Original title: Establishing Central Sensitization Inventory Cut-off Values in patients with Chronic Low Back Pain by Unsupervised Machine Learning
Authors: Xiaoping Zheng, Claudine JC Lamoth, Hans Timmerman, Ebert Otten, Michiel F Reneman
The article delves into Central Sensitization in chronic low back pain (CLBP). Central Sensitization Inventory (CSI) helps spot this sensitivity, usually using a cut-off of 40/100 based on chronic pain patients. But factors like different pain conditions and gender might alter this value. To address this, the study uses machine learning on data from CLBP patients and pain-free adults. They find three groups: healthy, CLBP with low sensitivity, and CLBP with high sensitivity. After analyzing these groups, they suggest a new cut-off of 35 for CLBP. However, they note that gender-specific cut-offs (like 34 for females) need more scrutiny due to uneven gender distribution in the study. This work highlights the importance of tailoring sensitivity measures for CLBP, offering a potential revised benchmark for diagnosis and treatment, while also emphasizing the need for more balanced gender representation in future studies.
Original article: https://arxiv.org/abs/2311.11862