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股骨颈骨折术后早期股骨头坏死影响因素分析及列线图预测模型构建
Hits: 559   Download times: 379   Received:February 06, 2024    
作者Author单位UnitE-Mail
付志强 FU Zhi-qiang 衢州市人民医院, 浙江 衢州 324000 Quzhou People's Hospital, Quzhou 324000, Zhejiang, China fzq17357078062@163.com 
王巍 WANG Wei 衢州市人民医院, 浙江 衢州 324000 Quzhou People's Hospital, Quzhou 324000, Zhejiang, China  
何飞熊 HE Fei-xiong 衢州市人民医院, 浙江 衢州 324000 Quzhou People's Hospital, Quzhou 324000, Zhejiang, China  
洪胜坤 HONG Sheng-kun 衢州市人民医院, 浙江 衢州 324000 Quzhou People's Hospital, Quzhou 324000, Zhejiang, China  
周卫军 ZHOU Wei-jun 衢州市人民医院, 浙江 衢州 324000 Quzhou People's Hospital, Quzhou 324000, Zhejiang, China  
期刊信息:《中国骨伤》2024年37卷,第7期,第694-699页
DOI:10.12200/j.issn.1003-0034.20230679
基金项目:衢州市科学技术局指导性科技攻关项目(编号:2021026)


目的:探讨股骨颈骨折患者术后早期发生股骨头坏死的危险因素,并建立列线图预测模型。

方法:选取自2020 年 1 月至 2022 年 4 月收治的 167 例行固定手术治疗的股骨颈骨折患者, 根据患者术后早期是否发生股骨头坏死分为坏死组和非坏死组。坏死组 38 例,其中男 21 例,女 17 例,年龄 33~72(53.49±10.96)岁,受伤至手术时间 40~67(53.46±7.23) h;非坏死组 129 例,其中男 72 例,女 57 例,年龄 18~83(52.78±12.55)岁,受伤至手术时间 18~65(39.88±7.79) h。对患者性别、合并糖尿病、高血压、慢性肝病、股骨头后倾角、手术方式、骨折位移情况、骨折线部位、术前制动牵引、螺钉排列方式、复位质量、年龄、身体质量指数、受伤至手术时间等可能影响因素进行单因素分析,并对 P<0.05的单因素进行多因素 Logistic 回归分析。并构建列线图风险模型。

结果:167 例股骨颈骨折患者术后股骨头坏死的发生率为 22.76%。合并糖尿病[OR=5.139,95%CI (1.405,18.793),P=0.013]、骨折移位情况[OR=3.723,95%CI(1.105,12.541),P=0.034]、术前制动牵引[OR=3.444,95%CI(1.038,11.427),P=0.043]、复位质量[OR=3.524,95%CI(1.676,7.411),P=0.001]和受伤至手术时间[OR=1.270,95%CI(1.154,1.399),P=0.000]是股骨颈骨折患者术后早期发生股骨头坏死的独立危险因素。Hosmer-Lemeshow 拟合优度检验 (χ2=3.951,P=0.862), 受试者工作特征 (receiver operatorcharacteristic,ROC)曲线下面积为 0.944[P<0.001,95%CI(0.903,0.987)],灵敏度为 89.50%,特异性为 88.40%,最大约登指数为 0.779, 模型校正曲线总体趋势接近理想曲线。模型回归方程 Z=1.637×合并糖尿病+1.314×骨折移位情况+1.237×术前制动牵引+1.260×复位质量+0.239×受伤至手术时间-18.310。

结论:股骨颈骨折患者术后早期股骨头坏死的发生受多重因素共同影响,根据因素建立的风险预警模型具有较好的预测效能。
[关键词]:股骨颈骨折  固定手术  股骨头坏死  列线图预测模型
 
Analysis of influencing factors of early femoral head necrosis after femoral neck fracture and construction of nomogram prediction model
Abstract:

Objective To explore the risk factors of early femoral head necrosis in patients with femoral neck fracture after operation,and to establish a nomogram prediction model.

Methods A total of 167 patients with femoral neck fracture from January 2020 to April 2022 were selected and divided into necrosis group and non necrosis group according to whether femoral head necrosis occurred in the early postoperative period. There were 21 males and 17 females in the necrosis group,aged from 33 to 72 years old,with an average of (53.49±10.96) years old,and the time from injury to operation ranged from 40 to 67 hours,with average time of (53.46±7.23) hours. There were 72 males and 57 females in the non-necrosis group,aged from 18 to 83 years,with an average of (52.78±12.55) years old,and the time from injury to operation was 18 to 65 hours,with an average time of (39.88±7.79) hours. The potential influencing factors,including patient gender, diabetes mellitus,hypertension, chronic liver disease,posterior inclination angle of the femoral head,operation mode,fracture displacement,fracture line location, preoperative braking traction,screw arrangement mode, reduction quality,age,body mass index (BMI), and injury to operation time were subjected to single factor analysis. Logistic multivariate regression analysis was conducted for factors with a significance level of P<0.05.

Results The incidence of femoral head necrosis in 167 patients with femoral neck fracture was 22.76%. The following factors were identified as independent risk factors for early postoperative femoral head necrosis in patients with femoral neck fractures:coexisting diabetes[OR=5.139,95%CI(1.405, 18.793),P=0.013],displaced fracture[OR=3.723,95%CI(1.105,12.541),P=0.034],preoperative immobilization[OR=3.444, 95%CI(1.038,11.427),P=0.043],quality of reduction[OR=3.524, 95%CI(1.676,7.411),P=0.001],and time from injury to surgery[OR=1.270,95%CI(1.154,1.399), P=0.000]. The Hosmer-Lemeshow goodness of fit test(χ2=3.951,P=0.862),the area under the receiver operator characteristic (ROC) curve was 0.944[P<0.001,95%CI(0.903,0.987)],with a sensitivity of 89.50%,the specificity was 88.40%,the maximum Youden index was 0.779,and the overall trend of the model correction curve was close to the ideal curve. Model regression equation was Z=1.637 × diabetes + 1.314× fracture displacement+1.237 × preoperative braking traction+1.260 × reduction quality + 0.239×injury to operation time-18.310.

Conclusion The occurrence of early femoral head necrosis in patients with femoral neck fracture postoperatively is affected by multiple factors. The risk early warning model established according to the factors has good predictive efficacy.
KEYWORDS:Femoral neck fracture  Fixed surgery  Femoral head necrosis  Nomogram prediction model
 
引用本文,请按以下格式著录参考文献:
中文格式:付志强,王巍,何飞熊,洪胜坤,周卫军.股骨颈骨折术后早期股骨头坏死影响因素分析及列线图预测模型构建[J].中国骨伤,2024,37(7):694~699
英文格式:FU Zhi-qiang,WANG Wei,HE Fei-xiong,HONG Sheng-kun,ZHOU Wei-jun.Analysis of influencing factors of early femoral head necrosis after femoral neck fracture and construction of nomogram prediction model[J].zhongguo gu shang / China J Orthop Trauma ,2024,37(7):694~699
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