ArticleThe spine journal : official journal of the North American Spine Society2026
Radiographic phenotype-driven clustering in lumbar decompression: comparative study of outcome and reoperation risk.
Article in The spine journal : official journal of the North American Spine Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
background contextLumbar spinal canal stenosis (LSCS) presents with various radiographic findings, often including concurrent degenerative changes. Prior studies have investigated the effects of individual radiographic findings and parameters separately using conventional methods such as logistic regression. However, applying these independent effects to real-world patients remains challenging due to an unknown interaction effect among multiple degenerative radiographic findings. PURPOSE: To identify distinct patient phenotypes based on preoperative radiographic findings using unsupervised clustering and to evaluate their associations with postoperative patient-reported outcomes and reoperation rates. STUDY
designRetrospective cohort study. PATIENT SAMPLE: Patients undergoing single-level lumbar decompression. OUTCOME MEASURES: Oswestry Disability Index (ODI), Short Form-12 physical component scale (SF-12 PCS), reoperation rates.
methodsUnsupervised clustering was performed using preoperative radiographic data from standing X-ray imaging and magnetic resonance imaging (MRI). Variable selection was optimized through preliminary correlation analysis, causal assessment using a directed acyclic graph, and expert review. A multivariable mixed-effects model was used to assess the impact of cluster membership on postoperative outcomes. Reoperation rates were compared using Kaplan-Meier survival analysis and Cox proportional hazards models.
resultsUnsupervised clustering identified 4 distinct clusters base on 10 radiographic variables: cluster 1 as "Young and Less Degenerative Spine" (cluster Y), cluster 2 as "Combined Coronal and Sagittal Spondylosis" (cluster CS), cluster 3 as "Coronal Spondylosis Characterized by Laterolisthesis" (cluster C), and cluster 4 as "Sagittal Spondylosis Characterized by Degenerative Spondylolisthesis" (cluster S). Multivariable regression analysis, adjusting for comorbidity, sex, and body mass index have revealed cluster C demonstrated slower improvement in ODI (β = 5.4, SE = 2.7, p=.043) and SF-12 PCS (β=-2.9, SE=1.4, p=.045) compared to cluster Y. Regarding reoperation, cluster CS showed the highest hazard ratio (24.3%, HR=4.18, 95% CI: 1.48-13.07, p=.007) compared to cluster S with the lowest reoperation rate (6.8%).
conclusionUnsupervised clustering based on preoperative radiographic findings identified 4 distinct degenerative phenotypes in LSCS. Patients with coronal spondylosis was associated with slower improvements in disability and function compared to those with minimal degeneration. Additionally, patients with combined sagittal and coronal degeneration exhibited the highest reoperation rates. These findings highlight the clinical relevance of coronal and sagittal degeneration in surgical decision-making.
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