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Open AccessDOI: 10.12307/2026.21640Original Research

Healing characteristics and influencing factors of large-segment infectious bone defect of tibia repaired by bone transfer

Bu Jianwen¹,Xie Zengru¹,Ma Chuang¹

Department of Trauma Orthopedics, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, Xinjiang Uyghur Autonomous Region, China

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Healing characteristics and influencing factors of large-segment infectious bone defect of tibia repaired by bone transfer
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Published In
Chinese Journal of Tissue Engineering Research
Published:January 15, 2026Edition:Vol 1905, Issue 33 • pp. 100-112Citation:Bu Jianwen et al. (2026), Chinese Journal of Tissue Engineering Research
Impact FactorPremier Chinese Biomedical Journal indexed in SinoBioData: Chinese Journal of Tissue Engineering Research (中国组织工程研究).
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Key Takeaways & Executive Findings

  • • Decreased serum bone turnover markers (BSAP, NMID, P1NP) are independently associated with poor healing after Ilizarov bone transfer for large-segment infectious tibial defects. • Soft tissue injury, wound infection, fibula fracture, and early weight-bearing (within 6 weeks) are significant risk factors for delayed or nonunion. • A combined model incorporating these markers and clinical factors can predict healing outcomes with good discrimination and accuracy. • Long-term smoking and diabetes also contribute to poor healing, emphasizing the need for comprehensive preoperative optimization.
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Abstract

BACKGROUND: Severe segmental infectious bone defects of the tibia pose a significant challenge in orthopedic treatment due to persistent infection, poor local blood supply, and poor soft tissue conditions. Although bone transplantation techniques are the main repair method, the healing process is complex and influenced by multiple factors. The underlying mechanisms are not yet fully understood. Therefore, it is necessary to conduct in-depth research on the healing characteristics and influencing factors to optimize the treatment. OBJECTIVE: To explore the healing characteristics and influencing factors of large-segment infectious bone defect of tibia repaired by bone transfer and analyze the influencing factors. METHODS: A total of 98 patients with large-segment infectious bone defect of the tibia treated by Ilizarov bone transfer in The First Affiliated Hospital of Xinjiang Medical University from May 2020 to October 2022 were selected as the study subjects. According to the clinical criteria of delayed or nonunion and union of fractures, they were divided into delayed or nonunion group (n=48) and union group (n=50), and the general data of the two groups were compared. A combined model was constructed. Cox regression analysis was used to evaluate the relationship between fluctuations in serum bone turnover markers (bone-specific alkaline phosphatase, N-terminal midfragment of osteocalcin, and N-terminal propeptide of type I procollagen) and bone healing. Least absolute shrinkage and selection operator regression and multivariate logistic regression were used to analyze risk factors affecting healing. After adjusting for confounders, Cox proportional hazards model analyzed the association of these markers with poor healing. A regression equation y=1-1/(1+e-z) was established for prediction and validated. RESULTS AND CONCLUSION: (1) Significant differences were found between the delayed/nonunion and union groups in long-term smoking history, diabetes, soft tissue injury, fibula fracture, wound infection, weight-bearing within 6 weeks postoperatively, transport direction, transport distance, and levels of bone-specific alkaline phosphatase, N-terminal midfragment of osteocalcin, and N-terminal propeptide of type I procollagen (P < 0.05). (2) The combined model showed that each unit decrease in these markers increased the risk of poor healing by 3%, 2%, and 4%, respectively. (3) LASSO and multivariate logistic regression identified soft tissue injury, weight-bearing within 6 weeks, wound infection, fibula fracture, and decreased levels of these markers as independent risk factors (P < 0.05). (4) Adjusted Cox model showed that bone-specific alkaline phosphatase (HR=0.67, 95%CI: 0.54-0.87, P < 0.001), N-terminal midfragment of osteocalcin (HR=0.80, 95%CI: 0.55-0.99, P < 0.001), and N-terminal propeptide of type I procollagen (HR=0.85, 95%CI: 0.43-0.97, P < 0.001) were significant factors for poor healing. (5) As levels decreased (Q2-Q4), the association increased, with significant trend tests (P trend < 0.05). Bootstrap validation showed good discrimination and accuracy of the prediction model. (6) These findings suggest that decreased serum bone turnover markers are closely related to poor healing after Ilizarov bone transfer, and soft tissue injury, weight-bearing within 6 weeks, wound infection, fibula fracture, and these markers are important factors affecting healing.

1. Introduction

Large-segment infectious bone defects of the tibia often result from lower limb trauma, where infection directly destroys bone tissue and initiates the defect, while the defect provides a pathological basis for persistent infection. The synergistic effect of these factors is key to difficult treatment and poor healing [1-2]. Clinically, the Ilizarov bone transfer technique is commonly used to treat tibial bone defects, based on the principle of 'tension-stress'. This approach involves selecting appropriate external fixation components to exert tension and axial compression, thereby promoting bone defect repair [3-4]. The Ilizarov technique controls infection through thorough debridement and external fixation, uses tension-stress to precisely induce bone regeneration to fill the defect, and simultaneously addresses soft tissue repair and limb alignment correction. It is particularly suitable for large-segment infectious bone defects that are difficult to manage with traditional bone grafting or internal fixation.

Studies have shown that even bone defects larger than 11 cm can heal reliably with Ilizarov external fixation [5]. This technique is simple, low-risk, and can reshape large bone segments and surrounding soft tissues. However, it has drawbacks such as long treatment duration and potential adverse effects on callus formation, leading to postoperative poor healing [6]. Currently, the factors influencing delayed or nonunion after surgery are not fully understood, preventing effective prevention. Bone-specific alkaline phosphatase (BSAP), primarily synthesized and secreted by osteoblasts, is a direct marker of osteoblast activity. It hydrolyzes phosphate esters to release inorganic phosphate, providing substrate for hydroxyapatite deposition and promoting bone matrix calcification.

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Cite This Research Paper
Bu Jianwen, Xie Zengru, Ma Chuang (2026). Healing characteristics and influencing factors of large-segment infectious bone defect of tibia repaired by bone transfer. Chinese Journal of Tissue Engineering Research. https://doi.org/10.12307/2026.21640
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Frequently Asked Questions

What is the main objective of this study?

The study aims to explore the healing characteristics and influencing factors of large-segment infectious bone defects of the tibia repaired by bone transfer, specifically using the Ilizarov technique.

What are the key risk factors for poor healing after Ilizarov bone transfer?

Independent risk factors include soft tissue injury, wound infection, fibula fracture, weight-bearing within 6 weeks postoperatively, and decreased levels of serum bone turnover markers (BSAP, NMID, P1NP).

How do serum bone turnover markers relate to healing outcomes?

Lower levels of BSAP, NMID, and P1NP are associated with a higher risk of delayed or nonunion. Each unit decrease in these markers increases the risk by 3%, 2%, and 4%, respectively.

What is the clinical significance of this study?

The findings can help clinicians identify patients at high risk for poor healing and implement early interventions, such as optimizing soft tissue management, controlling infection, and delaying weight-bearing, to improve outcomes.

What is the predictive model developed in this study?

A regression equation y=1-1/(1+e-z) was established to predict healing outcomes, incorporating significant risk factors and serum markers. The model showed good discrimination and accuracy after Bootstrap validation.

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