Development of a Nomogram for the Identification of Meniscus Injury by Subjective Symptoms

Abstract

Background: Our study aimed to construct a nomogram with a scoring system based on subjective symptoms to identify meniscus injury. Methods: This study recruited 157 participants for a cross-sectional study. The doctor used MRI to diagnose each participant's knee joint. We use questionnaires to collect data on 14 subjective symptoms of each patient. Chi-square test and logistic regression were used for statistical analysis to screen for significant symptoms of meniscus injury relative to other knee diseases. We used the nomogram method to score the significant symptoms and build a scoring model. Results: Multivariate analysis showed that Pain Activity (OR = 3.41), Pain Hyperflexion (OR = 4.135), Tend Knee Space (OR = 62.138) were statistically significant risk symptoms for meniscus injury. Knee dislocation (OR = 0.184) was not a significant distinguishing symptom. Analysis of the nomogram model showed that the total score for each symptom ranged from 37 to 219, with corresponding risk rates ranging from 0.10 to 0.95 points. The C-index was calculated to assess the recognition accuracy of this nomogram scoring system was 88.75% (95% CI 85.24%-90.78%). Conclusions: We found that using the nomogram to establish an identification model to distinguish meniscus injury from other knee diseases based on subjective symptoms was effective. This method is a convenient and effective tool to evaluate meniscus injury and support the prevention and self-management of meniscus injury.