To compare the efficacy and safety of insulin degludec/insulin aspart biosimilar B01711 (HS-IDegAsp) with originator insulin degludec/insulin aspart-Ryzodeg (NN-IDegAsp) in Chinese patients with type 2 diabetes mellitus (T2DM) who were inadequately controlled on once- or twice-daily (BID) premixed or basal insulin ± oral antidiabetic drugs (OADs).
In this multicenter, randomized, open-label, parallel-group, active-controlled, phase 3 study, 367 participants with T2DM were randomized 1:1 to receive BID injections of HS-IDegAsp (n = 183) or NN-IDegAsp (n = 184) for 24 weeks. Insulins were administered subcutaneously with breakfast and the main evening meal at the same titration target. The primary endpoint was the change from baseline in glycated hemoglobin (HbA1c) to week 24.
At Week 24, the least squares (LS) mean change in HbA1c from baseline was −1.12% (95% CI −1.24 to −1.01) and −1.23% (95% CI −1.34 to −1.11) with HS-IDegAsp and NN-IDegAsp, respectively. The LS mean difference (HS-IDegAsp minus NN-IDegAsp) at Week 24 was 0.10% (95% CI −0.06 to 0.27), demonstrating that HS-IDegAsp was non-inferior to NN-IDegAsp. There was no statistically significant difference (P > 0.05) in fasting plasma glucose or proportion of patients achieving HbA1c < 7.0% at Week 24 between both groups. Safety and immunogenicity were similar between both groups.
HS-IDegAsp demonstrated comparable efficacy and safety to NN-IDegAsp during the 24-week treatment period in Chinese patients with inadequately controlled T2DM previously treated on once- or twice-daily premixed or basal insulin, with or without OADs.
Stress hyperglycemia ratio (SHR), calculated by dividing admission glucose levels by estimated chronic glucose levels, has emerged as a novel marker of glycemic stress. However, its prognostic value in patients hospitalized with COVID-19 remains unclear. This meta-analysis investigates the association between SHR and adverse outcomes in this population.
A comprehensive literature search was conducted in PubMed, Embase, and Web of Science databases for relevant observational studies. The primary outcome was a composite of ICU admission, invasive mechanical ventilation (IMV), and all-cause in-hospital mortality. Secondary outcomes included the individual components of the primary outcome. A random effects model was used to pool the results by incorporating heterogeneity.
Seven studies involving 2,272 patients were included. Patients with a high SHR had a significantly higher risk of poor composite outcomes (risk ratio [RR]: 1.93, 95% confidence interval [CI]: 1.54–2.43; I2 = 56%). Subgroup analyses according to study country, age, sex, diabetic status, and cutoff of SHR showed consistent results (P for subgroup difference all >0.05). Secondary analyses revealed increased risks of ICU admission (RR: 1.77), IMV (RR: 1.87), and in-hospital mortality (RR: 2.25) in patients with a high SHR at admission.
High SHR at admission is independently associated with poor prognosis in patients hospitalized with COVID-19. However, as admission glucose levels in most studies were not standardized for fasting status, SHR may be influenced by postprandial hyperglycemia, which should be considered when interpreting its prognostic value.
Among patients with diabetes receiving sodium–glucose cotransporter 2 (SGLT2) inhibitors, HbA1c levels are higher than glycated albumin levels. This study therefore aimed to evaluate the discrepancy between HbA1c and glucose management indicator (GMI), an index of glucose management derived from continuous glucose monitoring, in this population.
This multicenter retrospective cohort study included patients with diabetes in whom HbA1c and GMI were simultaneously measured at two Japanese institutions. Data were collected when HbA1c levels had stabilized for at least 6 months after the administration of an oral hypoglycemic agent. The primary outcome was the discrepancy between HbA1c and GMI among patients receiving SGLT2 inhibitors and those receiving other oral hypoglycemic agents. Inverse probability of treatment weighting (IPTW) was used to adjust for confounding factors.
In total, 136 patients were included; of these, 109 and 27 were included in the SGLT2 inhibitor group and control group, respectively. After IPTW adjustment, the discrepancy between HbA1c and GMI (HbA1c–GMI) was significantly higher in the SGLT2 inhibitor group than in the control group (β = 0.42; 95% confidence interval 0.14–0.70; P = 0.003).
Patients receiving SGLT2 inhibitors may have increased HbA1c relative to their actual glycemic control.
This study aimed to investigate whether the use of sodium-glucose co-transporter 2 inhibitors (SGLT2is) is associated with an increase in hemoglobin in the presence of chronic inflammation.
This is a matched-pair cohort study. Patients with diabetes who visited outpatient clinics from 2019 to 2023 were enrolled. New users and never-users of SGLT2is were matched by propensity scores, separately for those with C-reactive protein (CRP) levels lower than and higher than the median time-averaged CRP. Hemoglobin levels at the last visit for given estimated glomerular filtration rates (eGFR) were estimated using robust regression models with cubic terms of eGFR as covariates. Changes in hemoglobin, CRP, and mean corpuscular volume (MCV) were compared using mixed-effects models.
Among 1835 never-users and 690 new users of SGLT2i, 209 and 127 pairs were matched for those with lower and higher time-averaged CRP, respectively. Hemoglobin levels at the last visit were higher among new SGLT2i users, irrespective of CRP levels (P for interaction 0.25). During the first 6 months, hemoglobin increased among new SGLT2i users while it decreased among never-users, and the difference in the trajectories of hemoglobin was more prominent among those with higher time-averaged CRP (P for 3-way interaction 0.02). CRP remained stable irrespective of SGLT2i use and MCV increased among SGLT2i users with higher CRP levels.
SGLT2i use was associated with an increase in hemoglobin levels irrespective of chronic inflammation.
To develop and validate an early second-trimester predictive model integrating body mass index (BMI) trajectories and pathophysiological biomarkers for gestational diabetes mellitus (GDM) risk stratification, with the aim of reducing weight-monitoring frequency while maintaining predictive accuracy.
In this prospective dual-center cohort study, 1,450 pregnant women (<12 weeks gestation) without preexisting diabetes were enrolled from two Beijing maternal-child hospitals. Serial anthropometric (BMI at 6–10, 12–14, 15–19, and 24–28 weeks) and metabolic biomarkers (fasting glucose, C-peptide, lipids, uric acid) were analyzed. GDM was diagnosed via 75 g OGTT at 24–28 weeks. Multivariable logistic regression identified predictors using a 7:3 training-test split. Model performance was assessed by area under the ROC curve (AUC), calibration, and decision curve analysis.
GDM incidence was 26.1% (378/1,450). Significant weight/BMI disparities emerged as early as 6–10 weeks (GDM vs NGT: +2.3 kg, P < 0.0001), escalating through gestation. The final model incorporated age (OR = 1.07/year, 95% CI = 1.03–1.11), 12–14-week BMI (OR = 1.06/kg/m2, 1.01–1.12), fasting glucose (OR = 1.86/mmol/L, 1.45–2.40), fasting C-peptide (OR = 1.87/ng/mL, 1.28–2.73). The model demonstrated moderate discrimination (training AUC = 0.684; testing AUC = 0.685) with 63.7–67.2% sensitivity and 59.8–61.4% specificity at the optimal threshold (0.237). Negative predictive values exceeded 82%, enabling effective risk exclusion.
This dual-center model pioneers GDM risk stratification by 12–14 weeks using clinically accessible metrics, reducing weight-monitoring frequency without compromising prognostic value. While AUC limitations (0.68–0.69) suggest unmeasured contributors, its operational simplicity and robust negative predictive capacity support implementation in resource-constrained settings. The findings redefine antenatal care paradigms by shifting focus to early metabolic dysregulation rather than late diagnostic thresholds.
Muscle wasting is common in heart failure (HF) patients, particularly those with diabetes mellitus (DM). Renin-angiotensin system inhibitors (RASI) may have muscle-protective effects, but their association with muscle wasting in diabetic HF patients remains unclear. We investigated whether the association between RASI use and muscle wasting differs by DM status and plasma 3-methylhistidine (3-Me-His) levels, a muscle protein breakdown biomarker.
We performed a cross-sectional analysis of 384 hospitalized HF patients (mean age 71 ± 14 years, 41% female, 38% with DM). Muscle wasting was defined by dual-energy X-ray absorptiometry according to the Asian Working Group for Sarcopenia criteria. Associations between RASI use and muscle wasting were evaluated using logistic regression with inverse probability of treatment weighting. Interaction analyses assessed effect modification by DM status and 3-Me-His levels.
Muscle wasting prevalence was 58%. DM was an independent risk factor for muscle wasting (adjusted odds ratio [OR] 2.07, 95% confidence interval [CI] 1.27–3.38, P = 0.004). RASI were prescribed in 52% of patients. After adjustment, a significant interaction with DM was observed (P = 0.033). Among DM patients, RASI use was associated with lower muscle wasting (OR 0.33, 95% CI 0.14–0.76, P = 0.010), while no association was found in non-DM patients. Within the DM subgroup, the association was more evident in patients with lower 3-Me-His levels (OR 0.12, 95% CI 0.03–0.52, P = 0.005).
RASI use was associated with significantly lower muscle wasting in HF patients with DM, particularly those with lower 3-Me-His levels. These findings suggest a potential therapeutic window and warrant prospective investigation.
Diabetic foot ulcers (DFU) have become a global health issue. Chronic inflammation is a key pathological feature of DFU; however, its role in the diagnosis of DFU remains unclear.
DFU sample data were acquired from public databases, and weighted gene co-expression network analysis (WGCNA) was employed to identify key genes associated with DFU traits. A protein–protein interaction (PPI) network was constructed to screen for diagnostic biomarkers, and receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy of these key genes. The non-negative matrix factorization algorithm was applied to classify DFU samples. To further investigate the potential molecular mechanisms of these diagnostic genes, single-gene functional enrichment analysis, single-sample gene set enrichment analysis (ssGSEA) for immune infiltration, and construction of upstream transcription factor regulatory networks were conducted.
Four feature genes (FOSL1, HBEGF, S100A12, and TICAM1) demonstrating diagnostic potential were identified. ROC curve analysis validated these genes as potential diagnostic biomarkers for DFU. Functional enrichment analysis indicated that these genes are predominantly involved in biological processes related to keratinization and differentiation of epidermal skin cells. Furthermore, the expression levels of these feature genes exhibited a significant negative correlation with the infiltration levels of most immune cells. The regulatory network of upstream transcription factors highlighted the interconnectedness of these feature genes.
This study identified DFU diagnostic genes linked to the inflammatory response, revealing their distinct transcriptional profiles and functional enrichment. These discoveries advance understanding of DFU pathology and provide a theoretical foundation for early diagnosis and treatment.
Diabetic foot ulcers (DFUs) have increasingly affected younger populations. This study aimed to analyze the clinical characteristics of DFUs in different age groups of diabetic patients with foot ulcers.
This is a retrospective cohort study of diabetic patients with foot ulcers admitted to West China Hospital, Sichuan University. They were divided into the young (<45 years), the middle-aged (45–64 years), and the elderly groups (≥65 years). The patients were followed up for a median of 44.5 months, either at the outpatient department or by phone.
This study enrolled 1,209 patients with DFUs, stratified into three groups according to age: young (n = 65), middle-aged (n = 509), and elderly (n = 635). All patients had a long history of diabetes with an average duration of 11.5 years. The DFU patients of all ages have poor glycemic control. About one-third of the patients have recurrent foot ulcers. The prevalence of comorbidities such as hypertension, coronary artery disease, chronic kidney disease, and peripheral artery disease increased significantly with age (P < 0.001). Neuropathic foot ulcers were more common in the young patients (48.3%), whereas neuro-ischemic ulcers were more prevalent in the middle-aged (42.1%) and elderly patients (56.9%). Compared with the young (27.7%) and middle-aged patients (26.9%), the ulcer healing rates during hospitalization were significantly lower in the elderly patients (18.9%, P = 0.004). During a median 44.5 (IQR 18.7–74.5)-month follow-up period, 375 (36.2%) deaths occurred, and all-cause mortality increased significantly with age (P < 0.001).
Clinical characteristics of DFUs are profoundly age-dependent: younger patients exhibited poorer glycemic control, neuropathic ulcers, and mechanical injuries, while the older patients developed more vascular complications and neuro-ischemic ulcers. Therefore, different prevention and treatment measures should be taken for DFUs based on their clinical characteristics in different age groups.
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