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| 基于纤维蛋白原与白蛋白比值构建心脏手术相关急性肾损伤的列线图预测模型 |
| Nomogram model to predict cardiac surgery-associated acute kidney injury based on fibrinogen-to-albumin ratio |
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| DOI：10.12089/jca.2026.07.003 |
| 中文关键词: 心脏手术相关急性肾损伤 纤维蛋白原与白蛋白比值 列线图预测模型 独立危险因素 预测价值 |
| 英文关键词: Cardiac surgery-associated acute kidney injury Fibrinogen to albumin ratio Nomogram prediction model Independent risk factors Predictive value |
| 基金项目:国家自然科学基金面上项目（82172190） |
| 作者 | 单位 | E-mail | | 李佳冰 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 韩雨 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 谢伟 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 魏本忠 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 张扬杨 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 柳青 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | | | 高巨 | 225001,徐州医科大学扬州临床学院,苏北人民医院麻醉科 | gaoju_003@163.com |
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| 中文摘要: |
目的：探究纤维蛋白原与白蛋白比值（FAR）对心脏手术相关急性肾损伤（CSA-AKI）的预测价值，并构建CSA-AKI列线图预测模型。
方法：回顾性收集择期心脏手术患者的围术期资料，年龄45～74岁，ASAⅢ—Ⅴ级。根据是否发生CSA-AKI将患者分为CSA-AKI组与非CSA-AKI组，比较两组基本资料及术中数据。筛选CSA-AKI独立危险因素，建立受试者工作特征曲线，构建列线图预测模型，绘制校准曲线并进行决策曲线分析。
结果：共纳入患者451例，其中115例（25.5%）发生CSA-AKI。多因素Logistic回归分析显示,年龄偏大（OR=1.099，95%CI 1.066～1.134）、BMI偏大（OR=1.101，95%CI 1.029～1.179）、术前FAR偏高（OR=1.238，95%CI 1.107～1.385）和术中失血量偏大（OR=1.003，95%CI 1.001～1.005）是发生CSA-AKI的独立危险因素。ROC分析显示,年龄预测CSA-AKI的曲线下面积（AUC）为0.702（95%CI 0.649～0.755），BMI预测CSA-AKI的AUC为0.543（95%CI 0.483～0.603），FAR预测CSA-AKI的AUC为0.647（95%CI 0.587～0.707），术中失血量预测CSA-AKI的AUC为0.568（95%CI 0.504～0.631）。其中，FAR取最佳截断值0.088时，敏感性为0.591，特异性为0.643。基于上述4项危险因素构建的列线图模型AUC为0.771（95%CI 0.724～0.819），敏感性为0.896，特异性为0.524。
结论：FAR对CSA-AKI具有中等预测价值。基于FAR、年龄、BMI和失血量构建的预测模型区分度较好，可作为术前风险评估的参考工具，但其特异性有限。 |
| 英文摘要: |
Objective: To evaluate the predictive value of fibrinogen-to-albumin ratio (FAR) for cardiac surgery-associated acute kidney injury (CSA-AKI) and to develop a nomogram prediction model for CSA-AKI.
Methods: Retrospectively collect perioperative data of elective cardiac surgery patients, aged 45-74 years, ASA Ⅲ-Ⅴ. The patients were divided into the CSA-AKI group and the non-CSA-AKI group, and baseline characteristics as well as intraoperative data were compared between the two groups. Independent risk factors for CSA-AKI were screened, and receiver operating characteristic (ROC) curves were constructed. A nomogram prediction model was developed, followed by calibration curve plotting and decision curve analysis (DCA).
Results: A total of 451 patients were included, of whom 115 (25.5%) developed CSA-AKI. Multivariate logistic regression analysis showed that advanced age (OR=1.099, 95% CI 1.066-1.134), higher BMI(OR = 1.101, 95% CI 1.029-1.179), elevated preoperative FAR (OR=1.238, 95% CI 1.107-1.385), and greater intraoperative blood loss (OR = 1.003, 95% CI 1.001-1.005) were independent risk factors for CSA-AKI. ROC analysis revealed that the area under the curve (AUC) for age in predicting CSA-AKI was 0.702 (95% CI 0.649-0.755), the AUC for BMI in predicting CSA-AKI was 0.543 (95% CI 0.483-0.603), the AUC for FAR in predicting CSA-AKI was 0.647 (95% CI 0.587-0.707), and the AUC for intraoperative blood loss in predicting CSA-AKI was 0.568 (95% CI 0.504-0.631). Using the optimal cut-off value of 0.088, FAR demonstrated a sensitivity of 0.591 and a specificity of 0.643. The nomogram model constructed based on the above four risk factors achieved an AUC of 0.771 (95% CI 0.724-0.819), with a sensitivity of 0.896 and a specificity of 0.524.
Conclusion: FAR demonstrates moderate predictive value for CSA-AKI. The prediction model incorporating FAR, age, BMI, and blood loss exhibits good discriminative ability and may serve as a reference tool for preoperative risk assessment; however, its specificity is limited, and further external validation is required. |
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