中国组织工程研究

中国组织工程研究 ›› 2025, Vol. 29 ›› Issue (33): 7143-7149.doi: 10.12307/2025.756

• 人工假体 artificial prosthesis • 上一篇    下一篇

人工股骨头置换治疗老年股骨颈骨折：髋关节功能不良风险预测模型的验证

阿布都艾尼江•阿不力米提，阿里木•马木提，李斯密   

  1. 喀什地区第一人民医院运动医学科，新疆维吾尔自治区喀什市  844000
  • 收稿日期:2024-07-23 接受日期:2024-09-24 出版日期:2025-11-28 发布日期:2025-04-12
  • 通讯作者: 李斯密，主治医师，喀什地区第一人民医院运动医学科，新疆维吾尔自治区喀什市 844000
  • 作者简介:阿布都艾尼江•阿不力米提，维吾尔族，硕士，主治医师，主要从事关节及运动损伤疾病相关研究。

Artificial femoral head replacement for femoral neck fracture in the elderly: validation of a risk prediction model for hip dysfunction

Abuduainijiang·Abulimiti, Alimu·Mamuti, Li Simi   

  1. Department of Sports Medicine, First People’s Hospital of Kashi Prefecture, Kashi 844000, Xinjiang Uygur Autonomous Region, China
  • Received:2024-07-23 Accepted:2024-09-24 Online:2025-11-28 Published:2025-04-12
  • Contact: Li Simi, Attending physician, Department of Sports Medicine, First People’s Hospital of Kashi Prefecture, Kashi 844000, Xinjiang Uygur Autonomous Region, China
  • About author:Abuduainijiang•Abulimiti, MS, Attending physician, Department of Sports Medicine, First People’s Hospital of Kashi Prefecture, Kashi 844000, Xinjiang Uygur Autonomous Region, China

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摘要：


文题释义：

列线图(Nomogram)：是一种可视化工具，主要用于展示多因素回归预测模型的结果，根据列线图中每个变量赋予一定分值，最终得出总分，以便在临床中个体化预测患者的预后或疾病风险。
人工股骨头置换：是老年股骨颈骨折患者常用的手术治疗方法，尤其适用于因骨质疏松导致的移位严重的骨折，具有快速恢复髋关节功能、减少疼痛并提高患者生活质量等特点。


背景：人工股骨头置换是老年人股骨颈骨折最主要的手术方式之一，然而术后髋关节功能不良是一个常见且棘手的问题。

目的：建立老年股骨颈骨折患者行人工股骨头置换后早期髋关节功能改善情况的列线图预测模型并进行验证。
方法：回顾性选择 2022年1月至2023年10月在喀什地区第一人民医院因股骨颈骨折行人工股骨头置换的230 例患者，收集可能影响术后早期髋关节功能的相关因素，在术后6个月时采用Harris髋关节评分量表评估髋关节功能改善情况。根据术后髋关节功能改善情况是否理想将患者分为功能正常组和功能不良组，比较两组患者术前、术中及术后因素，以LASSO回归筛选潜在因素后行多因素Logistic回归，以R4.1.3软件建立列线图预测模型并进行内部验证。

结果与结论：①最终纳入221例患者，术后 6 个月患者平均Harris评分为82.07±8.28；②LASSO 回归筛选出4个潜在影响因素，以此行多因素logistic回归分析结果显示，年龄、体质量指数、受伤至手术天数及术后负重时间为术后早期髋关节功能不良的独立影响因素(P < 0.05)；③根据多因素结果建立列线图模型，校准曲线结果显示，预测曲线与标准曲线基本拟合；受试者操作特征曲线分析结果显示，列线图模型预测术后早期髋关节功能不良的曲线下面积为0.870[95%CI (0.819，0.921)]；④术后早期髋关节功能改善情况受年龄、体质量指数、受伤至手术天数及术后负重时间等因素的影响，此次研究建立的列线图模型用于预测人工股骨头置换后早期髋关节功能不良具有较高的区分度与准确度。

https://orcid.org/0009-0005-2176-0812(阿布都艾尼江•阿不力米提)

中国组织工程研究杂志出版内容重点：人工关节；骨植入物；脊柱；骨折；内固定；数字化骨科；组织工程

关键词: 股骨颈骨折, 半髋关节置换, 人工股骨头置换, 多因素分析, 预测模型, 列线图, 骨科植入物

Abstract: BACKGROUND: Artificial femoral head replacement is one of the primary surgical methods for femoral neck fractures in the elderly patients. However, postoperative hip dysfunction remains a common and challenging issue.
OBJECTIVE: To establish and validate a nomogram prediction model for early improvement of hip joint function in elderly patients undergoing artificial femoral head replacement for femoral neck fractures.
METHODS: 230 patients who underwent hip hemiarthroplasty for femoral neck fractures at The First People’s Hospital of Kashi Prefecture from January 2022 to October 2023 were retrospectively selected. Relevant factors that could influence early postoperative hip function were collected, and hip function improvement was assessed at 6 months postoperatively using the Harris Hip Score. Patients were divided into two groups based on whether their postoperative hip function improvement was satisfactory. Preoperative, intraoperative, and postoperative factors were compared between the two groups. Potential factors were screened using LASSO regression, followed by multivariate logistic regression to establish a nomogram prediction model using R4.1.3 software, which was then internally validated.
RESULTS AND CONCLUSION: (1) A total of 221 patients were included in the study, with an average Harris Hip Score of (82.07±8.28) at 6 months postoperatively. (2) LASSO regression identified four potential influencing factors. Multivariate logistic regression analysis revealed that age, body mass index, time from injury to surgery, and time postoperative weight-bearing were independent factors affecting early postoperative hip function (P < 0.05). (3) Based on the multivariate results, a nomogram model was established. The calibration curve indicated good agreement between the predicted and observed outcomes. Receiver operating characteristic curve analysis results showed that the area under the curve for predicting early postoperative hip dysfunction using the nomogram model was 0.870[95%CI(0.819, 0.921)]. (4) Early postoperative hip function improvement was influenced by age, body mass index, time from injury to surgery, and time to postoperative weight-bearing. The nomogram model developed in this study demonstrates high discrimination and accuracy in predicting early hip dysfunction following artificial femoral head replacement.

Key words: femoral neck fracture, hip hemiarthroplasty, artificial femoral head replacement, multivariate analysis, prediction model, nomogram, orthopedic implant

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