Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion
Abstract Objective 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. Method Patients with LDH undergoing PLIF...
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| Language: | English |
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BMC
2025-01-01
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| Series: | Journal of Orthopaedic Surgery and Research |
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| Online Access: | https://doi.org/10.1186/s13018-024-05353-z |
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| author | Shuai Zhou Zhenbang Yang Wei Zhang Shihang Liu Qian Xiao Guangzhao Hou Rui Chen Nuoman Han Jiao Guo Miao Liang Qi Zhang Yingze Zhang Hongzhi Lv |
| author_facet | Shuai Zhou Zhenbang Yang Wei Zhang Shihang Liu Qian Xiao Guangzhao Hou Rui Chen Nuoman Han Jiao Guo Miao Liang Qi Zhang Yingze Zhang Hongzhi Lv |
| author_sort | Shuai Zhou |
| collection | DOAJ |
| description | Abstract Objective 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. Method 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. Results 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/ . Conclusion The predictive tools derived from this study can provide realistic and personalized expectations of postoperative outcomes for patients undergoing lumbar spine surgery. |
| format | Article |
| id | doaj-art-79d15b56e3734af6b4788ae2b3b79f6f |
| institution | Kabale University |
| issn | 1749-799X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Orthopaedic Surgery and Research |
| spelling | doaj-art-79d15b56e3734af6b4788ae2b3b79f6f2025-01-12T12:32:37ZengBMCJournal of Orthopaedic Surgery and Research1749-799X2025-01-0120111310.1186/s13018-024-05353-zDevelopment and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusionShuai Zhou0Zhenbang Yang1Wei Zhang2Shihang Liu3Qian Xiao4Guangzhao Hou5Rui Chen6Nuoman Han7Jiao Guo8Miao Liang9Qi Zhang10Yingze Zhang11Hongzhi Lv12Hebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalDepartment of Pathology, Hebei Key Laboratory of Nephrology, Center of Metabolic Diseases and Cancer Research, Hebei Medical UniversityHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalSchool of Public Health, Hebei Medical UniversitySchool of Public Health, Hebei Medical UniversityHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalHebei Orthopaedic Research Institute, Hebei Medical University Third HospitalAbstract Objective 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. Method 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. Results 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/ . Conclusion The predictive tools derived from this study can provide realistic and personalized expectations of postoperative outcomes for patients undergoing lumbar spine surgery.https://doi.org/10.1186/s13018-024-05353-zLDHPostoperative recoveryRisk factorsMachine learningPLIF |
| spellingShingle | Shuai Zhou Zhenbang Yang Wei Zhang Shihang Liu Qian Xiao Guangzhao Hou Rui Chen Nuoman Han Jiao Guo Miao Liang Qi Zhang Yingze Zhang Hongzhi Lv Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion Journal of Orthopaedic Surgery and Research LDH Postoperative recovery Risk factors Machine learning PLIF |
| title | Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion |
| title_full | Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion |
| title_fullStr | Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion |
| title_full_unstemmed | Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion |
| title_short | Development and validation of a predictive model and tool for functional recovery in patients after postero-lateral interbody fusion |
| title_sort | development and validation of a predictive model and tool for functional recovery in patients after postero lateral interbody fusion |
| topic | LDH Postoperative recovery Risk factors Machine learning PLIF |
| url | https://doi.org/10.1186/s13018-024-05353-z |
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