PDF(Pubmed)
Abstract：
UNASSIGNED: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with a high risk of stroke. This study was designed to investigate the relationship between hemodynamic parameters and left atrial thrombus/spontaneous echo contrast (LAT/SEC) in non-valvular atrial fibrillation (NVAF) patients and establish a predictive nomogram that integrates hemodynamic parameters with clinical predictors to predict the risk of LAT/SEC.
UNASSIGNED: From January 2019 to September 2022, a total of 354 consecutive patients with NVAF were enrolled in this cross-sectional study at the First Affiliated Hospital of Guangxi Medical University. To identify the optimal predictive features, we employed least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was subsequently constructed, and the results were visualized with a nomogram. We evaluated the model\'s performance using discrimination, calibration, and the concordance index (C-index).
UNASSIGNED: We observed a 38.7% incidence of SEC/TH in NVAF patients. Independent influencing factors of LAT/SEC were identified through LASSO and multivariate logistic regression. Finally, four indicators were included, namely, previous stroke/transient ischaemic attack (OR = 4.25, 95% CI = 1.57-12.23, P = 0.006), left atrial volume index (LAVI) (OR = 1.04, 95% CI = 1.01-1.06, P = 0.001), S/D ratio (OR = 0.27, 95% CI = 0.11-0.59, P = 0.002), and left atrial acceleration factor (OR = 4.95, 95% CI = 2.05-12.79, P = 0.001). The nomogram, which incorporated these four influencing factors, demonstrated excellent predictive ability. The training set had a C-index of 0.878, while the validation set had a C-index of 0.872. Additionally, the calibration curve demonstrated great consistency between the predicted probabilities and the observed outcomes, and the decision curve analysis confirmed the important clinical advantage of the model for patients with NVAF.
UNASSIGNED: Our findings indicate that an enlarged left atrium and abnormal hemodynamic parameters in the left atrial and pulmonary veins are linked to a greater risk of LAT/SEC. Previous stroke/transient ischaemic attack, LAVI, the S/D ratio, and left atrial acceleration factor were independently associated with LAT/SEC in NVAF patients. With the incorporation of these four variables, the developed nomogram effectively predicts the risk of LAT/SEC and outperforms the CHA2DS2-VASc score.
UNASSIGNED: From January 2019 to September 2022, a total of 354 consecutive patients with NVAF were enrolled in this cross-sectional study at the First Affiliated Hospital of Guangxi Medical University. To identify the optimal predictive features, we employed least absolute shrinkage and selection operator (LASSO) regression. A multivariate logistic regression model was subsequently constructed, and the results were visualized with a nomogram. We evaluated the model\'s performance using discrimination, calibration, and the concordance index (C-index).
UNASSIGNED: We observed a 38.7% incidence of SEC/TH in NVAF patients. Independent influencing factors of LAT/SEC were identified through LASSO and multivariate logistic regression. Finally, four indicators were included, namely, previous stroke/transient ischaemic attack (OR = 4.25, 95% CI = 1.57-12.23, P = 0.006), left atrial volume index (LAVI) (OR = 1.04, 95% CI = 1.01-1.06, P = 0.001), S/D ratio (OR = 0.27, 95% CI = 0.11-0.59, P = 0.002), and left atrial acceleration factor (OR = 4.95, 95% CI = 2.05-12.79, P = 0.001). The nomogram, which incorporated these four influencing factors, demonstrated excellent predictive ability. The training set had a C-index of 0.878, while the validation set had a C-index of 0.872. Additionally, the calibration curve demonstrated great consistency between the predicted probabilities and the observed outcomes, and the decision curve analysis confirmed the important clinical advantage of the model for patients with NVAF.
UNASSIGNED: Our findings indicate that an enlarged left atrium and abnormal hemodynamic parameters in the left atrial and pulmonary veins are linked to a greater risk of LAT/SEC. Previous stroke/transient ischaemic attack, LAVI, the S/D ratio, and left atrial acceleration factor were independently associated with LAT/SEC in NVAF patients. With the incorporation of these four variables, the developed nomogram effectively predicts the risk of LAT/SEC and outperforms the CHA2DS2-VASc score.
摘要：
■心房颤动（AF）是最常见的心律失常，与中风的高风险相关。本研究旨在研究非瓣膜性心房颤动（NVAF）患者的血流动力学参数与左心房血栓/自发性回声对比（LAT/SEC）之间的关系，并建立预测列线图，将血流动力学参数与临床预测因子相结合，以预测LAT/SEC的风险。
自2019年1月至2022年9月，广西医科大学第一附属医院共纳入354例连续NVAF患者。为了识别最佳预测特征，我们采用最小绝对收缩和选择算子(LASSO)回归。随后构建了多元逻辑回归模型，结果用列线图可视化。我们使用区分度评估了模型的性能，校准,和一致性指数(C指数)。
■我们观察到NVAF患者的SEC/TH发生率为38.7%。通过LASSO和多因素logistic回归分析确定LAT/SEC的独立影响因素。最后,包括四个指标，即,既往卒中/短暂性脑缺血发作(OR=4.25,95%CI=1.57-12.23,P=0.006),左心房容积指数(LAVI)(OR=1.04,95%CI=1.01-1.06,P=0.001),S/D比(OR=0.27,95%CI=0.11-0.59,P=0.002),左心房加速因子(OR=4.95,95%CI=2.05~12.79,P=0.001)。列线图，其中包含了这四个影响因素，表现出优异的预测能力。训练集的C指数为0.878，而验证集的C指数为0.872。此外,校准曲线显示了预测概率和观察结果之间的高度一致性，和决策曲线分析证实了该模型对NVAF患者的重要临床优势。
■我们的发现表明，左心房增大以及左心房和肺静脉的血流动力学参数异常与LAT/SEC的更大风险有关。以前的中风/短暂性脑缺血发作，LAVI,S/D比，NVAF患者左心房加速因子与LAT/SEC独立相关。随着这四个变量的合并，形成的列线图有效预测LAT/SEC的风险,优于CHA2DS2-VASc评分.
自2019年1月至2022年9月，广西医科大学第一附属医院共纳入354例连续NVAF患者。为了识别最佳预测特征，我们采用最小绝对收缩和选择算子(LASSO)回归。随后构建了多元逻辑回归模型，结果用列线图可视化。我们使用区分度评估了模型的性能，校准,和一致性指数(C指数)。
■我们观察到NVAF患者的SEC/TH发生率为38.7%。通过LASSO和多因素logistic回归分析确定LAT/SEC的独立影响因素。最后,包括四个指标，即,既往卒中/短暂性脑缺血发作(OR=4.25,95%CI=1.57-12.23,P=0.006),左心房容积指数(LAVI)(OR=1.04,95%CI=1.01-1.06,P=0.001),S/D比(OR=0.27,95%CI=0.11-0.59,P=0.002),左心房加速因子(OR=4.95,95%CI=2.05~12.79,P=0.001)。列线图，其中包含了这四个影响因素，表现出优异的预测能力。训练集的C指数为0.878，而验证集的C指数为0.872。此外,校准曲线显示了预测概率和观察结果之间的高度一致性，和决策曲线分析证实了该模型对NVAF患者的重要临床优势。
■我们的发现表明，左心房增大以及左心房和肺静脉的血流动力学参数异常与LAT/SEC的更大风险有关。以前的中风/短暂性脑缺血发作，LAVI,S/D比，NVAF患者左心房加速因子与LAT/SEC独立相关。随着这四个变量的合并，形成的列线图有效预测LAT/SEC的风险,优于CHA2DS2-VASc评分.
