Journal of Orthopaedic Surgery and Research (Dec 2024)

Risk factors analysis and predictive model of degree I degenerative lumbar spondylolisthesis

  • RuiYang Wang,
  • Neng Ru,
  • Qing Liu,
  • Fan Zhang,
  • Yu Wu,
  • ChangJin Guo,
  • Jie Liang

DOI
https://doi.org/10.1186/s13018-024-05346-y
Journal volume & issue
Vol. 19, no. 1
pp. 1 – 11

Abstract

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Abstract Study design Retrospective Case-Control Study. Background There have been some previous studies on the risk factors associated with lumbar spondylolisthesis, but there are few studies on the risk factors for disease progression in mild degenerative lumbar spondylolisthesis (DLS). To analyze the risk factors associated with aggravation of spondylolisthesis in patients with grade I degenerative spondylolisthesis and construct a prediction model. Methods We conducted a retrospective analysis of 220 patients diagnosed with DLS who were admitted to our hospital between January 2019 and January 2023. Data collected included gender, age, body mass index (BMI), diabetes, hypertension, occupation, and imaging parameters. Results A total of 220 patients were included in this study, including 111 males and 109 females; 178 patients with no aggravation of lumbar spondylolisthesis (group A) and 42 patients with aggravation of lumbar spondylolisthesis (group B). Progression of grade I DLS was associated with single factors such as age, BMI, Occupation, vertebral CT value, facet joint angle (FJA), Modic change (MC), Pfirrmann grade of intervertebral disc (PG), Facet joint effusion (FJE), osteophyte formation, and Percentage of the Fat Infiltration (FIA%) of multifidus muscle (MM). BMI, FJA, PG, and FI% of MM had a significant impact on disease progression in lumbar spondylolisthesis. Conclusion BMI, FJA, PG, and FIA% of MM were independent risk factors for the progression of degenerative spondylolisthesis. The risk prediction model was established by including the above four variables and nomograms were drawn. The internal validation proved that the model had good discrimination, calibration, and clinical practicability.

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