Introduction: There is conflicting data on the risk factors for recurrent lumbar disc herniation (rLDH). Most of the predictors for rLDH identified so far are acquired risk factors or radiological factors at the level of the herniation. Whole lumbar spine (WLS) morphometry has not been evaluated as a possible predictor of rLDH.
Objectives: We aimed to evaluate if preoperative spinal morphometry can predict the occurrence of rLDH requiring revision surgery.
Methods: This retrospective case-control study on 250 patients included 45 patients operated for rLDH, 180 controls without rLDH who had previously undergone microdiscectomy for a single level lumbar disc prolapse, and a holdout validation set of 25 patients. Morphometric variables related to the WLS were recorded in addition to previously identified predictors of rLDH. Logistic regression (LR) analysis was performed to identify independent predictors of rLDH.
Results: LR yielded four predictors of which two were WLS morphometric variables. While increasing age and smoking positively predicted rLDH, increasing WLS interfacet distance and WLS dural-sac circumference negatively predicted rLDH. The LR model was statistically significant, χ2 (4) =15.98, P = 0.003, and correctly classified 80.3% of cases. On validation, the model demonstrated a fair accuracy in predicting rLDH (accuracy: 0.80, AUC: 0.70).
Conclusions: Larger mean lumbar bony canals and dural sacs protect from the occurrence of symptomatic rLDH. These WLS morphometric variables should be included in future risk stratification algorithms for lumbar disc disease. In addition to the previously recognized risk factors, our study points to an underlying developmental predisposition for rLDH.
Keywords: Morphometry; predictive analysis; recurrent lumbar disc herniation; whole lumbar spine.