Diagnostic Value of Median Nerve Cross-sectional Area Measured by Ultrasonography for the Severity of Carpal Tunnel Syndrome: A Machine Learning-Based Approach.

Abstract

This study was conducted to evaluate the diagnostic performance and to establish cutoff values of median nerve cross-sectional area for classifying the severity of carpal tunnel syndrome. The study dataset included 1069 wrists from 1034 patients with carpal tunnel syndrome (May 2017-December 2022). A machine learning algorithm was used to predict carpal tunnel syndrome severity based on median nerve cross-sectional area, adjusting for sex, age, body mass index, and disease duration. The multivariable model showed a multiclass area under the receiver operating characteristic curve of 0.753 and s single-class area under the receiver operating characteristic curves of 0.733, 0.635, and 0.780 for mild, moderate, and severe syndrome, respectively. Optimal cross-sectional area cutoffs were identified as <14 mm 2 for mild and >16 mm 2 for severe syndrome, with area under the receiver operating characteristic curve values of 0.773 and 0.794, respectively. The model showed high sensitivity for mild and high specificity for severe syndrome but had a low performance for moderate carpal tunnel syndrome (area under the receiver operating characteristic curve = 0.568). Median nerve cross-sectional area is a valuable tool for diagnosing mild and severe carpal tunnel syndrome. While cross-sectional area provides limited accuracy for moderate carpal tunnel syndrome, it remains a useful adjunct to other diagnostic methods, potentially reducing the need for more invasive procedures.