Su Bo, Zhao Junyu, Dai Xinjia, Ma Changsheng
Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
Int J Cardiol. 2025 Oct 15;437:133498. doi: 10.1016/j.ijcard.2025.133498. Epub 2025 Jun 10.
The role of the new derived parameters of left atrial (LA) strain in cardioembolic risk stratification is unknown, besides, new algorithm is needed to provide incremental value of cardioembolic risk stratification in patients with atrial fibrillation (AF), especially in those with CHA2DS2-VASc score of 0-2.
We enrolled 566 consecutive subjects with non-valvular AF, who underwent transesophageal echocardiography. Left atrial appendage (LAA) thrombogenic milieu, as a surrogate for cardioembolic risk, was defined as the presence of a thrombus, severe spontaneous echo contrast, or sludge in the LAA. The impaired LAA emptying velocity was defined as LAA emptying velocity ≤ 30 cm/s. To classify LAA thrombogenic milieu, a decision tree analysis was performed to explore the way of the combination characteristic echocardiographic variables. LA strain parameters includes left atrial reservoir strain (LASr), left atrial systolic stain rate (LASRr), LA filling index, LA filling rate, LA stiffness index, and LA stiffness rate.
Among the 566 subjects, 176 (31.1 %) identified with LAA thrombogenic milieu. Compared those without, LA filling index, LA filling rate, LA stiffness index, and LA stiffness rate was significantly increased in the patients with LAA thrombogenic milieu. The multiple logistic regression analysis suggested that left atrial strain parameters (respectively) were independently correlated with LAA thrombogenic milieu. Left atrial strain parameters (AUC: 0.846-0.916) exhibited good accuracy for identifying LAA thrombogenic milieu, and non-inferior to conventional parameters including CHA2DS2-VASc score (0.645). The decision tree analysis identified LASr, LASRr, LAEF, CHA2DS2VASc score, and LA stiffness index as the most relevant variables to correctly discriminate LAA thrombogenic milieu from patients with AF. The decision tree as a novel algorithm could accurately identify subjects with LAA thrombogenic milieu (AUC 0.930, accuracy 89.31 %) or impaired LAA emptying velocity (AUC 0.868, accuracy 87.98 %). In the subgroup analysis, among 354 the subjects with lower CHA2DS2VASc score (0-2), 85 patients with LAA thrombogenic milieu. The novel algorithm (AUC: 0.938, accuracy 90.39 %) also performed well to discriminate subjects with LAA thrombogenic milieu.
The LA strain parameters were non-inferior to conventional parameters for risk stratification of LAA thrombogenic milieu in AF patients. Furthermore, a novel algorithm, based on left atrial strain parameters and CHA2DS2-VASc score, could accurately identify patients with LAA thrombogenic milieu in non-valvular AF, even in those with lower CHA2DS2VASc score (0-2).
左心房（LA）应变新衍生参数在心脏栓塞风险分层中的作用尚不清楚，此外，需要新的算法来为心房颤动（AF）患者的心脏栓塞风险分层提供增量价值，尤其是CHA2DS2-VASc评分为0-2的患者。
我们连续纳入了566例接受经食管超声心动图检查的非瓣膜性AF患者。左心耳（LAA）血栓形成环境作为心脏栓塞风险的替代指标，定义为LAA内存在血栓、严重自发回声增强或淤滞。LAA排空速度受损定义为LAA排空速度≤30cm/s。为了对LAA血栓形成环境进行分类，进行了决策树分析以探索组合特征性超声心动图变量的方法。LA应变参数包括左心房储备应变（LASr）、左心房收缩应变率（LASRr）、LA充盈指数、LA充盈率、LA僵硬度指数和LA僵硬度率。
在566例受试者中，176例（31.1%）被确定为LAA血栓形成环境。与无LAA血栓形成环境的患者相比，LAA血栓形成环境患者的LA充盈指数、LA充盈率、LA僵硬度指数和LA僵硬度率显著升高。多因素logistic回归分析表明，左心房应变参数分别与LAA血栓形成环境独立相关。左心房应变参数（AUC：0.846-0.916）在识别LAA血栓形成环境方面表现出良好的准确性，且不劣于包括CHA2DS2-VASc评分（0.645）在内的传统参数。决策树分析确定LASr、LASRr、LAEF、CHA2DS2VASc评分和LA僵硬度指数是正确区分AF患者LAA血栓形成环境的最相关变量。作为一种新算法，决策树能够准确识别LAA血栓形成环境的受试者（AUC 0.930，准确率89.31%）或LAA排空速度受损的受试者（AUC 0.868，准确率87.98%）。在亚组分析中，在354例CHA2DS2VASc评分较低（0-2）的受试者中，85例有LAA血栓形成环境。新算法（AUC：0.938，准确率90.39%）在区分有LAA血栓形成环境的受试者方面也表现良好。
在AF患者中，LA应变参数在LAA血栓形成环境风险分层方面不劣于传统参数。此外，基于左心房应变参数和CHA2DS2-VASc评分的新算法能够准确识别非瓣膜性AF患者中LAA血栓形成环境的患者，即使是CHA2DS2VASc评分较低（0-2）的患者。
