ArticleGlobal spine journal2021
Prediction Models in Degenerative Spine Surgery: A Systematic Review.
Article in Global spine journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Comparison of Machine Learning Models for Predicting Recurrent Lumbar Disc Herniation After Percutaneous Endoscopic Lumbar Discectomy.Journal of clinical medicine · 2026Article
- Article
- Enhanced prediction of spine surgery outcomes using advanced machine learning techniques and oversampling methods.Health information science and systems · 2025Article
- Review
- The future is now: How AI is reshaping spine care.North American Spine Society journal · 2025Article
- Identifying preoperative radiographic metrics to guide surgical selection in lumbar spondylolisthesis and stenosis.North American Spine Society journal · 2025Article
- Prediction Tools in Spine Surgery: A Narrative Review.Spine surgery and related research · 2025Review
- Accuracy of Pedicle Screw Placement Using the ExcelsiusGPS Robotic Navigation Platform: An Analysis of 728 Screws.International journal of spine surgery · 2024Article
- The strategic use of Big Data - A study protocol for a multicenter clinical trial testing if the use of the Swespine Dialogue Support alter outcomes in degenerative spine surgery.BMC musculoskeletal disorders · 2024Article
- Using Machine Learning Models to Identify Factors Associated With 30-Day Readmissions After Posterior Cervical Fusions: A Longitudinal Cohort Study.Neurospine · 2024Article
- Advancing spine care through AI and machine learning: overview and applications.EFORT open reviews · 2024Review
- Development and validation of a point-of-care clinical risk score to predict surgical site complication-associated readmissions following open spine surgery.Journal of spine surgery (Hong Kong) · 2024Article
- Clinical Decision Support System Used in Spinal Disorders: Scoping Review.Journal of medical Internet research · 2024Article
- Development of a Prediction Model for Significant Adverse Outcome After Spine Surgery.Global spine journal · 2024Article
- Leveraging web-based prediction calculators to set patient expectations for elective spine surgery: a qualitative study to inform implementation.BMC medical informatics and decision making · 2023Article
- Prospects of returning to work after lumbar spine surgery for patients considering disability pension: a nationwide study based on data from the Norwegian Registry for Spine Surgery.Occupational and environmental medicine · 2023Article
- Article
- Development and validation of a point-of-care clinical risk score to predict surgical site infection following open spinal fusion.North American Spine Society journal · 2023Article
- Social Determinants of Health Influence Early Outcomes Following Lumbar Spine Surgery.Ochsner journal · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
STUDY
designSystematic review.
objectivesTo review the existing literature of prediction models in degenerative spinal surgery.
methodsReview of PubMed/Medline and Embase databases was conducted to identify articles between January 1, 2000 and March 1, 2020 that reported prediction model performance for outcomes following elective degenerative spine surgery.
resultsThirty-one articles were included. Twenty studies were of thoracolumbar, 5 were of cervical, and 6 included all spine patients. Five studies were externally validated. Prediction models were developed using machine learning (42%) and logistic regression (42%) as well as other techniques. Web-based calculators were included in 45% of published articles. Various outcomes were investigated, including complications, infection, length of stay, discharge disposition, reoperation, readmission, disability score, back pain, leg pain, return to work, and opioid dependence.
conclusionsSignificant heterogeneity exists in methods used to develop prediction models of postoperative outcomes after degenerative spine surgery. Most internally validate their scores, but a few have been externally validated. Areas under the curve for most models range from 0.6 to 0.9. Techniques for development are becoming increasingly sophisticated with different machine learning tools. With further external validation, these models can be deployed online for patient, physician, and administrative use, and have the potential to optimize outcomes and maximize value in spine surgery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.