Construction of nomogram prediction model for knee joint cartilage injury in patients with anterior cruciate ligament rupture
10.3760/cma.j.cn115455-20230408-00348
- VernacularTitle:前交叉韧带断裂患者并发膝关节软骨损伤的列线图预测模型构建
- Author:
Jianfeng NI
1
;
Heyuan MENG
;
Bao ZHANG
;
Jixiang ZHENG
Author Information
1. 天津二七二医院骨科，天津 300020
- Keywords:
Anterior cruciate ligament injuries;
Knee joint cartilage injury;
Nomograms;
Prediction model
- From:
Chinese Journal of Postgraduates of Medicine
2024;47(5):427-433
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the relevant factors of knee joint cartilage injury in patients with anterior cruciate ligament rupture and construct a nomogram prediction model.Methods:The clinical data of 160 patients with unilateral anterior cruciate ligament rupture who underwent surgical treatment from March 2020 to February 2023 at Tianjin 272 Hospital and the Ninety-Eighty-Third Hospital of the People′s Liberation Army Joint Logistics Support Force were retrospectively analyzed. The patients were divided into injured group (97 cases) and non injured group (63 cases) based on whether there was concurrent knee joint cartilage injury. The optimal cutoff values of each factor were analyzed by the receiver operating characteristic (ROC) curve. Using a multiple Logistic regression model to analyze the independent risk factors of knee joint cartilage injury in patients with anterior cruciate ligament rupture; construct a nomogram model for predicting knee joint cartilage injury in patients with anterior cruciate ligament rupture. The internal validation of the nomogram model was validated using calibration curves, and the predictive performance of the nomogram model is evaluated using decision curves.Results:The body mass index (BMI), rate of meniscus injury, number of sprains and injury time in injured group were significantly higher than those in non injured group: (24.15 ± 2.52) kg/m 2 vs. (22.84 ± 3.13) kg/m 2, 77.32% (75/97) vs. 17.46% (11/63), (2.64 ± 0.90) times vs. (1.17 ± 0.64) times, (19.15 ± 3.77) d vs. (12.92 ± 3.14) d, and there were statistical differences ( P<0.05). The ROC curve analysis results show that the optimal cutoff values for BMI, number of sprains and injury time were 22.9 kg/m 2, once and 16 d, respectively. BMI (>22.9 kg/m 2), meniscus injury (with), number of sprains (>1 time) and injury time (>16 d) were independent risk factors for knee joint cartilage injury in patients with anterior cruciate ligament rupture, and they were also predictive factors for building nomogram model. The internal validation results show that the nomogram model predicts a C-index of 0.819 (95% CI 0.715 to 0.883) for patients with anterior cruciate ligament rupture complicated by knee cartilage injury. The consistency between the observed values and the predicted values was good. The nomogram model predicts a threshold of over 0.14 for knee joint cartilage injury in patients with anterior cruciate ligament rupture, and the clinical net benefits provided by the column chart model were higher than BMI, meniscus injury, number of sprains and injury time. Conclusions:This study constructs a nomogram model based on BMI, meniscus injury, number of sprains, and injury time to predict knee joint cartilage injury in patients with anterior cruciate ligament rupture. The model has good predictive value for knee joint cartilage injury in patients with anterior cruciate ligament rupture, and can be used to identify high-risk patients who are prone to knee joint cartilage injury in patients with anterior cruciate ligament rupture.
