| 基于列线图构建非瓣膜性房颤患者的左心耳血栓状态预测模型 |
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| 作者姓名： | 薛倩 卓小桢 杨春 韩秀 |
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| 作者单位： | 西安交通大学第一附属医院心内科超声室，陕西 西安 710061 |
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| 基金项目： | 国家自然科学基金青年科学基金81400302 |
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| 摘 要： | 目的构建非瓣膜性房颤(NVAF)患者左心耳血栓(LAAT)状态预测模型，为临床个体化判断提供参考。方法选取2018年3月1日~2020年11月30日期间所有在西安交通大学第一附属医院心内科住院患者资料，结合筛选标准共获得NVAF患者530例。根据LAAT状态分为无LAAT组(n=428)和有LAAT组(n=102)。结合国内外研究进展及本单位病例特点广泛收集可能与NVAF患者LAAT形成有关的危险因素，并通过二元Logistic回归分析确定独立危险因素。基于列线图构建NVAF患者LAAT状态模型，并对模型准确性进行评价及内部验证。结果血栓病史(非LAAT)、房颤病程、房颤发作类型、BNP、Cys-C、LAD等6个危险因素与NAVF患者LAAT状态相关(P均 < 0.05)，可作为独立危险因素；基于列线图构建NVAF患者LAAT状态预测模型，C-index为0.74(95%CI:0.69~0.79)。此外，在校准曲线中也表明模型预测能力较好；内部验证集的C-index为0.72(95%CI:0.67~0.77)。结论基于列线图构建的NVAF患者LAAT状态模型有着良好的实际预测能力，可较准确、直观、个体化地预测NVAF患者LAAT状态。
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| 关 键 词： | 血栓 危险因素 左心耳 心房颤动 列线图 |
| 收稿时间： | 2021-02-21 |
Construction and verification of a model for predicting the risk of left atrial appendage thrombus in patients with non-valvular atrial fibrillation based on nomogram |
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| Authors: | Qian XUE Xiaozhen ZHUO Chun YANG Xiu HAN |
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| Affiliation: | Department of Cardiology & Echocardiography Room, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, China |
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| Abstract: | ObjectiveTo construct a model for predicting the risk of left atrial appendage thrombus (LAAT) in patients with nonvalvular atrial fibrillation (NVAF) to provide a reference for individualized clinical judgment.MethodsThe data of all patients hospitalized in the Department of Cardiology of the First Affiliated Hospital of Xi'an Jiaotong University between March 1, 2018 and November 30, 2020 were collected. Then a total of 530 patients with NVAF were obtained according to the screening criteria. It is divided into the non-LAAT group (n=428) and the LAAT group (n=102) based on the presence or absence of LAAT status. Relevant advances in global research and the characteristics of our institution's cases were reviewed, and risk factors that may be associated with LAAT formation in NVAF patients were collected extensively. Independent risk factors associated with LAAT formation were identified by binary logistic regression analysis. A model to predict the risk of LAAT occurrence in NVAF patients was constructed based on nomogram, and the accuracy of the model was evaluated and validated internally.ResultsSix factors, including history of thrombosis, duration of AF, type of AF, BNP, Cys-C, and LAD, were associated with the presence or absence of LAAT status in patients with NAVF (all P < 0.05) and could be used as independent risk factors to predict LAAT formation. Accordingly, a model was constructed to predict the risk of LAAT occurrence in NVAF patients based on nomogram, with a C-index of 0.74 (95%CI: 0.69-0.79). In addition, the prediction accuracy of the model is also shown in the calibration curve.ConclusionThe model for predicting the risk of LAAT in patients with NVAF based on Nomogram has good accuracy and practicability, and can be used to predict the risk of LAAT in patients with NVAF accurately and intuitively. |
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