Construction and evaluation of the prediction model of knee degeneration based on bioelectrial impedance analysis
10.3760/cma.j.cn115682-20220130-00514
- VernacularTitle:基于生物电阻抗分析的膝关节退变程度预测模型构建及评价
- Author:
Mengqi WANG
1
;
Hongbo CHEN
;
Han LU
;
Cui WANG
;
Ziqiu ZOU
;
Yetian LIANG
;
Kexin CHEN
;
Shida JIN
;
Peiyuan LIU
;
Yuguang WANG
;
Shaomei SHANG
Author Information
1. 北京大学护理学院，北京 100191
- Keywords:
Osteoarthritis, knee;
Knee degeneration;
Electric impedance;
Support vector machine;
Predictive model
- From:
Chinese Journal of Modern Nursing
2023;29(1):7-13
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct the prediction model of knee degeneration in patients with knee osteoarthritis based on bioelectrical impedance index, and evaluate the prediction performance and application efficiency of the model.Methods:This was a cross-sectional study. From May to July 2021, 248 knee joints of 124 patients with knee osteoarthritis at home from Shijiazhuang Yuqiang Community Health Service Center who participated in physical examination were selected by convenience sampling to establish the model. According to Kellgren-Lawrence (K-L) grading system, the knee joints were divided into four groups, namely K-L1 ( n=19) , K-L2 ( n=103) , K-L3 ( n=96) , and K-L4 ( n=30) . The indicators included in the model were selected through analysis of variance or Kruskal-Wallis test, and a prediction model of knee degeneration was established using support vector machine, and the model was optimized using grid parameter optimization method. The prediction performance of the model was evaluated by the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy, positive predictive value and negative predictive value. Results:The indicators in the model included age, complications, lumbar/back/hip pain, high-risk occupation, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) -pain, WOMAC-function, capacitive reactance and phase angle. The area under the ROC curve of the training set model was 0.999, the prediction accuracy was 0.920, and the 95% confidence interval was 0.868 to 0.957. The area under the ROC curve of the test set model was 0.833, the prediction accuracy was 0.682, and the 95% confidence interval was 0.572 to 0.780.Conclusions:The prediction model of knee degeneration has good prediction performance and is easy to use, which can be used as a screening tool for knee degeneration in patients with knee osteoarthritis.
