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首页> 外文期刊>Acta Orthopaedica et Traumatologica Turcica >Predictive factors for postoperative deformity in thoracolumbar burst fractures: a statistical approach
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Predictive factors for postoperative deformity in thoracolumbar burst fractures: a statistical approach

机译:胸腰椎爆裂骨折术后畸形的预测因素:统计学方法

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摘要

Objective: To assess, using statistical analysis, if and to what extent the final outcome of surgical treatment for burst fractures depends on operation type, fracture level and initial deformity severity. Methods: A database of 287 patients with single-vertebral-level thoracic and lumbar spine fractures analysed using simple and multiple linear regression analyses models. The dependent variable was last follow-up (LFU) kyphotic angle and the predictor variables were operation type [anterior approach (AA), posterior short-segment fixation (PSSF) and posterior monosegmental fixation (PMF)], fracture level (T11–L1, L2–L3 and L4–L5) and preoperative kyphotic angle. The models were applied on either the whole sample or on the operation type subgroups. Results: In simple linear regression analysis models, fracture level accounted for 32% and 18% of the variation in LFU kyphotic angle in the AA and PMF subgroups, respectively. In the multiple linear regression models for the same subgroups, up to 40% of the variation in LFU kyphotic angle was accounted for by fracture level. Surgical treatment, as predictor variable, indicated that patients reated by PSSF developed a post-surgical kyphotic angle 8.51° more severe than those treated by AA. However, the model accounted for only 2% of the variation in LFU kyphotic angle. Simple linear regressions performed on each subgroup with preoperative kyphotic angle as the independent variable revealed that the variable accounted for 15% (PSSF subgroup), 17% (AA subgroup) and 34% (PMF subgroup) of the variation in LFU kyphotic angle. Conclusion: All valid regression models displayed modest explanatory power, suggesting that factors other than those taken into consideration are involved.
机译:目的:使用统计学分析评估爆裂性骨折手术治疗的最终结果是否以及在何种程度上取决于手术类型,骨折水平和初始畸形严重程度。方法:使用简单和多元线性回归分析模型对287例单椎体水平的胸椎和腰椎骨折患者进行数据库分析。因变量为上次随访(LFU)后凸角,预测变量为手术类型[前入路(AA),后短节段固定(PSSF)和后单节段固定(PMF)],骨折水平(T11–L1 ,L2-L3和L4-L5)和术前后凸角。这些模型适用于整个样本或操作类型子组。结果:在简单的线性回归分析模型中,AA和PMF亚组的骨折水平分别占LFU后凸角变化的32%和18%。在相同亚组的多元线性回归模型中,骨折水平解释了LFU后凸角变化的40%。手术治疗作为预测变量,表明PSSF治疗的患者比AA治疗的患者术后严重后凸角为8.51°。但是,该模型仅占LFU后凸角变化的2%。对每个亚组进行简单的线性回归分析,以术前后凸角为独立变量,发现该变量占LFU后凸角变化的15%(PSSF亚组),17%(AA亚组)和34%(PMF亚组)。结论:所有有效的回归模型均显示出适度的解释力,表明除考虑因素外还涉及其他因素。

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