Tianjin Hospital, No. 406 Jiefang Southern Road, Hexi District, Tianjin, China.
Graduate School, Tianjin Medical University, Tianjin, China.
Orthop Traumatol Surg Res. 2020 May;106(3):421-427. doi: 10.1016/j.otsr.2019.10.023. Epub 2020 Jan 18.
Due to the particularity of patients with bone tumors, the risk of periprosthetic infection following megaprosthetic replacement is much higher than that of traditional total knee arthroplasty. Unfortunately, few studies specifically reported the risk factors for periprosthetic infection following megaprosthetic replacement. The purposes of the study were to (1) establish a nomogram model, which can provide a reference for clinicians, and patients to reduce the occurrence of periprosthetic infection (2) explore the risk factors for deep infection of megaprosthesis.
A prediction model can be established and has favorable predictive accuracy.
One hundred and seventy-seven megaprostheses were identified. There were 61 female patients and 116 male patients with a mean age of 35 years. The following risk factors were analyzed: tumor site, sex, age, material for prosthetic stem, tumor type, smoking, diabetes, length of bone resection, operation time, chemotherapy, BMI, malignant tumor staging and hematoma formation. Finally, based on the multivariate analysis, the independent risk factors were used to develop a nomogram model.
Univariate Cox regression analysis showed that the chemotherapy, longer operation time and hematoma formation were risk factors for periprosthetic infection. Multivariate Cox regression analysis showed that the chemotherapy, longer operation time and hematoma formation were significant risk factors for periprosthetic infection. The nomogram model was established using these significant risk factors, with a C-index of 0.766 and an acceptable consistency according to the internal validation, indicating that the prediction model had favorable predictive accuracy.
This study has important implications for the future investigations of prevention of periprosthetic infection. The nomogram model identifies high-risk patients for whom attached prophylaxis measures are required. Future studies regarding reduction of incidence of periprosthetic infection should pay close attention to these high-risk patients.
IV, retrospective, cohort study.
由于骨肿瘤患者的特殊性，巨大假体置换后假体周围感染的风险远高于传统的全膝关节置换。不幸的是，很少有研究专门报道巨大假体置换后假体周围感染的危险因素。本研究的目的是：（1）建立列线图模型，为临床医生和患者提供参考，以降低假体周围感染的发生；（2）探讨巨大假体深部感染的危险因素。
可以建立一个预测模型，并具有良好的预测准确性。
共确定 177 例巨大假体，其中女性 61 例，男性 116 例，平均年龄 35 岁。分析了以下危险因素：肿瘤部位、性别、年龄、假体柄材料、肿瘤类型、吸烟、糖尿病、骨切除长度、手术时间、化疗、BMI、恶性肿瘤分期和血肿形成。最后，基于多变量分析，采用独立危险因素建立列线图模型。
单因素 Cox 回归分析显示，化疗、手术时间较长和血肿形成是假体周围感染的危险因素。多因素 Cox 回归分析显示，化疗、手术时间较长和血肿形成是假体周围感染的显著危险因素。该列线图模型是使用这些显著的危险因素建立的，内部验证的 C 指数为 0.766，一致性可接受，表明预测模型具有良好的预测准确性。
本研究对假体周围感染预防的未来研究具有重要意义。该列线图模型确定了需要附加预防措施的高危患者。未来关于降低假体周围感染发生率的研究应密切关注这些高危患者。
IV，回顾性队列研究。
