Department of Orthopedics, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, PR China; Jiangxi Provincial Key Laboratory of Spine and Spinal Cord Diseases, Nanchang, PR China.
Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, PR China.
World Neurosurg. 2024 Sep;189:e807-e813. doi: 10.1016/j.wneu.2024.07.009. Epub 2024 Jul 8.
This study aimed to establish a predictive nomogram model for recollapse of fractured vertebra after posterior pedicle screw fixation in thoracolumbar fractures (TLFs).
Patients undergoing posterior pedicle screw fixation for TLFs at our hospital between January 2016 and December 2021 were retrospectively reviewed. Patients were divided into 2 groups according to the presence or absence of recollapse of the fractured vertebra at the final follow-up. The predictors for fractured vertebra recollapse were identified by univariate and multivariable logistic regression analysis, and a nomogram model was developed. The prediction performance and internal validation were established.
A total of 224 patients were included in this study. Of these, 46 (20.5%) patients developed recollapse of fractured vertebra. Age, thoracic and lumbar injury severity score, screw distribution in the fractured vertebra, and anterior vertebral height compression ratio were associated with vertebral recollapse. These predictors were used to construct a predictive nomogram. The area under the receiver operating characteristic curve of the nomogram model was 0.891. The concordance index was 0.891, and it was 0.877 with bootstrapping validation. The calibration curves and decision curve analysis also suggested that the nomogram model had excellent predictive performances for fractured vertebra recollapse.
A clinical nomogram incorporating 4 variables was constructed to predict fractured vertebra recollapse after posterior pedicle screw fixation for TLFs. The nomogram demonstrated good calibration and discriminative abilities, which may help clinicians to make better treatment decisions.
本研究旨在建立一个预测胸腰椎骨折（TLFs）后路椎弓根螺钉固定后骨折椎体再塌陷的列线图模型。
回顾性分析 2016 年 1 月至 2021 年 12 月在我院接受后路椎弓根螺钉固定 TLFs 的患者。根据最终随访时骨折椎体是否再塌陷，将患者分为两组。采用单因素和多因素逻辑回归分析确定骨折椎体再塌陷的预测因素，并建立列线图模型。建立预测性能和内部验证。
本研究共纳入 224 例患者，其中 46 例（20.5%）患者发生骨折椎体再塌陷。年龄、胸腰椎损伤严重程度评分、骨折椎体螺钉分布、前方椎体高度压缩比与椎体再塌陷有关。这些预测因素被用来构建一个预测列线图。列线图模型的受试者工作特征曲线下面积为 0.891。一致性指数为 0.891，bootstrap 验证为 0.877。校准曲线和决策曲线分析也表明，该列线图模型对骨折椎体再塌陷具有良好的预测性能。
构建了一个包含 4 个变量的临床列线图，以预测 TLFs 后路椎弓根螺钉固定后骨折椎体再塌陷。该列线图具有良好的校准和判别能力，可能有助于临床医生做出更好的治疗决策。
