To evaluate the associations and diagnostic ability of non-traditional lipid parameters and lipid-inflammation parameters with abnormal glucose metabolism, and to investigate the mediating role of high-sensitivity C-reactive protein (hs-CRP).

Based on cross-sectional survey data from 9,790 adults in Fujian Province, China (2020-2021), 2,301 participants were included in the analysis. Eight non-traditional lipid parameters and lipid-inflammation parameters incorporating hs-CRP were calculated. Associations with impaired glucose metabolism were examined using ordinal logistic regression, restricted cubic spline analysis, and subgroup analyses. Incremental diagnostic ability was evaluated using receiver operating characteristic curve analysis, C-statistics, net reclassification improvement, and integrated discrimination improvement. Mediation analysis was performed to examine the role of hs-CRP.

All parameters were significantly positively associated with impaired glucose metabolism, with several showing nonlinear dose-response relationships. Subgroup analyses demonstrated generally consistent associations with those in the overall population. In the prediabetes comparison, atherogenic coefficient, Castelli's index-I, remnant cholesterol-C-reactive protein index, and remnant cholesterol to high-density lipoprotein cholesterol-C-reactive protein index (RC/HDL-C-CRP) had superior diagnostic ability, whereas atherogenic index of plasma and RC/HDL-C-CRP performed better in the diabetic comparison. Mediation analysis indicated that hs-CRP partially mediated the association between non-traditional lipid parameters and prediabetes, with bidirectional mediation effects observed. No mediation effect was observed for diabetes risk.

Non-traditional lipid parameters and lipid-inflammation parameters were significantly associated with impaired glucose metabolism. Incorporating inflammatory information may enhance the identification of high-risk individuals, providing early warning particularly in prediabetic populations.

While the long-term cardiorenal benefits of finerenone have been established in landmark clinical trials, its immediate impact on hemodynamic parameters in routine clinical practice remains to be fully characterized. This study aimed to evaluate the real-world acute effects of finerenone on blood pressure (BP) and heart rate (HR) in hospitalized patients with type 2 diabetes (T2D).

We conducted a retrospective observational study of patients with T2D who were initiated on finerenone as part of standard clinical care. Patients were grouped into five cohorts based on the day of treatment initiation (Day 1 to Day 5). We monitored morning (a.m.) and afternoon (p.m.) systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) daily for 7 days. Baseline characteristics, including urinary albumin-to-creatinine ratio (UACR), serum potassium, and renin-angiotensin-aldosterone system (RAAS) markers, were assessed to reflect the real-world population's heterogeneity.

In this real-world cohort, finerenone was mainly prescribed to patients with notably high UACR (average grade III; p < 0.0001 compared to non-users), indicating its targeted use for high-risk kidney patients. Despite a complex background of intensive therapies-including ARBs (90.6%), CCBs (84.6%), and SGLT-2 inhibitors (91.4%)-adding finerenone was linked to significant decreases in both SBP and DBP. Daily detailed analysis showed that the largest BP reductions often occurred within the first 24-48 hours of treatment (p < 0.05 to p < 0.0001), across various treatment groups. Additionally, heart rate (HR) remained stable during the initial days of therapy. The distribution of background medications stayed consistent during finerenone treatment, suggesting that the hemodynamic improvements were not due to changes in other antihypertensive medications.

This real-world evidence indicates that finerenone was associated with antihypertensive effects in hospitalized T2D patients with albuminuria. Its ability to substantially reduce BP and stabilize HR shortly after hospitalization, despite concurrent standard therapies, underscores its practical utility in managing hypertension.

To assess the knowledge, attitude, and practice (KAP) levels among patients with osteomyelitis, analyze their associated factors, and explore the pathways between knowledge, attitude, and practice.

A cross-sectional study was conducted in a large tertiary hospital from April 1st to June 1st, 2025, enrolling 405 patients with osteomyelitis. A self-administered questionnaire collected demographic and disease-related information and assessed KAP. Cronbach's α tested questionnaire reliability, and confirmatory factor analysis examined construct validity. Univariate analysis, multivariate binary logistic regression with a two-tailed p < 0.05 as the statistical significance cut-off, and structural equation modeling (SEM) were used to explore factors associated with KAP and their interrelationship mechanisms.

Mean scores for knowledge, attitude, and practice were 28.56 ± 10.28, 29.08 ± 11.36, and 28.58 ± 11.62, respectively; achievement rates were 32.1, 35.6, and 30.9%. The overall Cronbach's α was 0.962, the KMO value was 0.971, and model fit was good (CMIN/DF = 1.32, RMSEA = 0.028, CFI = 0.984). Multivariate analysis showed that age (p = 0.013), income (p < 0.001), education (p < 0.001), history of diabetes mellitus (p = 0.009), and number of hospitalizations (p = 0.020) were independently associated with knowledge. Knowledge level (p < 0.001), age (p = 0.034), income (p < 0.001), and education (p < 0.001) were associated with attitude. Attitude level (p < 0.001), knowledge level (p < 0.001), income (p < 0.001), and education (p = 0.019) were associated with practice. SEM revealed that knowledge had a direct theoretical association with attitude (β = 0.694, p < 0.001) and practice (β = 0.303, p < 0.001); attitude had a direct theoretical association with practice (β = 0.465, p < 0.001). The indirect theoretical association of knowledge with practice via attitude was significant (β = 0.357, p < 0.001), accounting for 54.1% of the total effect.

Patients with osteomyelitis showed insufficient knowledge, attitude, and practice. Older age, lower education, and lower income were associated with poorer outcomes. Attitude mediated the knowledge-practice association. Future interventions should focus on attitude change in vulnerable populations, and prospective studies are warranted.

This study aimed to evaluate the demographic, clinical, and hormonal characteristics; comorbidities; surgical pathology; treatment modalities; and long-term clinical outcomes of patients diagnosed with and managed for acromegaly at our tertiary referral center over a 15-year period.

Between 2010 and 2024, 247 patients with acromegaly were evaluated. Diagnosis and biochemical remission were determined according to the 2024 Acromegaly Consensus Criteria.

The median follow-up duration was 8 years (IQR: 3-14). At the time of diagnosis, the most frequent pituitary hormone deficiency was secondary adrenal insufficiency, present in 17.8% of patients. The most common comorbidities were hypertension (HT, 42.1%) and diabetes mellitus (DM, 30.8%). At the time of diagnosis, macroadenomas were present in 153 of 193 patients (79.3%), and, according to the Knosp classification, 28.6% of tumors were grade 4. A total of 218 patients underwent surgical intervention; 86 (39.4%) achieved postoperative cure without the need for adjuvant medical therapy or radiotherapy. Postoperatively, one or more anterior pituitary hormone deficiencies were found in 34 patients (22.8%), with central hypothyroidism being the most common (52.9%). Patients who achieved biochemical remission were significantly older (p = 0.003), had a higher prevalence of HT and DM (both p < 0.05), and were more likely to exhibit positive growth hormone (GH) immunostaining (p = 0.017). In contrast, those who did not achieve remission were more likely to have higher Knosp grades (3-4) (p = 0.002).

In this study, a favorable prognosis was associated with older age at diagnosis, lower baseline GH levels, positive GH immunostaining, smaller tumor size, and lower Knosp grade, underscoring the prognostic value of both biochemical and anatomical parameters. Further studies are warranted to refine prognostic markers and establish standardized treatment algorithms to improve long-term outcomes in acromegaly.

Dietary fiber is recommended in diabetes management for its potential anti-inflammatory effects, but currently, the association between fiber intake, systemic inflammation, and long-term survival in adults with diabetes remains uncertain. This cohort study analyzed data from 3894 U.S. adults with diabetes across 10 National Health and Nutrition Examination Survey cycles (1999-2020). Fiber intake levels (grams of fiber per kilogram of body weight, g/kg) was assessed via dietary interviews, and mortality outcomes were linked to National Death Index records through 2019. The systemic immune-inflammation index (SII) was calculated using platelet, neutrophil, and lymphocyte counts. Cox proportional hazards models evaluated associations between fiber intake and all-cause mortality, adjusted for demographics, lifestyle factors, and comorbidities. Mediation analysis quantified SII's role in mortality risk reduction. Higher fiber intake levels demonstrated a dose-dependent inverse relationship with all-cause mortality (P < .001). In fully adjusted models, the 3rd quartile (Q3) of fiber intake levels showed the lowest mortality risk (hazard ratio = 0.47, 95% confidence interval = 0.37-0.68). The association attenuated slightly in Q4, possibly indicating a threshold effect. Mediation analysis revealed that 13.07% (95% confidence interval = 6.85%-18%) of the mortality reduction was attributable to SII downregulation. Increased dietary fiber intake levels are associated with reduced all-cause mortality in diabetic populations, with a possible mediating factor being the reduction in systemic inflammation levels among U.S. adults with diabetes. These findings support integrating fiber-rich diets into diabetes management protocols.

Acute respiratory distress syndrome (ARDS) and diabetes mellitus (DM) constitute a high-risk comorbidity, with diabetes-related immune dysfunction and metabolic dysregulation exacerbating ARDS severity and worsening outcomes. However, long-term national mortality trends and subgroup disparities for this comorbidity remain inadequately characterized. Using US national mortality data from the CDC WONDER database (1999-2023), we analyzed death records listing both ARDS (ICD-10 J80) and all types of DM (ICD-10 E10-E14) as underlying or contributing causes of death. Age-adjusted mortality rates (AAMR) per 1,00,000 population were standardized to the 2000 US census. Temporal trends were evaluated using Joinpoint regression to compute average annual percent change (AAPC) and identify inflection points, with stratification by sex, race/ethnicity, census region, urbanization level, and age group. From 1999 to 2023, overall AAMR for ARDS-DM comorbidity declined from 0.66 to 0.40 per 1,00,000 (AAPC: -0.12%, 95% CI: -2.75 to 2.58). A triphasic pattern emerged: pre-pandemic relative stability or gradual decline, a sharp mortality surge during the COVID-19 pandemic (2017-2020/21), followed by steep post-pandemic decline (2020/21-2023). Persistent disparities were evident, with higher 2023 mortality among males, non-Hispanic Black and Hispanic populations, and residents of the South and West census regions. While long-term AAMR for ARDS-DM comorbidity showed an overall declining trend, the COVID-19 pandemic induced significant transient disruption. Preexisting socioeconomic and demographic disparities in mortality persisted throughout the 25-year period, most evident in rural areas, the South, and the Midwest, highlighting the continued need for targeted public health strategies to reduce severe respiratory complications in high-risk diabetic populations.

Digital health technologies are increasingly applied in diabetes care, enabling continuous monitoring, personalized support and remote interventions. Meanwhile, artificial intelligence (AI) is enhancing the precision and effectiveness of these tools. This study aims to map global research trends and thematic developments in AI-driven digital health technologies for diabetes management and to explore their future directions.

We collected data from the Web of Science Core Collection, including articles and reviews published up to July 12, 2025, using CiteSpace, VOSviewer, and Microsoft Excel to analyze countries/regions, institutions, journals, references, authors, and keywords.

A total of 673 publications were included in the analysis. Global publications on AI-driven digital health technologies for diabetes increased steadily, with the USA leading in output. The University of London ranked as the most productive institution. Sensors and diabetes care were the most frequently published and cited journals in this field. Herrero P was among the most prolific authors. The most cited article was "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs." "diabetes" was the most frequently occurring keyword. Keyword cluster analysis identified 3 primary research hotspots: AI-enabled monitoring, digital health interventions, and AI-based diabetic retinopathy screening.

This study summarizes the evolution of AI-driven digital health technologies in diabetes care. Although challenges remain in data security, standardization and validation, these technologies hold increasing potential for accurate diagnosis, real-time monitoring and personalized care.

Although sustained virological response (SVR) after hepatitis C virus treatment reduces hepatocellular carcinoma (HCC) incidence, residual risk persists. Metformin has been associated with lower HCC risk, but whether cumulative metformin exposure (CME) lowers post-SVR risk remains unclear. We evaluated whether CME was associated with lower HCC risk after SVR.

We analysed a multicentre cohort of 1531 patients who achieved SVR after direct-acting antiviral therapy (median follow-up, 75.5 months). Metformin exposure was modelled as a time-updated cumulative variable in start-stop Cox models to control for immortal-time bias. Stabilised inverse probability weighting addressed confounding by indication and censoring. The overall model was sex-stratified and adjusted for FIB-4, clinically significant portal hypertension (CSPH), type 2 diabetes mellitus (T2DM) and smoking. A prespecified T2DM-restricted analysis used T2DM-specific IPTW plus IPCW, sex stratification and CSPH adjustment.

During follow-up, 50 patients developed HCC. Crude incidence was highest among patients with FIB-4 > 3.25, CSPH and T2DM without metformin exposure (4.84 cases per 100 person-years). In the overall weighted model, CME was associated with lower HCC risk (HR, 0.46 per year; 95% CI, 0.27-0.77; p = 0.004). CSPH, T2DM, smoking and FIB-4 > 3.25 independently increased risk. In the T2DM-restricted model, each additional year remained associated with lower HCC hazard (HR, 0.49; 95% CI, 0.29-0.84; p = 0.009), whereas CSPH was associated with higher risk (HR, 6.04; 95% CI, 2.12-17.19; p < 0.001).

After SVR, CME was associated with lower HCC risk; this possible duration-dependent inverse association was clinically interpretable only among metformin-eligible patients with T2DM.

Colorectal cancer (CRC) and diabetes mellitus are major global health burdens that frequently coexist and share overlapping metabolic and molecular abnormalities. Accumulating epidemiological evidence indicates that diabetes is associated with an increased risk of CRC; however, the underlying mechanisms remain incompletely defined. Long non-coding RNAs (lncRNAs) have recently emerged as important regulators of gene expression and cellular signaling, with critical roles in both metabolic disorders and cancer. In this review, we summarize current evidence on key lncRNAs that are implicated in the shared molecular networks linking diabetes and CRC. These lncRNAs modulate multiple signaling pathways, including PI3K/AKT, Wnt/β-catenin, NF-κB-mediated inflammation, hypoxia-associated signaling, metabolic reprogramming, angiogenesis, and epigenetic regulation. Through interactions with microRNAs (miRNAs), transcription factors, and chromatin-modifying complexes, they influence key biological processes such as insulin signaling, glucose metabolism, epithelial-mesenchymal transition, oxidative stress responses, and tumor progression. Elucidating the roles of lncRNAs provides important insight into the molecular interplay between metabolic dysfunction and colorectal tumorigenesis. Notably, many lncRNAs are detectable in circulating fluids, highlighting their potential as non-invasive biomarkers for early detection and risk assessment in diabetic populations at increased risk of CRC. Furthermore, targeting dysregulated lncRNAs may offer novel therapeutic opportunities to simultaneously modulate metabolic and oncogenic pathways. Overall, integrating lncRNA biology into the study of CRC and diabetes may advance our understanding of disease mechanisms and support the development of improved diagnostic and therapeutic strategies.

We evaluated the feasibility of using a precise oral glucose loading combined with subcutaneous insulin administration protocol for ¹⁸F-FDG PET myocardial metabolic imaging in patients with coronary artery disease (CAD) complicated by diabetes mellitus (DM).

179 consecutive CAD patients complicated by DM were enrolled. Oral glucose was given at variable doses based on baseline blood glucose, and subcutaneous insulin was injected at adjusted doses according to post-load glucose levels before FDG injection. SPECT myocardial perfusion imaging and PET myocardial metabolic imaging were performed using a one-day protocol. The image quality and adverse reaction data were analyzed.

Among 179 patients, FDG image quality was scored as excellent in 57.5%, very good in 31.8%, good in 7.8%, fair in 1.7% and non-diagnostic in 1.1%. When patients were stratified by blood glucose level at time of FDG injection >7.77 mmol/L, 5.55-7.77 mmol/L and <5.55 mmol/L, the image quality were excellent in 43.1, 60.4 and 74.1%, very good in 43.1, 30.7 and 14.8%, good in 9.8, 5.9 and 11.1%, fair in 3.9, 1.0% and 0, and non-diagnostic in 0, 2.0% and 0, respectively. Patients were divided into insulin therapy group and oral medication group, the image quality were excellent in 50.7 and 62.5%, very good in 33.3 and 30.8%, good in 10.7 and 5.8%, fair in 2.7 and 1.0%, and non-diagnostic in 2.7% and 0, respectively. Patients with blood glucose at time of FDG injection >7.77 mmol/L had significantly lower odds of excellent image quality (p = 0.021) than those with 5.55-7.77 mmol/L or <5.55 mmol/L, while no significant difference was observed between the latter two groups (p = 0.262). 47 patients (26.3%) exhibited completely viable myocardium, 89 patients (49.7%) had partially viable myocardium, and 43 patients (24.0%) showed nonviable myocardium. None of the patients had severe adverse reactions.

The precise oral glucose loading protocol prior to ¹⁸F-FDG injection is feasible for clinical application.