A predictive model for disability in patients with lumbar disc herniation

Background: Lumbar disc herniation may influence patients' daily activities and social interactions; however, no predictive models of disability could be found for patients with lumbar disc herniation. We aimed to explore predictive factors for disability in patients with lumbar disc herniation. Methods: The sample included 216 patients recruited from the orthopedic outpatient clinics at a medical center in northern Taiwan. Data were collected on patients' pain, fatigue, depression, disability, and demographics. Hierarchical multiple regression analysis was used in model verification. Path analysis was used to investigate causal relationships between disability and other factors. Results: In path analysis, the most influential factor affecting the disability level was the pain level (standardized regression coefficient, b = 0.746), followed by the fatigue level (b = 0.138) and depression level (b = 0.100). The depression level was directly affected by the fatigue level (b = 0.416) and the pain level (b = 0.367), the fatigue level was directly affected by the pain level (b = 0.538), and the pain level was directly affected by age (b = 0.140) and previous surgery (b = 0.260). Conclusions: We recommend that health-care providers regularly assess and treat pain and depression to reduce/prevent disability among patients with lumbar disc herniation, even among those who are apparently functioning well in the community.