He Weibin, Yin Lei, Liu Qian, Zhang Yan, Zhao Yanlei, Wang Lianxia, You Ling
Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Front Cardiovasc Med. 2024 Sep 19;11:1468379. doi: 10.3389/fcvm.2024.1468379. eCollection 2024.
Atrial fibrillation (AF) is the most common cardiac arrhythmia, significantly increasing the risk of death and stroke. The left atrial appendage (LAA) plays a crucial role in the development of AF. Reduced left atrial appendage emptying velocity (LAAEV) is an important indicator of nonvalvular AF, associated with thrombosis and recurrence after catheter ablation. This study aims to identify factors influencing LAAEV and construct a predictive model for LAAEV in nonvalvular AF patients.
This retrospective cohort study included 1,048 nonvalvular AF patients hospitalized at the Second Hospital of Hebei Medical University from January 1, 2015, to December 31, 2021. Patients underwent transthoracic and transesophageal echocardiography and had complete laboratory data. Statistical analyses included binary logistic regression and multiple linear regression to identify independent predictors of reduced LAAEV and construct a predictive model.
Patients were divided into two groups: reduced LAAEV (<40 cm/s) and normal LAAEV (≥40 cm/s). The reduced LAAEV group included 457 patients (43.61%), with significant differences in age, gender, alcohol consumption, heart failure (HF), ischemic stroke, AF type, resting heart rate, CHA2DS2-VASc score, serum creatinine (SCR), serum uric acid (SUA), estimated glomerular filtration rate (eGFR), glycated hemoglobin (HbA1C), β2 macroglobulin (B2M), left atrial diameter (LAD), and left ventricular ejection fraction (LVEF) compared to the normal LAAEV group. Logistic regression analysis identified age (OR 0.974, 95% CI 0.951-0.997, = 0.028), HF (OR 0.637, 95% CI 0.427-0.949, = 0.027), AF type [Persistent AF vs. PAF (OR 0.063, 95% CI 0.041-0.095, = 0) Long-standing Persistent AF vs. PAF (OR 0.077, 95% CI 0.043-0.139, = 0)], LAD (OR 0.872, 95% CI 0.836-0.91, < 0.001), and LVEF (OR 1.057, 95% CI 1.027-1.089, = 0) as independent predictors of reduced LAAEV. Multiple linear regression analysis included age, AF type, LAD, and LVEF in the final predictive model, explaining 43.5% of the variance in LAAEV (adjusted R² = 0.435).
Age, HF, type of AF, LAD, and LVEF are independent predictors of reduced LAAEV. The predictive model (LAAEV = 96.567-15.940 × AFtype-1.309 × LAD-0.18 × Age + 37.069 × LVEF) demonstrates good predictive value, aiding in the initial assessment and management of nonvalvular AF patients.
心房颤动（AF）是最常见的心律失常，显著增加死亡和中风风险。左心耳（LAA）在房颤的发生发展中起关键作用。左心耳排空速度（LAAEV）降低是非瓣膜性房颤的重要指标，与导管消融术后血栓形成及复发相关。本研究旨在确定影响LAAEV的因素，并构建非瓣膜性房颤患者LAAEV的预测模型。
这项回顾性队列研究纳入了2015年1月1日至2021年12月31日在河北医科大学第二医院住院的1048例非瓣膜性房颤患者。患者接受了经胸和经食管超声心动图检查，并拥有完整的实验室数据。统计分析包括二元逻辑回归和多元线性回归，以确定LAAEV降低的独立预测因素并构建预测模型。
患者被分为两组：LAAEV降低组（<40 cm/s）和LAAEV正常组（≥40 cm/s）。LAAEV降低组包括457例患者（43.61%），与LAAEV正常组相比，在年龄、性别、饮酒、心力衰竭（HF）、缺血性中风、房颤类型、静息心率、CHA2DS2-VASc评分、血清肌酐（SCR）、血清尿酸（SUA）、估算肾小球滤过率（eGFR）、糖化血红蛋白（HbA1C）、β2微球蛋白（B2M）、左心房直径（LAD）和左心室射血分数（LVEF）方面存在显著差异。逻辑回归分析确定年龄（OR 0.974，95%CI 0.951-0.997，P = 0.028）、HF（OR 0.637，95%CI 0.427-0.949，P = 0.027）、房颤类型[持续性房颤与阵发性房颤（OR 0.063，95%CI 0.041-0.095，P = 0）；长期持续性房颤与阵发性房颤（OR 0.077，95%CI 0.043-0.139，P = 0）]、LAD（OR 0.872，95%CI 0.836-0.91，P < 0.001）和LVEF（OR 1.057，95%CI 1.027-1.089，P = 0）为LAAEV降低的独立预测因素。多元线性回归分析在最终预测模型中纳入了年龄、房颤类型、LAD和LVEF，解释了LAAEV变异的43.5%（调整R² = 0.435）。
年龄、HF、房颤类型、LAD和LVEF是LAAEV降低的独立预测因素。预测模型（LAAEV = 96.567 - 15.940×房颤类型 - 1.309×LAD - 0.18×年龄 + 37.069×LVEF）显示出良好的预测价值，有助于非瓣膜性房颤患者的初始评估和管理。
