| 个体化预测急性脊髓损伤并发呼吸功能障碍的风险Nomogram预测模型的构建 |
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Received:March 18, 2024
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| 作者 | Author | 单位 | Unit | E-Mail |
| 刘洁 |
LIU Jie |
首都医科大学附属复兴医院, 北京 100038 |
Fuxing Hospital Affiliated to Capital Medical University, Beijing 100038, China |
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| 刘素娟 |
LIU Su-juan |
首都医科大学附属复兴医院, 北京 100038 |
Fuxing Hospital Affiliated to Capital Medical University, Beijing 100038, China |
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| 李冉 |
LI Ran |
首都医科大学附属复兴医院, 北京 100038 |
Fuxing Hospital Affiliated to Capital Medical University, Beijing 100038, China |
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| 张文静 |
ZHANG Wen-jing |
首都医科大学附属复兴医院, 北京 100038 |
Fuxing Hospital Affiliated to Capital Medical University, Beijing 100038, China |
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| 王泳 |
WANG Yong |
首都医科大学附属复兴医院, 北京 100038 |
Fuxing Hospital Affiliated to Capital Medical University, Beijing 100038, China |
wyrehabil@ccmu.edu.cn |
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| 期刊信息：《中国骨伤》2025年25卷，第5期，第525-531页 |
| DOI：10.12200/j.issn.1003-0034.20231109 |
| 基金项目:国家自然科学基金项目(编号:82205151);中国中医科学院新入职青年科研人员培养专项(编号:ZZ17-XRZ-058);国家中医药管理局中医药创新团队及人才支持计划项目(编号:ZYYCXTDC-202003);中国中医科学院望京医院自主选题专项课题(编号:WJYY-ZZXT-2023-22) |
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目的:分析急性脊髓损伤并发呼吸功能障碍的危险因素并构建急性脊髓损伤并发呼吸功能障碍的临床预测模型。
方法:回顾性分析2019年4月至2022年10月治疗的急性脊髓损伤连续病例170例,根据治疗期间患者是否发生呼吸功能障碍将其分为呼吸功能障碍组30例和非呼吸功能障碍组140例。采用Lasso回归分析筛选急性脊髓损伤并发呼吸功能障碍的预测因素,采用多因素Logistic回归分析筛选急性脊髓损伤并发呼吸功能障碍的危险因素,采用R(R4.2.1)软件建立预测急性脊髓损伤并发呼吸功能障碍的列线图风险预警模型,应用Hosmer-Lemeshow检验评价模型拟合度,最后采用受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under curve,AUC)、校准曲线、决策曲线分析(decision curve analysis,DCA)评估模型的区分度、校准度及临床影响力。
结果:170例患者中发生呼吸功能障碍30例,发生率为17.65%。Lasso回归分析筛选出年龄、居住地、婚姻状态、抽烟、高血压、瘫痪程度、脊髓损伤平面、合并多发伤、骨折脱位脊髓损伤、ASIA分级共计10个变量为影响因素。通过多因素Logistic回归分析显示,年龄、抽烟、瘫痪程度、脊髓损伤平面、骨折脱位脊髓损伤、ASIA分级等是急性脊髓损伤并发呼吸功能障碍的危险因素。构建急性脊髓损伤并发呼吸功能障碍的预测模型经Hosmer-Lemeshow检验得到χ2=5.830,P=0.67;模型的AUC值为0.912;DCA分析显示,阈值概率为1%~100%时列线图预测急性脊髓损伤并发呼吸功能障碍的净获益值较高。
结论:列线图有助于临床早期识别急性脊髓损伤并发呼吸功能障碍风险,便于临床早期决策及干预,对优化患者临床疗效改善其预后具有重要的指导意义。后续期待更大样本以及多中心对本模型进行完善、验证。 |
| [关键词]:急性脊髓损伤 呼吸功能障碍 危险因素 列线图 |
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| Establishment of a Nomogram model for individualized prediction of the risk of acute spinal cord injury complicated with respiratory dysfunction |
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Abstract:
Objective To analyze the risk factors of acute spinal cord injury complicated with respiratory dysfunction,and to construct the clinical prediction model of acute spinal cord injury complicated with respiratory dysfunction.
Methods Continuous 170 cases of acute spinal cord injury treated from April 2019 to October 2022 were retrospectively collected,and clinical data were uniformly collected. Patients were divided into respiratory dysfunction group 30 cases and non-respiratory dysfunction group 140 cases according to whether they had respiratory dysfunction during treatment. The predictive factors of acute spinal cord injury complicated with respiratory dysfunction were screened by Lasso analysis,and the risk factors of acute spinal cord injury complicated with respiratory dysfunction were screened by multivariate Logistic regression analysis. R(R4.2.1) software was used to establish a nomogram risk warning model for predicting acute spinal cord injury complicated with respiratory dysfunction,and Hosmer-Lemeshow test was used to evaluate the model fit. Finally,area under receiver operating characteristic(ROC) curve (AUC),calibration curve,and decision curve analysis(DCA) were used to evaluate the differentiation,calibration and clinical impact of the model.
Results The incidence of respiratory dysfunction in 170 patients was 17.65%. Lasso regression analysis selected age,residence,marital status,smoking,hypertension,degree of paralysis,spinal cord injury plane,multiple injuries,spinal cord fracture and dislocation,and ASIA grade as the influencing factors. Multivariate Logistic regression analysis showed that age,smoking,degree of paralysis,level of spinal cord injury,spinal cord injury of fracture and dislocation,and ASIA grade were risk factors for acute spinal cord injury complicated with respiratory dysfunction. The prediction model of acute spinal cord injury complicated with respiratory dysfunction was established by Hosmer-Lemeshow test,χ2=5.830,P=0.67. The AUC value of the model was 0.912. DCA analysis showed that the net benefit value of nomogram prediction of acute spinal cord injury complicated with respiratory dysfunction was higher when threshold probability ranged from 1% to 100%.
Conclusion This column chart can help identify the risk of acute spinal cord injury complicated with respiratory dysfunction in early clinical stage,facilitate early clinical decision-making and intervention,and has important guiding significance for optimizing clinical efficacy and improving prognosis of patients. It is expected to improve and verify this model with larger samples and multi-center in the future. |
| KEYWORDS:Aacute spinal cord injury Respiratory dysfunction Risk factors Column diagram |
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| 引用本文，请按以下格式著录参考文献： |
| 中文格式: | 刘洁,刘素娟,李冉,张文静,王泳.个体化预测急性脊髓损伤并发呼吸功能障碍的风险Nomogram预测模型的构建[J].中国骨伤,2025,25(5):525~531 |
| 英文格式: | LIU Jie,LIU Su-juan,LI Ran,ZHANG Wen-jing,WANG Yong.Establishment of a Nomogram model for individualized prediction of the risk of acute spinal cord injury complicated with respiratory dysfunction[J].zhongguo gu shang / China J Orthop Trauma ,2025,25(5):525~531 |
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