ArticleJournal of orthopaedic surgery and research2024
Development and validation of a nomogram to predict the risk of adjacent segment disease after transforaminal lumbar interbody fusion in patients with lumbar degenerative diseases.
Article in Journal of orthopaedic surgery and research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence for prediction of clinical response and therapeutic value in interventional pain management: a scoping review.Frontiers in digital health · 2026Pooled it
- Development and validation of explainable machine learning models to predict the risk of adjacent segment disease after lumbar fusion surgery.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Sarcopenia, paraspinal muscle degeneration, and bone quality as prognostic factors for adjacent segment degeneration or disease after lumbar fusion: a systematic review and meta-analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Letter to the editor concerning "Do all symptomatic adjacent segment diseases (ASD) require surgery? A prognostic classification and predictors of surgical treatment of lumbar ASD" by RM Kanna, et al. (Eur spine J [2025]: doi: 10.1007/s00586-025-08797-x).European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- Answer to the letter to the editor of D. Li, et al. concerning "Do all symptomatic adjacent segment diseases (ASD) require surgery? A prognostic classification and predictors of surgical treatment of lumbar ASD" by RM Kanna, et al. (Eur Spine J [2025]: doi: 10.1007/s00586-025-08797-x).European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- The influence of the interfacing angle between the pedicle screw and support rods on the clinical outcomes after posterior lumbar-sacral topping-off surgery: A retrospective clinical study.Journal of orthopaedic surgery and research · 2025Observational
- Biomechanical effects of screw loosening after lumbar PEEK rod and titanium rod fixation: a finite element analysis.Frontiers in bioengineering and biotechnology · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundAdjacent segment disease (ASD) is a common and serious complication that can develop in the mid- to long-term after lumbar fusion surgery. However, the underlying mechanisms of ASD are not yet fully understood. This study aimed to develop and validate a risk prediction model for ASD in patients who underwent transforaminal lumbar interbody fusion (TLIF) for lumbar degenerative diseases.
methodsPatients with lumbar degenerative disease who underwent TLIF between January 2015 and December 2016 were included in the retrospective study. The participants were divided into two groups: ASD and non-ASD. Univariate and multivariate logistic regression analyses were performed to identify factors influencing ASD after TLIF surgery. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the model's discrimination, calibration and clinical value, respectively.
resultsA total of 11.5% (59/513) of patients developed ASD. Higher BMI, lower BMD, higher disc grade, and reduced disc height were identified as independent risk factors for ASD after TLIF. The model demonstrated good discrimination in both the training and validation sets, with calibration and Hosmer-Lemeshow tests confirming accuracy, and DCA demonstrating clinical applicability.
conclusionsThe nomogram model demonstrated promise in predicting ASD in patients who underwent TLIF, aiding clinicians in selecting the most suitable surgical approach and optimizing surgical decisions.
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