Predictive factors for postoperative deformity in thoracolumbar burst fractures: a statistical approach

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 treated 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.