AI Prediction of Neuropathic Pain after Lumbar Disc Herniation-Machine Learning Reveals Influencing Factors
Wirries A, Geiger F, Hammad A, Baeumlein M, Schmeller JN, Blümcke I, Jabari S (2022)
Publication Type: Journal article
Publication year: 2022
Journal
Book Volume: 10
Journal Issue: 6
DOI: 10.3390/biomedicines10061319
Abstract
The treatment options for neuropathic pain caused by lumbar disc herniation have been debated controversially in the literature. Whether surgical or conservative therapy makes more sense in individual cases can hardly be answered. We have investigated whether a machine learning-based prediction of outcome, regarding neuropathic pain development, after lumbar disc herniation treatment is possible. The extensive datasets of 123 consecutive patients were used to predict the development of neuropathic pain, measured by a visual analogue scale (VAS) for leg pain and the Oswestry Disability Index (ODI), at 6 weeks, 6 months and 1 year after treatment of lumbar disc herniation in a machine learning approach. Using a decision tree regressor algorithm, a prediction quality within the limits of the minimum clinically important difference for the VAS and ODI value could be achieved. An analysis of the influencing factors of the algorithm reveals the important role of psychological factors as well as body weight and age with pre-existing conditions for an accurate prediction of neuropathic pain. The machine learning algorithm developed here can enable an assessment of the course of treatment after lumbar disc herniation. The early, comparative individual prediction of a therapy outcome is important to avoid unnecessary surgical therapies as well as insufficient conservative therapies and prevent the chronification of neuropathic pain.
Authors with CRIS profile
Julia Nadine Schmeller
Medizinische Fakultät
Ingmar Blümcke
Lehrstuhl für Neuropathologie
Samir Jabari
Institute of Neuropathology
Involved external institutions
Germany (DE)How to cite
APA:
Wirries, A., Geiger, F., Hammad, A., Baeumlein, M., Schmeller, J.N., Blümcke, I., & Jabari, S. (2022). AI Prediction of Neuropathic Pain after Lumbar Disc Herniation-Machine Learning Reveals Influencing Factors. Biomedicines, 10(6). https://doi.org/10.3390/biomedicines10061319
MLA:
Wirries, Andre, et al. "AI Prediction of Neuropathic Pain after Lumbar Disc Herniation-Machine Learning Reveals Influencing Factors." Biomedicines 10.6 (2022).
BibTeX: Download