Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To construct a prediction model for the progression of knee osteoarthritis(KOA)based on ultrasound score,magnetic resonance imaging(MRI)score,and serum levels of transforming growth factor-β1(TGF-β1)and cathepsin D(Cat D).Methods Clinical data from 270 patients with KOA in Hengshui People's hospital from December 2022 to June 2024 were retrospec-tively analyzed.The patients were randomly divided into a modeling set(n=189)and validation set(n=81)at a ratio of 7∶3.The patients in the modeling set were categorized into mild-to-moderate and severe groups based on the degree of disease progression.Mul-tivariate logistic regression analysis was used to identify factors influencing KOA progression,and a prediction model was constructed using R software.Results Multivariate logistic regression analysis showed that body mass index,knee injury history,ultrasound score,WORMS score,TGF-β1,and Cat D were significant predictors of KOA progression(P＜0.05).A nomogram-based prediction model was developed using these variables.The areas under the curve(AUC)of the nomograms for predicting disease progression in the modeling and validation sets were 0.889 and 0.860,respectively.The calibration curves showed that the predicted probability was in good agreement with the actual probability.Conclusion The prediction model developed in this study is effective in identifying patients at high-risk of KOA progression and may servce as a valuable tool for clinical assessment and decision making.

Objective To explore the value of dynamic ultrasound combined with 3.0T MRI for diagnosing and typing synovial plica of knee joint.Methods Dynamic ultrasound and 3.0T MRI data of 100 patients with suspected synovial plica of knee joint were retrospectively analyzed.Taking the results of arthroscopy as standards,the efficacy of dynamic ultrasound and 3.0T MRI alone and their combination for diagnosing synovial plica of knee joint were evaluated and compared.The length and thickness of synovial plica of knee joint measured with dynamic ultrasound,3.0T MRI alone and their combination were compared with those of arthroscopy,and the consistencies of the location and classification of synovial plica of knee joint with arthroscopy were analyzed.Results Synovial plica was detected in 70 cases,including 11 cases of supropatellar synovial plica,15 cases of infrapatellar synovial plica,medial patellar in 30 cases and lateral patellar synovial plica in 14 cases,among them type A,B,C and D were classified in 9,35,23 and 3 cases,respectively.No significant difference of sensitivity was found between dynamic ultrasound and 3.0T MRI alone for diagnosing synovial plica of knee joint(P＞0.05),which were both lower than that of their combination(both P＜0.05).The length and thickness of knee synovial plica measured with dynamic ultrasound and 3.0T MRI alone were lower than those measured with their combination and arthroscopy(all P＜0.05),and there was no significant difference between the results of their combination and arthroscopy(both P＞0.05).Dynamic ultrasound,3.0T MRI alone and their combination had high consistency of location(Kappa=0.755,0.826,0.897)and classification of knee synovial plica with those of arthroscopy(Kappa=0.721,0.744,0.860).Conclusion Dynamic ultrasound combined with 3.0T MRI was valuable for diagnosing and typing of synovial plica of knee joint.