Zhou Shuai, Yang Zhenbang, Zhang Wei, Liu Shihang, Xiao Qian, Hou Guangzhao, Chen Rui, Han Nuoman, Guo Jiao, Liang Miao, Zhang Qi, Zhang Yingze, Lv Hongzhi
Hebei Orthopaedic Research Institute, Hebei Medical University Third Hospital, No.139 Ziqiang Road, Shijiazhuang, 050051, P.R. China.
School of Public Health, Hebei Medical University, No.361 Zhongshan East Road, Shijiazhuang, 050017, P.R. China.
J Orthop Surg Res. 2025 Jan 10;20(1):38. doi: 10.1186/s13018-024-05353-z.
The postoperative recovery of patients with lumbar disc herniation (LDH) requires further study. This study aimed to establish and validate a predictive model for functional recovery in patients with LDH and explore associated risk factors.
Patients with LDH undergoing PLIF admitted from January 1, 2018 to December 31, 2022 were included, and patient data were prospectively collected through follow-up. The training and validation cohorts were randomly assigned in a 7:3 ratio. To pool data variables LASSO regression was used. The pooled variables were subsequently included in binary logistic regression analyses, construct risk prediction models, and plot nomograms. Additionally, recovery prediction models and interactive web page calculators were developed using R Shiny.
Overall, 1,097 patients with LDH following PLIF were included in this study. Regarding patients' economic and functional scores, 927 (84.5%) received excellent scores. Key indicators significantly were screened. Multivariate analysis showed that age, season, occupation, HDL-C, smoking, weekly exercise time, and osteoporosis were independent risk factors for postoperative recovery. The C-index of the model was 0.776 (95% CI: 0.7312-0.8208) and 0.804 (95% CI: 0.7408-0.8673) for the training and validation cohorts, respectively. The H-L test showed good fitting of the model (all P > 0.05). The DCA curve showed the best clinical efficacy when the threshold probability was in the ranges of 0-0.71 and 0.79-0.84. The interactive web calculator is accessed at https://postoperativerecoveryofldh.shinyapps.io/DynNomapp/ .
The predictive tools derived from this study can provide realistic and personalized expectations of postoperative outcomes for patients undergoing lumbar spine surgery.
腰椎间盘突出症（LDH）患者术后恢复情况仍需进一步研究。本研究旨在建立并验证LDH患者功能恢复的预测模型，并探索相关危险因素。
纳入2018年1月1日至2022年12月31日期间接受后路腰椎椎间融合术（PLIF）的LDH患者，通过随访前瞻性收集患者数据。训练队列和验证队列按7:3的比例随机分配。采用LASSO回归合并数据变量。随后将合并后的变量纳入二元逻辑回归分析，构建风险预测模型并绘制列线图。此外，使用R Shiny开发了恢复预测模型和交互式网页计算器。
本研究共纳入1097例接受PLIF治疗的LDH患者。在患者的经济和功能评分方面，927例（84.5%）获得了优异评分。筛选出了显著的关键指标。多因素分析显示，年龄、季节、职业、高密度脂蛋白胆固醇（HDL-C）、吸烟、每周运动时间和骨质疏松是术后恢复的独立危险因素。该模型在训练队列和验证队列中的C指数分别为0.776（95%CI：0.7312 - 0.8208）和0.804（95%CI：0.7408 - 0.8673）。Hosmer-Lemeshow（H-L）检验显示模型拟合良好（所有P>0.05）。决策曲线分析（DCA）曲线显示，当阈值概率在0 - 0.71和0.79 - 0.84范围内时，临床疗效最佳。交互式网页计算器可通过https://postoperativerecoveryofldh.shinyapps.io/DynNomapp/访问。
本研究得出的预测工具可为接受腰椎手术的患者提供术后结果的现实且个性化预期。
