PDF(Pubmed)
Abstract：
BACKGROUND: The Ilizarov bone transport technique is widely recognised as an effective method for treating large segment bone defects in clinical practice. However, axial deviation is a common complication in the treatment of tibial large segment bone defects, which can have a serious impact on the clinical efficacy of bone transport. Our study aims to construct and validate a nomogram for predicting axial deviation of tibial bone transport.
METHODS: This study retrospectively collected data from 363 patients who underwent the tibial Ilizarov technique for bone transport. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for axial deviation, which were later used to construct a nomogram. The nomogram was evaluated using the decision curve analysis (DCA), the calibration curve, and the area under the receiver operating characteristic curve (AUC).
RESULTS: Of the 363 patients who underwent Ilizarov tibial bone transport, 31.7% (115/363) experienced axial deviation. Multivariate logistic regression analysis showed that gender, height, defect site, and external fixation index were important risk factors for axial deviation. The AUC value of the nomogram model was 0.705. The calibration curve and the decision curve analysis showed a good consistency between the actual axial deviation and the predicted probability.
CONCLUSIONS: The model assigns a quantitative risk score to each variable, which can be used to predict the risk of axial deviation during tibial bone transport.
METHODS: This study retrospectively collected data from 363 patients who underwent the tibial Ilizarov technique for bone transport. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for axial deviation, which were later used to construct a nomogram. The nomogram was evaluated using the decision curve analysis (DCA), the calibration curve, and the area under the receiver operating characteristic curve (AUC).
RESULTS: Of the 363 patients who underwent Ilizarov tibial bone transport, 31.7% (115/363) experienced axial deviation. Multivariate logistic regression analysis showed that gender, height, defect site, and external fixation index were important risk factors for axial deviation. The AUC value of the nomogram model was 0.705. The calibration curve and the decision curve analysis showed a good consistency between the actual axial deviation and the predicted probability.
CONCLUSIONS: The model assigns a quantitative risk score to each variable, which can be used to predict the risk of axial deviation during tibial bone transport.
摘要：
背景：在临床实践中，Ilizarov骨运输技术被广泛认为是治疗大段骨缺损的有效方法。然而,轴偏移是胫骨大段骨缺损治疗中常见的并发症,会严重影响骨转运的临床疗效。我们的研究旨在构建和验证用于预测胫骨骨运输轴向偏差的列线图。
方法：本研究回顾性收集了363例接受胫骨Ilizarov技术骨运输的患者的数据。进行单因素和多因素logistic回归分析以确定轴向偏离的独立危险因素。后来被用来构造列线图。使用决策曲线分析(DCA)评估列线图，校正曲线,和受试者工作特征曲线下面积(AUC)。
结果：在363例接受Ilizarov胫骨骨运输的患者中，31.7%(115/363)出现轴向偏差。多因素logistic回归分析显示,性别,高度,缺陷部位,外固定架指数是轴位偏离的重要危险因素。列线图模型的AUC值为0.705。校准曲线和决策曲线分析显示实际轴向偏差与预测概率之间具有良好的一致性。
结论：模型为每个变量分配定量风险评分，可用于预测胫骨骨运输过程中轴向偏离的风险。
方法：本研究回顾性收集了363例接受胫骨Ilizarov技术骨运输的患者的数据。进行单因素和多因素logistic回归分析以确定轴向偏离的独立危险因素。后来被用来构造列线图。使用决策曲线分析(DCA)评估列线图，校正曲线,和受试者工作特征曲线下面积(AUC)。
结果：在363例接受Ilizarov胫骨骨运输的患者中，31.7%(115/363)出现轴向偏差。多因素logistic回归分析显示,性别,高度,缺陷部位,外固定架指数是轴位偏离的重要危险因素。列线图模型的AUC值为0.705。校准曲线和决策曲线分析显示实际轴向偏差与预测概率之间具有良好的一致性。
结论：模型为每个变量分配定量风险评分，可用于预测胫骨骨运输过程中轴向偏离的风险。
