Hongmou Zhao

Impaired bone healing in diabetes continues to present a major challenge in orthopedic and regenerative medicine. The compromised osseous regeneration typically stems from a complex pathological cascade—namely, persistent local hyperglycemia, excessive reactive oxygen species (ROS), impaired neurovascular coupling, sustained low-grade inflammation, altered insulin signaling, and the deleterious deposition of advanced glycation end products. Together, these systemic and microenvironmental anomalies impede endogenous repair, potentially culminating in delayed union or frank non-union. To overcome these limitations, functional and stimuli-responsive (smart) hydrogel networks have emerged as a versatile therapeutic platform. These matrices provide sustained local delivery, while selected responsive chemistries couple release or degradation to glucose, ROS, proteases, pH, or externally applied light. Temperature-dependent gelation, antioxidant activity, and electrical conductivity are distinguished from pathological-signal-triggered release. In this review, we summarize current progress in the rational design and implementation of functional and stimuli-responsive hydrogels for diabetic bone repair. We evaluate their biological mechanisms together with responsive chemistry, tested trigger levels, release and degradation kinetics, mechanical properties, and the relevance of each experimental model, concluding with prospective strategies to guide subsequent biomaterial innovation and clinical translation in this domain.

Background: Evidence on perioperative factors associated with postoperative outcomes for diabetic Charcot neuroarthropathy (DCN) of the foot and ankle remains limited. We evaluated whether routinely available clinical, laboratory, and surgery-related variables were associated with postoperative failure-free survival (po-FFS) after arthrodesis. Methods: This single-center retrospective exploratory prognostic factor study screened consecutive surgically treated patients with DCN between June 2017 and October 2025. The final cohort included 83 patients with Eichenholtz stage III DCN of the foot or ankle treated with arthrodesis and follow-up sufficient for early endpoint ascertainment. The primary endpoint was early po-FFS. Kaplan-Meier analyses, Cox regression, sensitivity analyses, and supplementary analyses of anatomic variables and prior ulcer history were performed. Results: Thirty-five of 83 patients (42.2%) experienced postoperative failure, and 48 (57.8%) remained stable during follow-up. The estimated overall po-FFS was 96.0% (95% CI, 88.1%-98.7%) at 6 months and 45.3% (95% CI, 31.2%-58.5%) at 12 months. In the primary multivariable model, longer duration of diabetes (adjusted hazard ratio [HR] 1.091, 95% CI 1.034-1.150; P = .001) and smoking (adjusted HR 2.579, 95% CI 1.119-5.946; P = .026) were associated with worse po-FFS. Glycated hemoglobin (HbA1c) was not independently associated with po-FFS (adjusted HR 1.229, 95% CI 0.972-1.555; P = .085). In sensitivity analyses, duration of diabetes and smoking remained the most consistent factors. Fasting blood glucose was associated with worse po-FFS only in the alternative model replacing HbA1c. Brodsky classification and prior ulcer history were not independently associated with po-FFS after adjustment. Conclusion: Among patients with Eichenholtz stage III DCN of the foot or ankle treated with arthrodesis, diabetes duration and smoking showed the most consistent associations with early po-FFS. Glycemic markers may add information, but findings were marker-dependent. These exploratory findings require validation in larger prospective cohorts with longer follow-up. Level of Evidence: Level III, retrospective prognostic cohort study.

Objectives: Long-term survivorship of total ankle arthroplasty depends on coronal alignment. Short-term complications include wound infection. Conventional extramedullary guides need repeated fluoroscopy, prolonging operative and tourniquet time, increasing contamination, and wound complications. Patient-specific instrumentation has long cycles and high costs. Material and Methods: This study presents a robotic-assisted technique for Infinity total ankle arthroplasty using the TiRobot system. After O-arm 3D scanning, the guide pin trajectory was planned perpendicular to the tibial mechanical axis in coronal and sagittal planes, and centered in the ankle mortise axially. The robotic arm rigidly placed the pins, followed by standard osteotomy and implantation. A comparative review included 42 robotic-assisted and 71 conventional cases. Results: In the robotic group, the mean operative time was 75.4±10.2 min, tourniquet time was 60.5±8.5 min. Mean fluoroscopic shots were 28.2±3.4, with a mean time of 32 seconds—about 50% less radiation than conventional methods. Minor delayed wound healing occurred in 2 cases (5%), lower than reported rates. The O-arm scan added a single radiation bolus to the patient but eliminated the surgeon’s fluoroscopy exposure. Conclusion: Robotic navigation-assisted total ankle arthroplasty provides precise pin placement, reduces radiation, shortens tourniquet time, and may lower wound complications. It may shorten the learning curve for less experienced surgeons and merits broader use. Long-term survivorship data are still needed.

Objective: This cross-sectional study was designed to explore the independent link between the HbA1c/high-density lipoprotein cholesterol ratio (HHR) and diabetic foot ulcer (DFU) among adult Han patients from northwest China. Methods: Clinical data from 866 patients with type 2 diabetes mellitus (T2DM) were retrospectively analyzed in Honghui Hospital of Xi’an Jiaotong University between July 2023 and March 2026. Logistic regression models were applied to estimate the association between HHR and DFU risk, with smooth curve fitting (SCF) used to characterize potential nonlinear trends. Discriminatory capacity of HHR for DFU detection was assessed using receiver operating characteristic (ROC) curve, and quantified the area under the curve (AUC). In addition, decision curve analysis (DCA) was conducted to evaluate the clinical net benefit of HHR. Results: After adjusting for all covariates, the logistic regression demonstrated that every one-unit elevation in HHR was correlated with a remarkable increase in DFU risk, corresponding to an OR of 1.327 (95% CI: 1.222–1.440). Compared to the lowest tertile, the highest tertile of HHR was linked to a substantially elevated DFU risk, with an OR of 5.366 (95% CI: 2.939–9.798). The SCF also exhibited similar trends. Moreover, compared with the triglyceride-glucose (TyG) index (AUC = 0.649, 95% CI: 0.609–0.690), the HHR yielded a significantly larger area under the ROC curve of 0.704 (95% CI: 0.663–0.745) for DFU identification. Furthermore, the results of DCA demonstrated that HHR conferred a higher net clinical benefit across a wide range of threshold probabilities for DFU identification. Conclusion: This study demonstrated a positive correlation between DFU and the combined glucose-lipid metabolic dysfunction status represented by increased HHR in northwest Chinese Han adults with T2DM, and offer supportive evidence for the promising role of HHR as an auxiliary metabolic marker for the evaluation of DFU. Accordingly, closer DFU assessment and foot examination may be essential for T2DM individuals with elevated HHR. However, additional large-sample prospective investigations are still required to validate the putative causal associations suggested by the present observational data.

Objective: The study aimed to investigate the relationship between neutrophil percentage-to-albumin ratio (NPAR) and diabetic foot ulcer (DFU) in Chinese adults, further establish a clinical predictive model, and verify its effectiveness. Methods: We retrospectively collected and analyzed clinical data from a total of 1,002 diabetic patients at Honghui Hospital of Xi’an Jiaotong University between January 2024 and January 2026. The association between the NPAR and DFU risk was assessed using a logistic regression. Moreover, the nonlinear relationship was further characterized through smooth curve fitting and generalized additive model analysis. The predictors were identified via the least absolute shrinkage and selection operator and multivariate logistic analysis. The discrimination and calibration of the nomogram were validated by receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) was used to evaluate clinical usefulness and net benefits of the prediction model. Results: The multivariate logistic regression analysis demonstrated that NPAR (odds ratio [OR] =1.303, 95% confidence intervals [CI]: 1.212–1.402), age (OR = 1.058, 95% CI: 1.032–1.083), sex (female vs. male, OR = 0.475, 95% CI: 0.281–0.802), body mass index (20–25 kg/m² vs. <20 kg/m², OR = 0.184, 95% CI: 0.094–0.359; ≥25 kg/m² vs. <20 kg/m², OR = 0.445, 95% CI: 0.252–0.788), smoke (yes vs. no, OR = 1.735, 95% CI: 1.023–2.941), peripheral vascular disease (yes vs. no, OR = 5.522, 95% CI: 3.428–8.896), peripheral neuropathy (yes vs. no, OR = 6.914, 95% CI: 4.114–11.618), and hemoglobin (OR = 0.981, 95% CI: 0.967–0.996) were risk-associated indicators for DFU. The calibration curves for the training and validation cohorts both revealed good agreement. In addition, the area under the ROC curve values in the training and validation cohorts were 0.892 (95% CI: 0.864–0.919) and 0.877 (95% CI: 0.831–0.922), respectively, indicating good predictive discrimination. The DCA showed that the nomogram could provide clinical usefulness and net benefit. Conclusion: This study indicated a positive relationship between DFU risk and the integrated inflammatory-nutritional status represented by NPAR in the Chinese diabetic population. The DFU prediction model incorporating NPAR was validated for its effectiveness and clinical utility, providing evidence for the potential of NPAR as a risk-associated indicator measured at DFU diagnosis.

Hallux valgus (HV) assessment commonly relies on measuring the hallux valgus angle (HVA) and intermetatarsal angle (IMA) on weight-bearing radiographs. Manual measurement is time-consuming and subject to intra- and inter-observer variability. Deep learning (DL) methods may automate angle measurement with high accuracy, but prior studies often lacked control groups and comparisons across surgeon experience levels. We developed a DL model based on UNet++ with a MobileNetV2 backbone to segment bone axes, followed by a linear regression module to predict HVA and IMA. The dataset comprised 2,468 weight-bearing radiographs (1,920 HV; 548 control) from 2,124 participants. Performance metrics included mean absolute error (MAE), root mean squared error (RMSE), intraclass correlation coefficient (ICC), and outlier rates; model results were compared with measurements from two foot and ankle surgeons of differing experience. In the HV group, the model achieved ICCs of 0.902 for HVA and 0.887 for IMA; in the control group, ICCs were 0.821 (HVA) and 0.898 (IMA). For IMA, the model demonstrated lower MAE and fewer outliers than the surgeons (HV outliers 4.6% vs. 6.6-7.9%; control 4.8% vs. 6.0-9.5%). Average measurement time was 0.13 s per radiograph for the model versus 1.8-2.6 min manually. The proposed DL model automates HVA and IMA measurement with accuracy and reliability comparable to experienced surgeons while markedly improving efficiency. The model also showed consistent performance across HV and control radiographs in our cohort, supporting potential clinical application pending external validation.

To review the pathological characteristics of calcaneal fracture malunions and the research progress of surgical treatment, so as to provide a reference for standardized clinical diagnosis and treatment. The relevant research literature on calcaneal fracture malunions at home and abroad in recent years was reviewed. The pathological characteristics, imaging manifestations, classification, and the latest surgical treatment strategies of calcaneal fracture malunions were systematically expounded. Malunion may ensue after calcaneal fractures if conservative treatment fails or surgical intervention is improperly performed, leading to abnormal foot biomechanics and severe functional impairment. Typical pathological changes include three-dimensional morphological disorders of the calcaneus (abnormal width, height loss, and varus-valgus deformity), collapse of the subtalar articular surface accompanied by joint mismatch, secondary joint degeneration, Achilles tendon contracture, and lateral soft tissue impingement syndrome. Given the complex pathological anatomy after malunion, surgical plans should be individually tailored. The clinically used Stephens-Sanders classification and Zwipp-Rammelt classification provide a reliable basis for the accurate selection of treatment modalities. Staged treatments such as subtalar arthrodesis, osteotomy correction, and soft tissue release can effectively improve ankle and foot function. In recent years, the biomechanical mechanisms, imaging evaluation systems, and reconstructive surgical strategies of calcaneal fracture malunion have become research hotspots. The selection of treatment plans should take into account specific clinical symptoms and morphological changes of the calcaneus, which is crucial for subsequent recovery. In the future, it is necessary to focus on individual differences, promote the integration of diagnosis and treatment, establish evidence-based guidelines, and achieve accurate and long-term deformity correction and functional reconstruction.

A fully automated, end-to-end deep learning framework was developed and validated for accurate and reliable estimation of the hallux valgus angle (HVA) and