Haixia Qi1  · Tao Zhang2  · Lijie Hou3  · Qi LI4  · Ruiping Huang3  · Lihua Ma1,3

Received: 23 December 2024 / Accepted: 29 March 2025 / Published online: 19 April 2025 © The Author(s) 2025, corrected publication 2025

Abstract

Objective This study aimed to comprehensively review the latest advancements in diabetic foot risk prediction models over the past four years to address the severe challenges posed by diabetic foot ulcers, which are among the leading causes of disability and mortality among diabetic patients. Diabetic foot ulcers are characterized by their complex aetiology, pose a grave threat to life and impose enormous social and economic burdens, thus becoming a critical issue in public health that urgently requires attention. By accurately predicting the risk of diabetic foot and implementing early intervention strategies, this study aimed to reduce its incidence and mortality rates.

Methods This study employed a systematic review and comprehensive analysis framework, conducted extensive searches of electronic databases (including PubMed, EMBASE, the Cochrane Library, CNKI, etc.) and supplemented these searches with manual literature collection to ensure comprehensive information coverage. During the literature screening and evalua-tion phase, strict adherence to the predetermined inclusion and exclusion criteria was maintained to guarantee the high qual-ity of the included studies. Further detailed quality assessments, data extraction, and analysis of the selected literature were conducted, with a focus on exploring the construction strategies of risk prediction models, the selection of key variables, the evaluation indicators of model performance, and the validation methods.

Results By comparing and analysing the differences among studies in terms of methodology, model effectiveness, and prac-tical application potential, this study summarized the development trends of diabetic foot risk prediction models and antici-pated future research directions. These findings indicate that with the assistance of advanced diabetic foot risk prediction models, potential risk factors can be identified and addressed early on, thereby effectively reducing the incidence of diabetic foot and significantly improving patients’ quality of life.

Conclusion This study revealed that diabetic foot risk prediction models have significant effects on accurately identifying risk factors and guiding early interventions, serving as effective tools to reduce the incidence of diabetic foot. Through early identification and intervention, the prognosis and quality of life of patients can be significantly improved, providing impor-tant references and guidance for the field of public health.

Keywords Diabetic foot ulcer · High-risk diabetic foot · Diabetes · Prediction model

Gabriele Angelo Vassallo1  · Tommaso Dionisi2,3  · Vittorio De Vita4  · Giuseppe Augello1  ·Antonio Gasbarrini3,5  · Dario Pitocco6  · Giovanni Addolorato2,3

Received: 25 January 2025 / Accepted: 29 March 2025 / Published online: 19 April 2025 © The Author(s) 2025

Abstract

Fecal microbiota transplantation (FMT) has emerged as a potential therapeutic strategy for modulating gut dysbiosis in diabetes mellitus. This review critically evaluates preclinical and clinical evidence on FMT in type 1 (T1D) and type 2 dia-betes (T2D). Studies suggest that FMT can restore microbial diversity, improve glycemic control, and modulate immune responses, with varying effects across diabetes subtypes. In T1D, preclinical models demonstrate that FMT influences regulatory T-cell expansion and β-cell preservation, though clinical translation remains limited. In T2D, FMT has shown transient improvements in insulin sensitivity, with sustained effects observed only in patients with specific microbiome signatures. However, heterogeneity in patient responses, donor variability, and methodological limitations complicate its clinical application. This review highlights the interplay between FMT, immune modulation, and microbial metabolism, advocating for phenotype-stratified trials and multi-omics integration to enhance therapeutic precision.

Keywords Fecal microbiota transplantation · Intestinal Microbiome · Diabetes · Insulin sensitivity · Metabolic syndrome · Beta-cell

Abbreviations

FMT Fecal microbiota transplantation TUDCA Tauroursodeoxycholic acid VEGF Vascular endothelial growth factor SCFAs Short-chain fatty acids MMTT Mixed meal tolerance test FVT Fecal virome transplantation OGTT Oral glucose tolerance test SRB Sulfate-reducing bacteria LSI Lifestyle intervention

Huanjia Qu1  · Lingling Zhou1  · Dong Tang2  · Qiuling Zhang1  · Pu Yang3  · Boyi Yang3  · Junping Shi4

Received: 25 December 2024 / Accepted: 22 March 2025 / Published online: 19 April 2025 © The Author(s) 2025

Abstract

Purpose Type 2 diabetes mellitus (T2DM) is associated with ectopic fat deposition, especially in the liver and pancreas.Therefore, this study aimed to evaluate the relationship between liver fat fraction (LFF), pancreatic fat fraction (PFF), and new-onset T2DM in metabolic dysfunction-associated fatty liver disease (MAFLD) by magnetic resonance imaging (MRI).

Methods This is a retrospective study of patients with MAFLD who underwent abdominal MRI between 2022 and July 2024. LFF and PFF were measured using an axial multi-echo Dixon-based sequence. All participants underwent routine medical history, anthropometric measurements, and laboratory tests. Multivariable stepwise selection models were con-structed to predict PFF and T2DM status based on variables of clinical interest.

Results This study included 80 MAFLD patients with 40 untreated new-onset T2DM and 40 non-T2DM controls. LFF, PFF, and homeostasis model assessment of insulin resistance (HOMA-IR) index were higher in the T2DM group than in the control group. In the new-onset T2DM group, PFF was linearly positively correlated with LFF (rs=0.321, P=0.04) and HOMA-IR (rs=0.350, P=0.03). After adjustment for several metabolic variables, PFF remained an independent risk factor for incident T2DM in MAFLD patients (all P<0.05). The area under the receiver operating characteristic curve for PFF and LFF to predict T2DM was 0.889 and 0.633 (P<0.001 and P=0.03), respectively.

Conclusion In MAFLD patients, PFF, and LFF play a prominent role in new-onset T2DM with high predictive and diag-nostic value.

Keywords Metabolic dysfunction-associated fatty liver disease · Type 2 diabetes mellitus · Liver fat fraction ·Pancreatic fat fraction · Ectopic fat deposition · MRI

Krzysztof Łupina1  · Artur Dziewierz2,3  · Jakub Janczura1  · Zbigniew Siudak1,4

Received: 6 March 2026 / Accepted: 26 April 2026

© The Author(s) 2026

Abstract

Aims To characterize switching among GLP-1 receptor agonists (GLP-1 RAs) in a large private-sector cohort in Poland and to quantify therapy- and patient-level associations with switching while accounting for switching opportunity and calendar-time dynamics.

Methods We conducted a retrospective analysis of GLP-1 RA prescription records from the LUX MED network (2018–2025). Switching was defined as any change in agent between consecutive prescriptions. Patients with more than one pre-scription were included (n=42,423). The primary analysis used a transition-level discrete-time hazard model in which each prescription-to-prescription interval contributed one observation, and the outcome was switching at that interval. Current-therapy contrasts were reported relative to subcutaneous semaglutide. Sensitivity analyses examined alternative temporal parameterizations and additional adjustment for elapsed time.

Results Overall, 29.7% of patients switched at least once and 14.3% switched two or more times. In the transition-level analysis, 12,620 patients contributed 27,095 transitions. After adjustment for opportunity and calendar time, liraglutide was associated with substantially lower odds of switching compared with subcutaneous semaglutide (OR, 0.02; 95% CI, 0.01–0.03), whereas oral semaglutide (OR, 1.30; 95% CI, 0.78–2.17) and dulaglutide (OR, 1.70; 95% CI, 0.95–3.04) did not differ significantly. Temporal analyses revealed peaks consistent with episodic substitution and accelerated tirzepatide uptake after market entry. The principal associations remained directionally consistent in sensitivity analyses.

Conclusions Switching among GLP-1 RAs is common and time-dependent. Time-aware modelling identified therapy-spe-cific switching patterns and pronounced temporal variation; reasons for switching remain unmeasured, and the observed associations should be interpreted as hypothesis-generating.

Keywords Glucagon-like peptide-1 receptor agonists · Tirzepatide · Treatment switching · Real-world evidence · Private healthcare · Obesity