Analysis of influencing factors and predictive performance of lumbar disc herniation in elderly patients with osteoporosis.

Objective: This study aimed to analyze the influencing factors associated with lumbar disc herniation (LDH) in elderly patients with osteoporosis and to evaluate the predictive performance of multiple clinical indicators for LDH risk, thereby providing evidence for early risk assessment and targeted prevention and treatment strategies. Methods: A single-center retrospective case-control study was conducted at Tianshan Hospital of Traditional Chinese Medicine, Changning District, Shanghai, China. Clinical data of patients aged 60-80 years who underwent lumbar quantitative computed tomography (QCT) examination from January 2023 to January 2025 were collected, and a total of 441 patients were included. In this study, elderly patients were defined as those aged 60-80 years. Osteoporosis was defined as QCT-measured lumbar vertebral trabecular bone mineral density <80 mg/cm³. According to QCT-measured bone mineral density, patients were divided into group A (147 cases, osteoporosis, bone mineral density <80 mg/cm³), group B (162 cases, low bone mass, 80 mg/cm³ ≤ bone mineral density ≤120 mg/cm³), and group C (132 cases, normal bone mass, bone mineral density >120 mg/cm³), and the prevalence of LDH among the three groups was compared. Based on patients' past medical history, clinical manifestations, and imaging findings, group A was further divided into the LDH group (40 cases) and the non-LDH group (107 cases). Differences in general characteristics, laboratory indicators, bone mineral density parameters, lumbar-abdominal muscle endurance, and nutritional indicators between the two groups were compared. Multivariate Logistic regression analysis was used to identify independent risk factors for LDH in elderly patients with osteoporosis, and receiver operating characteristic (ROC) curves were plotted to evaluate the predictive performance of related indicators alone and in combination for LDH in elderly patients with osteoporosis. All statistical analyses were performed using GraphPad Prism 9.0 (GraphPad Software, USA). Results: The incidence of LDH in group A was significantly higher than that in groups B and C, and the differences among groups were statistically significant (P<0.05). Compared with the non-LDH group, the proportions of patients with bone mineral density <60 mg/cm³, estradiol (E2) level <18.35 pmol/L, and lumbar-abdominal muscle endurance <25 s were significantly higher in the LDH group (P<0.05). Multivariate Logistic regression analysis showed that bone mineral density <60 mg/cm³, E2 level <18.35 pmol/L, and lumbar-abdominal muscle endurance <25 s were independent risk factors for LDH in elderly patients with osteoporosis (P<0.05). ROC curve analysis showed that the areas under the curve (AUCs) for bone mineral density, E2 level, and lumbar-abdominal muscle endurance in predicting LDH in elderly patients with osteoporosis were 0.843, 0.847, and 0.826, respectively, while the AUC of the combined prediction was 0.892, and its predictive performance was significantly better than that of any single indicator (P<0.05). Conclusion: The incidence of LDH is significantly increased in elderly patients with osteoporosis, and decreased bone mineral density, reduced E2 levels, and impaired lumbar-abdominal muscle function are closely associated with the occurrence of LDH. Combined assessment of multiple indicators can significantly improve the predictive performance for the risk of LDH in elderly patients with osteoporosis, which is of great significance for early identification of high-risk populations and implementation of targeted interventions in clinical practice.