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BMC Musculoskeletal Disorders

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Open Access 01-12-2024 | Research

Prediction of specific structural damage to the knee joint using qualitative isokinetic analysis

Authors: Feisheng Zheng, Rui Jia, Jinqun Ye, Mengyuan Li, Yunping Zhang, Guangqing Xu, Lei Zhang

Published in: BMC Musculoskeletal Disorders | Issue 1/2024

Abstract

Background

An isokinetic moment curve (IMC) pattern-damaged structure prediction model may be of considerable value in assisting the diagnosis of knee injuries in clinical scenarios. This study aimed to explore the association between irregular IMC patterns and specific structural damages in the knee, including anterior cruciate ligament (ACL) rupture, meniscus (MS) injury, and patellofemoral joint (PFJ) lesions, and to develop an IMC pattern-damaged structure prediction model.

Methods

A total of 94 subjects were enrolled in this study and underwent isokinetic testing of the knee joint (5 consecutive flexion-extension movements within the range of motion of 90°-10°, 60°/s). Qualitative analysis of the IMCs for all subjects was completed by two blinded examiners. A multinomial logistic regression analysis was used to investigate whether a specific abnormal curve pattern was associated with specific knee structural injuries and to test the predictive effectiveness of IMC patterns for specific structural damage in the knee.

Results

The results of the multinomial logistic regression revealed a significant association between the irregular IMC patterns of the knee extensors and specific structural damages (“Valley” - ACL, PFJ, and ACL + MS, “Drop” - ACL, and ACL + MS, “Shaking” - ACL, MS, PFJ, and ACL + MS). The accuracy and Macro-averaged F1 score of the predicting model were 56.1% and 0.426, respectively.

Conclusion

The associations between irregular IMC patterns and specific knee structural injuries were identified. However, the accuracy and Macro-averaged F₁ score of the established predictive model indicated its relatively low predictive efficacy. For the development of a more accurate predictive model, it may be essential to incorporate angle-specific and/or speed-specific analyses of qualitative and quantitative data in isokinetic testing. Furthermore, the utilization of artificial intelligence image recognition technology may prove beneficial for analyzing large datasets in the future.

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Title: Prediction of specific structural damage to the knee joint using qualitative isokinetic analysis
Authors: Feisheng Zheng
Rui Jia
Jinqun Ye
Mengyuan Li
Yunping Zhang
Guangqing Xu
Lei Zhang
Publication date: 01-12-2024
Publisher: BioMed Central
Published in: BMC Musculoskeletal Disorders / Issue 1/2024
Electronic ISSN: 1471-2474
DOI: https://doi.org/10.1186/s12891-024-07434-w

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Prediction of specific structural damage to the knee joint using qualitative isokinetic analysis

Abstract

Background

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusion

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