variant and a coexisting NEUROD1 p.Arg98Ser variant of uncertain significance. The NEUROD1 variant was also present in her mother and sister, both of whom manifested impaired glucose tolerance, but was absent in her father and brother. Structural analyses suggested that the HNF1A variant alters the surface charge of the protein, whereas the NEUROD1 variant may affect protein structural stability. Conclusion: We have identified an unusual case of MODY with a pathogenic HNF1A variant and a coexisting NEUROD1 variant of uncertain significance, and structural analyses suggested that the NEUROD1 variant may affect protein structure.

Background: Immune checkpoint inhibitor (ICI)-induced diabetes is a rare endocrine immune-related adverse event, and long-term pancreatic magnetic resonance imaging (MRI) findings after disease onset have not been well characterized. Case presentation: An individual developed abrupt hyperglycemia during pembrolizumab therapy for recurrent renal cell carcinoma and subsequently required insulin therapy. Serum C-peptide rapidly declined to below the detection threshold, whereas pancreatic enzyme levels remained within normal limits throughout follow-up. MRI performed 1 day after diagnosis demonstrated diffuse high signal intensity on diffusion-weighted imaging (DWI) and reduced apparent diffusion coefficient (ADC) values throughout the pancreas. Serial imaging over 25 months showed progressive pancreatic atrophy, whereas the DWI/ADC features persisted. Conclusion: This case provides a new descriptive longitudinal radiological observation of persistent diffusion-related pancreatic MRI findings and progressive pancreatic atrophy after the onset of ICI-induced diabetes.

Introduction and objective: Short sleep duration is associated with worse hemoglobin A _1c (HbA _1c ), and treatment guidelines recommend sufficient sleep duration. However, it is unclear whether extending sleep duration of short-sleeping people with type 2 diabetes causes improved HbA _1c . We aimed to assess the effect on HbA _1c of increasing sleep duration. Methods: We developed a personalized digital intervention based on the theory of planned behavior and conducted a single-blind, two-arm randomized controlled trial with 70 short-sleeping (≤6 hours) people with type 2 diabetes in Japan. Both arms measured sleep duration using an actigraph and a sleep diary. The intervention group received bedtime advancement support, including achievable bedtime goal setting and feedback. The primary outcome was between-arm difference in HbA _1c change after 12 weeks. Results: The baseline average sleep duration and HbA _1c were 5.96 ± 1.26 (hours) and 8.30 ± 0.91 (%) in the intervention group, and 5.94 ± 0.96 (hours) and 8.09 ± 0.51 (%) in the control group, respectively. Sleep duration improved with statistical significance (between-arm difference in change: 32.8 minutes, P = .0042). However, HbA _1c did not reduce significantly (between-arm difference in change: –0.11%, P = .51), and increases in sleep duration were not significantly associated with HbA _1c reduction ( P = .69). Conclusion: In this randomized trial, an average sleep extension of approximately 30 minutes over 12 weeks did not result in a significant improvement in HbA _1c among short-sleeping adults with type 2 diabetes. Further studies with larger sample sizes and greater sleep extension are warranted.

In Japan, approximately 20% of women in their twenties are underweight (BMI < 18.5 kg/m ² ), representing one of the highest prevalences among developed nations. Underweight and undernutrition are associated with decreased bone mass, menstrual abnormalities, impaired glucose tolerance, sarcopenia‐like changes, and systemic symptoms including depression and fatigue, significantly impacting health from young adulthood through the life course. This situation is influenced by complex factors including the societal internalization of thinness ideals, social media and mass media influences, the off‐label use of GLP‐1 receptor agonists, and socioeconomic factors such as poverty. However, while current healthcare and screening systems have advanced in addressing obesity, systematic approaches to underweight remain inadequately developed. Based on discussions by an expert working group established by the Japan Society for the Study of Obesity in collaboration with multiple related academic societies, this paper proposes a novel disease concept: Female Underweight/Undernutrition Syndrome (FUS). FUS encompasses the diverse physical and psychological health disorders arising from underweight or undernutrition, aiming to establish clear diagnostic criteria and frameworks for early detection and preventive intervention. Comprehensive measures are required, including stigma prevention, collaboration with educational and industrial sectors, integration into health screening systems, and addressing underlying social determinants. Through the proposal of FUS, we anticipate progress toward comprehensive interventions addressing the societal challenges surrounding women's health and body image.

Background: Diabetes distress is common in patients with type 1 diabetes mellitus (T1DM). The aim of this study was to construct and validate prediction models for diabetes distress in adults with T1DM using continuous glucose monitoring (CGM) metrics. Methods: The CGM metrics were collected from 259 adults with T1DM. Severe diabetes distress was defined as 40 points on the Problem Areas in Diabetes scale. Prediction models were developed based on ten machine learning algorithms: random forest (RF), support vector machine (SVM), Naive Bayes (NB), Neural Network (NN), k‐nearest neighbor (k‐NN), XGBoost (XGB), SGDClassifier (SGDC), XGB_limitet_depth (CGB_ld), L1LogisticRegression (L1), and LightGBM. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score. Results: Among the ten models, accuracy in the NN model was the highest (NN: 0.744, L1: 0.731, NB: 0.718, SVM: 0.692, SGDC: 0.654, RF: 0.628, k‐NN: 0.628, LightGBM: 0.615, XGBoost: 0.564, and XGB_ld: 0.564). The NN model achieved the highest AUC of 0.728 (95% confidence interval: 0.608–0.845). Conclusions: This study developed a predictive model for severe diabetes distress using machine learning, incorporating both demographic and CGM metrics in adults with type 1 diabetes mellitus. The NN model demonstrated potential as a practical tool to assist clinicians in identifying individuals at risk of severe diabetes distress.

Introduction The current clinical reality and burden of obesity disease in Japan are poorly understood. To address this knowledge gap, in this real-world study we describe the characteristics of Japanese individuals with obesity disease (IwOD) and their obesity disease treatments using data from the Japan Obesity Research Based on electronIc healTh record (J-ORBIT) database. Methods This retrospective observational study (January 2019 to January 2024) assessed data of ≥ 18-year-old IwOD registered in J-ORBIT and diagnosed with primary obesity per the criteria of the Japan Society for the Study of Obesity (JASSO). IwOD were grouped according to the most advanced treatment received during the study period, including the index date: lifestyle intervention, pharmacotherapy, or bariatric surgery. Demographic and clinical characteristics, degree of weight reduction, and percent change in metabolic parameters from baseline to the latest follow-up timepoint were described. Results Among the 782 IwOD included in this study, 274, 487, and 21 had received advanced treatment in the form of lifestyle intervention, pharmacotherapy, and bariatric surgery, respectively. At baseline, across treatment groups the mean age ranged from 45 to 57 years, female proportion ranged from 45% to 76%, and body mass index (BMI) ranged from 31 to 39 kg/m², respectively. Across treatment groups, 62–69% had ≥ 3 obesity-related health disorders (ORHDs) at baseline. Mean follow-up periods in these groups ranged from 846 to 1211 days. Mean weight and BMI numerically decreased from baseline to follow-up across groups. In the lifestyle intervention , pharmacotherapy, and bariatric surgery groups, 38%, 45%, and 65% of IwOD achieved ≥ 3% weight reduction at the latest follow-up timepoint. IwOD with baseline BMI ≥ 30 kg/ m² tended to achieve greater weight reduction. Triglyceride, high-density lipoprotein-cholesterol, blood glucose, hemoglobin A1c, and uric acid levels tended to improve in IwOD with ≥ 3% weight reduction and greater categories. Conclusion Obesity-associated burden in terms of ORHDs was common among Japanese IwOD. Although IwOD tended to have the highest weight reduction after bariatric surgery, this treatment is indicated for a highly restrictive population and requires specific criteria to be met, leaving many IwOD with unmet needs. These IwOD may need pharmacotherapy for better weight management than that provided by current options.