| 踝关节骨折术后创伤性关节炎发生的影响因素及风险预测模型的构建 |
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Received:May 12, 2023
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| 作者 | Author | 单位 | Unit | E-Mail |
| 李松 |
LI Song |
广元市第一人民医院, 四川 广元 628000 |
Guangyuan City First People's Hospital, Guangyuan 628000, Sichuan, China |
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| 杨塍尧 |
YANG Cheng-yao |
广元市第一人民医院, 四川 广元 628000 |
Guangyuan City First People's Hospital, Guangyuan 628000, Sichuan, China |
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| 彭茜 |
PENG Qian |
广元市第一人民医院, 四川 广元 628000 |
Guangyuan City First People's Hospital, Guangyuan 628000, Sichuan, China |
306368428@qq.com |
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| 期刊信息：《中国骨伤》2024年37卷，第3期，第264-270页 |
| DOI：10.12200/j.issn.1003-0034.20221216 |
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目的:探讨影响踝关节骨折患者术后创伤性关节炎的危险因素,并构建风险预测模型。
方法:选取2020年5月至2022年5月治疗的550例踝关节骨折患者为研究对象,按照7:3分为建模组(385例)和验证组(165例),建模组根据术后是否发生创伤性关节炎将患者作为发生组(112例)和未发生组(273例)。记录患者的年龄、身体质量指数(body mass index,BMI)、性别、吸烟史、糖尿病史、致伤原因、骨折类型、手术时机、体力劳动、开放性损伤、骨质疏松、复位不良、术后负重时间、血管损伤、手术方式等信息;采用单因素和多因素Logistic回归分析影响踝关节骨折患者术后发生创伤性关节炎的危险因素;采用R软件建立构建列线图预测模型;采用受试者工作特征(receiver operating characteristic,ROC)曲线、校准图形验证模型的区分度以及一致性。
结果:建模组112例出现术后创伤性关节炎,273例未发生。单因素分析结果显示,发生组和未发生组年龄、BMI、骨折类型、手术时机、体力劳动>Ⅱ级、开放性损伤、骨质疏松、复位不良例数比较,差异有统计学意义(P<0.05);多因素Logistic回归分析结果显示年龄(OR=2.887)、BMI(OR=4.042)、骨折类型(OR=4.244)、手术时机(OR=2.665)、体力劳动>Ⅱ级(OR=5.099)、骨质疏松(OR=10.219)、复位不良(OR=3.112)均为影响踝关节骨折患者术后创伤性关节炎的独立危险因素(P<0.05)。基于以上危险因素建立预测踝关节骨折患者术后创伤性关节炎发生风险的列线图模型,并进行内外部验证,结果显示建模组和验证组校准曲线显示校正曲线和理想曲线拟合度均较好,表明模型预测术后创伤性关节炎发生风险与实际发生风险基本一致;ROC曲线下面积分析结果显示分别为0.867[95%CI(0.826,0.908)]、0.882[95%CI(0.827,0.938)],表明预测模型具有良好的预测能力。
结论:年龄、BMI、骨折类型、手术时机、体力劳动>Ⅱ级、骨质疏松、复位不良均为影响踝关节骨折患者术后创伤性关节炎的危险因素,基于以上危险因素构建的预测模型可有效评估踝关节骨折患者术后创伤性关节炎的发生风险。 |
| [关键词]:踝关节骨折 创伤性关节炎 影响因素 列线图 预测模型 |
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| Influencing factors of traumatic arthritis after ankle fracture surgery and construction of risk prediction model |
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Abstract:
Objective To explore risk factors of post-operative traumatic arthritis in patients with ankle fracture,and to establish risk prediction model.
Methods Totally 550 patients with ankle fracture treated from May 2020 to May 2022 were selected as research objects and divided into modeling group (385 patients) and verification group (165 patients) according to 7:3. In modeling group,patients were classified as occurrence group (112 patients) and non-occurrence group (273 patients) according to whether traumatic arthritis occurred after opertaion. Age,body mass index(BMI),gender,smoking history,diabetes history,injury type,fracture type,operation time,manual labor,open injury,osteoporosis,poor reduction,postoperative weight-bearing time,vascular injury,and surgical method were recorded; risk factors of traumatic arthritis in ankle fracture patients were analyzed by single factor and multi factor logistic regression analyses; R software was used to build the prediction model of line graph;receiver operating characteristic (ROC) curve and calibration graph were applied to verify the discrimination and consistency of the model.
Results One hundred and twelve of 385 patients with ankle fracture were developed to post-operative traumatic arthritis,and 275 did not. Univariate analysis showed that there were significant differences in age,BMI,fracture type,operation time,physical labor aboveⅡ,open injury,osteoporosis and poor reduction between two groups (P<0.05). Multivariate Logistic regression analysis showed that age (OR=2.887),BMI (OR=4.042),fracture type (OR=4.244),operation time (OR=2.665),physical labor above gradeⅡ(OR=5.099),osteoporosis (OR=10.219),and poor reduction (OR=3.112) were independent risk factors for traumatic arthritis after ankle fracture (P<0.05). Based on the above risk factors,an nomogram model was established to predict the risk of postoperative traumatic arthritis in ankle fracture patients,and internal and external verification was conducted. The results showed calibration curve of modeling group and verification group showed a good fit between correction curve and ideal curve,indicating that the predicted risk of postoperative traumatic arthritis by the model was basically consistent with actual risk. Area runder ROC curve analysis results showed 0.867[(95%CI(0.826,0.908)] and 0.882[95%CI(0.827,0.938)],respectively,indicating that the prediction model had good prediction ability.
Conclusion Age,BMI,fracture type,operation time,physical labor above gradeⅡ,osteoporosis and poor reduction are all risk factors for post-operative traumatic arthritis in patients with ankle fracture. The prediction model based on the above risk factors could effectively evaluate risk of post-operative traumatic arthritis in patients with ankle fracture. |
| KEYWORDS:Ankle fracture Traumatic arthritis Influencing factors Nomogram Prediction model |
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| 引用本文，请按以下格式著录参考文献： |
| 中文格式: | 李松,杨塍尧,彭茜.踝关节骨折术后创伤性关节炎发生的影响因素及风险预测模型的构建[J].中国骨伤,2024,37(3):264~270 |
| 英文格式: | LI Song,YANG Cheng-yao,PENG Qian.Influencing factors of traumatic arthritis after ankle fracture surgery and construction of risk prediction model[J].zhongguo gu shang / China J Orthop Trauma ,2024,37(3):264~270 |
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