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Rebecca Boyle

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Review Open access Jul 2026

Impact of “Asymptomatic,” Radiographic Foraminal Stenosis on Lumbar Spine Surgery Outcomes: A Systematic Review

Study Design Systematic Review. Objectives Lumbar foraminal stenosis (LFS) is a common finding on spine imaging. While surgery is indicated for symptomatic LFS, the clinical impact of incidentally found asymptomatic LFS (aLFS) on surgical outcomes remains unclear. This study aims to evaluate the influence of aLFS on reoperation rates and functional outcomes following lumbar spine surgery. Methods A systematic search of PubMed, Embase, MEDLINE, and the Cochrane Library was conducted. Eight of 795 records met inclusion criteria and encompassed 1,744 adult patients undergoing lumbar spinal surgery, of whom 468 (26.8%) had aLFS. Due to heterogeneity in LFS classification, surgical procedures, follow-up duration, and patient-reported outcome measures (PROMs), quantitative pooling was not feasible and a structured narrative synthesis was performed. Study characteristics, patient demographics, surgical details, LFS classification methods, PROMs, and reoperation events were assessed. Results aLFS was associated in some studies with less postoperative improvement in Oswestry Disability Index and greater residual back and leg pain. Several studies suggested that preoperative aLFS at the surgical level was associated with increased index-level reoperations following decompression (low-moderate certainty). However, no association was found at adjacent levels or with fusion procedures. Conclusions Evidence regarding the prognostic significance of incidental aLFS remains limited, heterogeneous, and low certainty. Association between index-level aLFS and later reoperation should be interpreted cautiously because instability-related factors may be stronger drivers of failure than stenosis severity alone. Current evidence does not support prophylactic treatment of radiographically asymptomatic foraminal stenosis, particularly at adjacent levels in the absence of instability or symptom correlation.

Rebecca Boyle, Tim Xu, Zora C Hahn et al. · 0 citations

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