Background:
The management of recurrent lumbar disc herniation (rLDH) lacks a consensus. Consequently, the choice between repeat microdiscectomy (MD) without fusion, discectomy with fusion, or endoscopic discectomy without fusion typically hinges on the surgeon’s expertise. This study conducts a comparative analysis of postoperative outcomes among these three techniques and proposes a straightforward classification system for rLDH aimed at optimizing management.
Patients and Methods:
We examined the patients treated for rLDH at our institution. Based on the presence of facet resection, Modic-2 changes, and segmental instability, they patients were categorized into three groups: Types I, II, and III rLDH managed by repeat MD without fusion, MD with transforaminal lumbar interbody fusion (TLIF) (MD + TLIF), and transforaminal endoscopic discectomy (TFED), respectively.
Results:
A total of 127 patients were included: 52 underwent MD + TLIF, 50 underwent MD alone, and 25 underwent TFED. Recurrence rates were 20%, 12%, and 0% for MD alone, TFED, and MD + TLIF, respectively. A facetectomy exceeding 75% correlated with an 84.6% recurrence risk, while segmental instability correlated with a 100% recurrence rate. Modic-2 changes were identified in 86.7% and 100% of patients experiencing recurrence following MD and TFED, respectively. TFED exhibited the lowest risk of durotomy (4%), the shortest operative time (70.80 ± 16.5), the least blood loss (33.60 ± 8.1), and the most favorable Visual Analog Scale score, and Oswestry Disability Index quality of life assessment at 2 years. No statistically significant differences were observed in these parameters between MD alone and MD + TLIF. Based on this analysis, a novel classification system for recurrent disc herniation was proposed.
Conclusion:
In young patients without segmental instability, prior facetectomy, and Modic-2 changes, TFED was available should take precedence over repeat MD alone. However, for patients with segmental instability, MD + TLIF is recommended. The suggested classification system has the potential to enhance patient selection and overall outcomes.