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Aims/Introduction: This study aimed to investigate the risk factors for diabetic retinopathy (DR) and diabetic kidney disease (DKD) in Japanese patients with diabetes mellitus (DM). Identifying these factors could provide insights into the shared and distinct mechanisms contributing to these complications in the diabetic population. Materials and Methods: We conducted a retrospective analysis using the J‐DREAMS (Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System) database, which is directly linked to electronic medical records. The study included Japanese people aged 18 years and older with diabetes, who were registered at a referral center between December 1, 2015, and March 31, 2021, and had simultaneous measurements of serum creatinine and hemoglobin A1c (HbA1c). The presence or absence of DR and DKD was determined for 8,794 and 8,770 patients, respectively. Multivariable logistic regression analyses were used to identify risk factors, considering patient characteristics, comorbid conditions, and laboratory data as explanatory variables. Results: Common risk factors for both DR and DKD included hypertension, anemia, diabetic neuropathy, cerebrovascular disease, chronic heart failure, low serum albumin levels, and elevated HbA1c. The contributions of age, duration of DM, and body mass index (BMI) differed between the DR and DKD groups. Conclusions: In addition to poor glycemic control and hypertension, anemia, low serum albumin, cerebrovascular disease, and heart failure were identified as independent common risk factors for DR and DKD, suggesting the existence of cardio‐renal anemia syndrome in patients with DM. [ABSTRACT FROM AUTHOR]

The principal causes of death among 68,555 patients with diabetes and 164,621 patients without diabetes who died in 208 hospitals throughout Japan between 2011 and 2020 were determined based on a survey of hospital records. The most frequent cause of death in patients with diabetes was malignant neoplasms (38.9%) (lung 7.8%, pancreas 6.5%, liver 4.1%), followed, in order of descending frequency, by infectious diseases (17.0%) and then vascular diseases (10.9%) (cerebrovascular diseases 5.2%, ischemic heart diseases 3.5%, renal failure 2.3%). The proportion of deaths from malignant neoplasms and vascular diseases has trended upward and downward, respectively. Almost all deaths from ischemic heart diseases were due to myocardial infarction, and the proportion of deaths from heart diseases other than ischemic heart diseases was relatively high (9.0%), with most cases due to heart failure. Diabetic coma associated with hyperglycemia accounted for only 0.3% of deaths. The proportion of deaths from malignant neoplasms, infectious diseases, renal failure, ischemic heart diseases, and heart failure was significantly higher in patients with diabetes than in those without diabetes, and the proportion of deaths from cerebrovascular diseases was significantly lower in patients with diabetes. With regard to the relationship between the age and cause of death in patients with diabetes, malignant neoplasms were the most frequent cause of death in all age groups, and the incidence was around 50% for those in their 50s and 60s. The incidence of death due to infectious diseases was highest in patients older than their 70s. The incidence of death due to vascular diseases for patients in their 40s and 50s was higher than that due to infectious diseases. The highest incidence of death due to ischemic heart diseases was observed for patients in their 40s, and that due to renal failure and heart failure in patients older than their 70s. Compared with patients without diabetes, patients with diabetes demonstrated a higher incidence of death due to pancreatic cancer, infectious diseases, renal failure, ischemic heart diseases, and heart failure, and a lower incidence of death due to cerebrovascular diseases in all age groups. The average age at death of patients with diabetes was 74.4 years old in men and 77.4 years old in women, which were lower than the average lifespan of the Japanese general population in 2020 by 7.2 and 10.3 years, respectively. However, these differences were smaller than in previous surveys. The average age at death due to all causes, especially due to ischemic heart diseases, cerebrovascular diseases, heart failure, infectious diseases, and diabetic coma, was lower in patients with 'poorer' glycemic control than in those with 'better' glycemic control. In the total survey population, the average age at death of patients with diabetes was significantly higher than that of patients without diabetes. The average age at death due to malignant neoplasms and cerebrovascular diseases was higher in patients with diabetes than in those without diabetes and that due to renal failure, ischemic heart diseases, and infectious diseases was lower in patients with diabetes than in those without diabetes. [ABSTRACT FROM AUTHOR]

Aims/Introduction: We aimed to explore the associations between income/employment status and diabetes care processes, health behaviors and health outcomes. Materials and Methods: This cross‐sectional study used health insurance claims data between April 2021 and March 2022, and a questionnaire survey between December 2022 and January 2023 in Tsukuba City. The study analyzed the participants with diabetes (other than type 1) from those selected by stratified random sampling. We evaluated diabetes care processes, health behaviors and health outcomes by calculating weighted proportions among the groups. We also assessed the associations between income/employment status and these variables using multivariable modified Poisson regression models. Results: Of the 264 identified participants, 161 (64.2%) were men and 168 (72.8%) were aged ≥65 years old. Compared with the low‐income groups, the high‐income group had a higher proportion of sodium–glucose cotransporter 2 inhibitors or glucagon‐like peptide‐1 receptor agonists use (adjusted risk ratio [aRR] 1.70, 95% confidence interval (CI) 1.07–2.72), a higher proportion of attendance to annual health checkups for ≥2 years (aRR 1.68, 95% CI 1.07–2.64) and a lower proportion of all‐cause hospitalization (aRR 0.15, 95% CI 0.04–0.48); additionally, the middle‐income group had a lower proportion of high total outpatient medical expenses (aRR 0.57, 95% CI 0.35–0.92). Compared to the no work time group, the full‐time work group had a lower proportion of exercise habits (aRR 0.59, 95% CI 0.35–0.99) and a higher proportion of good self‐reported health (aRR 2.08, 95% CI 1.22–3.55). Conclusions: Several variables were associated with income/employment status. Policy intervention should focus on high‐risk groups identified by considering these associations. [ABSTRACT FROM AUTHOR]

Aims/Introduction: The clinical significance of age‐related biomarkers in patients with diabetes has not been fully elucidated. In this study, we aimed to establish models to predict the progression of aging in patients with diabetes using biomarkers. Materials and Methods: This single‐center, retrospective cohort study included 115 Japanese patients with diabetes aged ≥60 years. Age‐related adverse health outcomes were defined as emergency hospitalization, any increase in the level of nursing care certification, admission to a nursing home or death. The associations of age‐related biomarker levels (adiponectin, growth differentiation factor 15 [GDF15], C‐X‐C motif chemokine ligand 9 and apelin) and clinical indicators with age‐related adverse health outcomes were evaluated. Factors that predominantly influenced the occurrence of age‐related adverse health outcomes were explored using the Cox proportional hazards model. Results: The mean age of the 115 participants was 73 years, 50.6% were men, the mean body mass index and hemoglobin A1c level were 25.3 kg/m2 and 9.79%, respectively. There were 26 age‐related adverse health outcomes during the study period (median 1.93, range 0–4.65 years). In a model combining clinical indicators and biomarkers, including the Barthel Index, GDF15 and adiponectin, the occurrence of age‐related adverse health outcomes was found to be significantly associated with GDF15 and Barthel Index. The group with both GDF15 and adiponectin levels higher than the median proved to be significantly higher than the group with both lower. Conclusions: The measurement of GDF15 and adiponectin levels and the Barthel Index might be useful for predicting age‐related adverse health outcomes in patients with diabetes. [ABSTRACT FROM AUTHOR]

Aims/Introduction: A recent US Food and Drug Administration report highlighted concerns over nitrosamine (7‐nitroso‐3‐(trifluoromethyl)‐5,6,7,8‐tetrahydro[1,2,4] triazolo‐[4,3‐a]pyrazine [NTTP]) impurities in sitagliptin, prompting investigations into its safety profile. The present study aimed to determine if the use of NTTP‐contaminated sitagliptin, in comparison with other dipeptidyl peptidase‐4 (DPP‐4) inhibitors, is associated with an increased cancer risk. Materials and Methods: This retrospective cohort study secondarily used the National Database of Health Insurance Claims and Specific Health Checkups of Japan, encompassing data on >120 million individuals. The study involved patients who initiated DPP‐4 inhibitor therapy (sitagliptin or other DPP‐4 inhibitors) and continued its exclusive use for 3 years. Sitagliptin users were compared with other DPP‐4 inhibitor users for assessing the occurrence of cancers, as defined by diagnosis codes. Further analyses focused on specific types of cancer, using either diagnosis codes or a combination of diagnosis and procedure codes. We also carried out various sensitivity analyses, including those with different exposure periods. Results: Sitagliptin users (149,120 patients, 388,356 person‐years) experienced 9,643 cancer incidences (2,483.0/100,000 person‐years) versus 12,621 incidences (2,504.4/100,000 person‐years) among other DPP‐4 inhibitor users (199,860 patients, 503,952 person‐years), yielding a minimal difference (incidence rate ratio 0.99, 95% confidence interval 0.97–1.02). A multiple Cox proportional hazards model showed no significant association between sitagliptin use and overall cancer incidence (hazard ratio 1.01, 95% confidence interval 0.98–1.04). Findings were also consistent across cancer types and sensitivity analyses. Conclusions: We observed no evidence to suggest an increased cancer risk among patients prescribed NTTP‐contaminated sitagliptin, although continued investigation is needed. [ABSTRACT FROM AUTHOR]

Sarcopenic obesity is the co‐existence of obesity and sarcopenia in individuals aged 40–75 years. The Japanese Working Group on Sarcopenic Obesity has developed diagnostic criteria tailored for the Japanese population, considering their unique characteristics compared with European populations. Our algorithm consists of two steps: screening and diagnosis. The screening of obesity mandates using waist circumference and/or body mass index (BMI) based on national standards, while screening for sarcopenia involves the "finger ring test" in addition to the Asian Working Group for Sarcopenia 2019 criteria. The final diagnosis of sarcopenia involves handgrip strength for low muscle strength, the five‐times chair stand test for low physical function, and limb skeletal muscle mass (corrected for BMI) for low muscle mass. Obesity is assessed by visceral fat area or body fat percentage. Sarcopenic obesity is then categorized into Stage I, with muscle weakness/loss of function, loss of muscle mass, and obesity; or Stage II, which includes complications. Further clinical validation is needed to refine the consensus and age range. Geriatr Gerontol Int 2024; 24: 997–1000. [ABSTRACT FROM AUTHOR]

Aim: To explore differences in imeglimin response among type 2 diabetes (T2D) patient clusters using data‐driven cluster analysis. Methods: Data‐driven cluster analysis (non‐hierarchical k‐means clustering) was performed on randomized, double‐blind, imeglimin monotherapy and adjunctive (to insulin) therapy trials based on four baseline variables: (1) disease duration; (2) body mass index (BMI); (3) HbA1c; and (4a) homeostatic model assessment of β‐cell function (HOMA‐β) (monotherapy trials) or (4b) insulin total daily dose (adjunctive trial). Results: Four clusters were identified with distinct clinical characteristics in both monotherapy (1‐4) and adjunctive therapy (I‐IV) trials; clusters 1 and I had lower values across all four indices versus the overall population, clusters 2 and II had a longer diabetes duration, cluster 3 had higher baseline BMI and HOMA‐β, and cluster III had higher baseline BMI and insulin total daily dose, while clusters 4 and IV had higher baseline HbA1c. Between‐group differences in HbA1c change (95% confidence interval) and effect size (ES) at week 24 varied considerably by cluster (cluster 1: −0.82 [−1.00, −0.63], ES = 1.47; cluster 2: −0.64 [−0.89, −0.39], ES = 1.18; cluster 3: −0.86 [−1.38, −0.33], ES = 0.84; cluster 4: −1.27 [−1.73, −0.82], ES = 1.44). For imeglimin adjunctive therapy, HbA1c improvements were significant versus placebo at week 16, excluding cluster III (cluster I: −0.63 [−0.95, −0.31], ES = 0.88; cluster II: −0.66 [−1.02, −0.30], ES = 1.13; cluster III: −0.31 [−0.73, 0.11], ES = 0.46; cluster IV: −0.82 [−1.29, −0.35], ES = 0.99). Conclusions: Differences in imeglimin response were observed among T2D patient clusters. Patient stratification may help with selection of those most probable to respond to imeglimin. [ABSTRACT FROM AUTHOR]

Aims: The utilization of long‐term effect of internet of things (IoT) on glycemic control is controversial. This trial aimed to examine the effect of an IoT‐based approach for type 2 diabetes. Materials and Methods: This randomized controlled trial enrolled 1,159 adults aged 20–74 years with type 2 diabetes with a HbA1c of 6.0–8.9% (42–74 mmol/mol), who were using a smartphone on a daily basis were randomly assigned to either the IoT‐based approach group (ITG) or the control group (CTG). The ITG were supervised to utilize an IoT automated system that demonstrates a summary of lifelogging data (weight, blood pressure, and physical activities) and provides feedback messages that promote behavioral changes in both diet and exercise. The primary end point was a HbA1c change over 52 weeks. Results: Among the patients, 581 were assigned to the ITG and 578 were in the CTG. The changes in HbA1c from baseline to the final measurement at 52 weeks [mean (standard deviation)] were −0.000 (0.6225)% in ITG and − 0.006 (0.6449)% in CTG, respectively (P = 0.8766). In the per protocol set, including ITG using the IoT system almost daily and CTG, excluding those using the application almost daily, the difference in HbA1c from baseline to 52 weeks were −0.098 (0.579)% and 0.027 (0.571)%, respectively (P = 0.0201). We observed no significant difference in the adverse event profile between the groups. Conclusions: The IoT‐based approach did not reduce HbA1c in patients with type 2 diabetes. IoT‐based intervention using data on the daily glycemic control and HbA1c level may be required to improve glycemic control. [ABSTRACT FROM AUTHOR]

Aims/Introduction: To investigate the effect of patient characteristics on imeglimin effectiveness in Japanese patients with type 2 diabetes mellitus. Materials and Methods: Data were pooled from two randomized, placebo‐controlled, 24‐week, double‐blind studies of imeglimin monotherapy in Japanese adults with type 2 diabetes mellitus, with the proportion of responders (glycated hemoglobin [HbA1c] < 7.0%) and sustained responders (i.e., achieved and maintained response) in the imeglimin 1,000 mg twice daily group calculated at each visit. Patient factors significantly (P < 0.05) correlated with response were explored through multivariate logistic regression. Subgroup analyses compared the efficacy of imeglimin in patients with a HbA1c improvement less than or equal to −0.3% (early responders) versus greater than −0.3% (early non‐responders) at week 4. Results: A total of 38.0% of imeglimin‐treated patients and 7.2% of placebo‐treated patients were responders (P < 0.001, number needed to treat = 4). The proportion of sustained responders at weeks 4, 8, 12, 16 and 20 was 10.6, 19.0, 24.0, 25.7 and 29.1%, respectively (>70% of responders at each visit). Improvements in HbA1c and fasting glucose were significantly greater in early responders versus early non‐responders from week 4; between‐group differences remained significant to week 24. Older age (odds ratio 1.09, 95% confidence interval 1.04–1.14; P < 0.001); treatment‐naïve status vs previous treatment (odds ratio 3.70, 95% confidence interval 1.55–8.82; P = 0.003), and lower baseline HbA1c (odds ratio 0.06, 95% confidence interval 0.02–0.16; P < 0.001) predicted response. Conclusions: A significantly higher proportion of patients receiving imeglimin 1,000 mg twice daily monotherapy were responders versus placebo. Most (>70%) were sustained responders, suggesting that response is fairly predictable. Older age, treatment‐naïve status and early treatment response significantly predicted imeglimin effectiveness. [ABSTRACT FROM AUTHOR]

Purpose: Thyrotoxic periodic paralysis (TPP) is characterized by muscle paralysis and significant intracellular potassium movement resulting in hypokalemia. Since TPP is a rare condition, only a few studies have explicated the clinical characteristics of patients with this disease. This study aimed to elucidate the clinical characteristics of patients with TPP by comparing them with those with thyrotoxicosis without paralysis (non-TPP) and sporadic periodic paralysis (SPP). Methods: This was a single-center retrospective cohort study. Clinical data of patients with hyperthyroidism (n = 62) or periodic paralysis (n = 92) who were emergently admitted to our hospital was extracted from the electronic medical records and analyzed. Results: All patients in the TPP group (15 males and 2 females) had Graves' disease, with 14 being newly diagnosed. The average serum potassium level on admission was 2.3±0.75 mEq/L. No significant correlation was observed among serum potassium level, amount of potassium required for normalization, and thyroid hormone levels. The TPP group showed significantly younger age, higher male ratio and body mass index (BMI), and lower serum potassium and phosphorus levels than the non-TPP group, which comprised 36 patients with Graves' disease. No significant differences were observed between the TPP and SPP (n = 11) groups in terms of age, sex, BMI, serum electrolyte levels, potassium requirement for normalization, and recovery time. Main conclusions: Considering that most patients with TPP have undiagnosed Graves' disease, distinguishing TPP from SPP based on clinical information and course alone is difficult in emergency settings. Therefore, for early detection and launch of specific treatment of Graves' disease, screening for thyroid hormone and anti-thyroid stimulating hormone receptor antibody levels is necessary when treating patients with periodic paralysis. [ABSTRACT FROM AUTHOR]

The potential liability to hypercatabolism in lipodystrophy remains to be fully elucidated. Here we report a 28‐year‐old Japanese woman with acquired generalized lipodystrophy, who presented with recurrence of panniculitis and anemia. After corticosteroid treatment was started, she showed rapid reductions in body weight and lean mass by 15% at maximum, accompanied by an elevated urea nitrogen/creatinine ratio, which recovered almost fully as the corticosteroid treatment was tapered and discontinued. She had multiple risk factors for hypercatabolism: lack of metabolic reserves, insulin resistance, and hyperglycemia due to lipodystrophy, lowered daily activity due to anemia, persistent inflammation, and wasting associated with panniculitis, and relatively insufficient energy and protein intake during hospitalization. More attention should be paid to the potential liability to hypercatabolism in patients with lipodystrophy, and to skeletal muscle loss as an adverse effect of corticosteroid treatment in patients at high risk, such as those with diabetes or decreased metabolic reserves. [ABSTRACT FROM AUTHOR]