One hundred fifty-three patients with hypoxia of both sexes,underwent hip arthroplasty from January 2012 to January 2014,aged 65-97 yr,weighing 41-80 kg,living in areas at altitude above 1800 m,of American Society of Anesthesiologists physical status Ⅱ-Ⅵ,were selected.The hemoglobin (Hb) at 3-4 days after operation was collected,and the patients were divided into 3 groups depending on whether or not postoperative anemia occurred:no anemia group (Hb＞ 110 g/L);mild anemia group (90 g/L≤ Hb≤ 110 g/L);moderate anemia group (70 g/L ≤ H b＜ 90 g/L).The 36-item Short-Form Health Survey score and Harris Hip Score at 28 days after operation were collected.There was no significant difference between the three groups in the postoperative 36-item Short-Form Health Survey score and Harris Hip Score (P＞0.05).Postoperative mild and moderate anemia did not affect the short-term outcome after hip arthroplasty in elderly patients in high-altitude regions.

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.