Division of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
J Interv Cardiol. 2022 Nov 4;2022:7806027. doi: 10.1155/2022/7806027. eCollection 2022.
The purpose of this study was to investigate the risk factors of left atrial (LA) or left atrial appendage (LAA) thrombi in patients with nonvalvular atrial fibrillation (NVAF) and to establish and validate relevant predictive models. It might improve thromboembolic risk stratification in patients with NVAF.
This study retrospectively included 1210 consecutive patients with NVAF undergoing transesophageal echocardiography (TEE), of whom 139 patients had thrombi in LA or in LAA. Through literature review and the ten events per variable (10EPV) principle, 13 variables were finally identified for inclusion in multivariate analysis. Models were constructed by multivariate logistic stepwise regression and least absolute shrinkage and selection operator (lasso) regression.
After logistic regression, five variables (AF type, age, B-type natriuretic peptide, /' ratio, and left atrial diameter) were finally screened out as model 1. After Lasso regression, AF type, age, gender, B-type natriuretic peptide, E/e' ratio, left atrial diameter, and left ventricular ejection fraction were finally screened as model 2. After comparing the two models, the simpler model 1 was finally selected. The area under the ROC curve (AUC) of the model 1 was 0.865 (95% CI: 0.838-0.892), the Hosmer-Lemeshow test = 0.898, and the AUC = 0.861 after internal validation. The clinical decision curve showed that the new clinical prediction model could achieve a net clinical benefit when the expected threshold was between 0 and 0.6.
This study constructed a new clinical prediction model of LA or LAA thrombi, with a higher discriminative degree than the CHADS2 and CHA2DS2-VASc scoring systems (AUC: 0.865 vs. 0.643; AUC: 0.865 vs 0.652).
本研究旨在探讨非瓣膜性心房颤动(NVAF)患者左心房(LA)或左心耳(LAA)血栓形成的危险因素,并建立和验证相关预测模型。这可能会改善 NVAF 患者的血栓栓塞风险分层。
本研究回顾性纳入 1210 例接受经食管超声心动图(TEE)检查的 NVAF 连续患者,其中 139 例患者 LA 或 LAA 有血栓形成。通过文献回顾和 10 个事件/变量(10EPV)原则,最终确定了 13 个变量进行多变量分析。通过多变量逻辑逐步回归和最小绝对值收缩和选择算子(lasso)回归构建模型。
经过逻辑回归,最终筛选出 5 个变量(AF 类型、年龄、B 型利钠肽、'/比和左心房直径)作为模型 1。经过 Lasso 回归,最终筛选出 AF 类型、年龄、性别、B 型利钠肽、E/e'比、左心房直径和左心室射血分数作为模型 2。比较两个模型后,最终选择了更简单的模型 1。模型 1 的 ROC 曲线下面积(AUC)为 0.865(95%CI:0.838-0.892),Hosmer-Lemeshow 检验 = 0.898,内部验证后的 AUC 为 0.861。临床决策曲线显示,当预期阈值在 0 到 0.6 之间时,新的临床预测模型可以实现净临床获益。
本研究构建了一种新的 LA 或 LAA 血栓形成的临床预测模型,其区分度高于 CHADS2 和 CHA2DS2-VASc 评分系统(AUC:0.865 与 0.643;AUC:0.865 与 0.652)。