Echocardiographic Screening Model for Improved Assessment of Atrial Septal Defect Closure: A Multicenter Retrospective Study

IF 1.6 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Hezhi Li, Zehan Huang, Gangcheng Zhang, Qunshan Shen, Hongwen Fei, Dongling Luo, Ziyang Yang, Bin Zhang, Caojin Zhang
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引用次数: 0

Abstract

Background

Atrial septal defect (ASD) is a prevalent congenital heart condition in adults, which finally leads to pulmonary hypertension and right heart failure if left untreated. Right heart catheterization (RHC), the current gold standard for determining ASD closure feasibility, is invasive. Thus, a noninvasive prescreening tool is urgently needed.

Methods and Results

In a multicenter, retrospective study, we assessed 924 ASD patients (2012–2022) to determine their suitability for ASD closure. Using LASSO regression, we identified predictors for a correctable shunt, enabling us to create the ASD model. The ASD model, comprising of estimated pulmonary artery systolic pressure (ePASP), peak velocity through the pulmonary valve (PV), peak E-wave velocity through the tricuspid valve (TVE), and right atrial longitudinal dimension (RA) by echocardiography, was constructed and exhibited favorable discriminative capability with an area under the curve (AUC) of 0.941 (95% CI: 0.920–0.961) in the derivation group. The model also demonstrated good calibration and discriminative abilities in the validation cohort. When juxtaposed with the earlier congenital heart disease (CHD) model, the newly developed ASD model demonstrated superior predictive capabilities for correctable shunt, supported by the net reclassification index (NRI) [0.063 (95% CI: 0.001–0.127, p = 0.047)] and integrated discrimination improvement (IDI) [0.023 (95% CI: 0.011–0.036, p < 0.001)].

Conclusion

In summary, our research advocates the ASD model as a superior tool for screening suitable ASD defect closure candidates.

超声心动图筛查模型用于改进心房间隔缺损闭合的评估:一项多中心回顾性研究
背景:房间隔缺损(ASD)是成人中普遍存在的先天性心脏病,如不及时治疗,最终会导致肺动脉高压和右心衰竭。右心导管检查(RHC)是目前确定 ASD 封堵可行性的金标准,但具有创伤性。因此,迫切需要一种无创预检工具:在一项多中心回顾性研究中,我们评估了 924 例 ASD 患者(2012-2022 年),以确定他们是否适合 ASD 闭合。通过 LASSO 回归,我们确定了可纠正分流的预测因素,从而建立了 ASD 模型。ASD 模型由估计肺动脉收缩压 (ePASP)、通过肺动脉瓣的峰值速度 (PV)、通过三尖瓣的 E 波峰值速度 (TVE) 和超声心动图显示的右心房纵向尺寸 (RA) 组成,在推导组中显示出良好的判别能力,曲线下面积 (AUC) 为 0.941(95% CI:0.920-0.961)。该模型在验证组中也表现出良好的校准和判别能力。与早期的先天性心脏病(CHD)模型相比,新开发的 ASD 模型对可矫正分流的预测能力更强,净再分类指数(NRI)[0.063(95% CI:0.001-0.127,p = 0.047)]和综合分辨改进指数(IDI)[0.023(95% CI:0.011-0.036,p 结论:新开发的 ASD 模型对可矫正分流的预测能力更强:总之,我们的研究主张将 ASD 模型作为筛选合适的 ASD 缺损闭合候选者的卓越工具。
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来源期刊
CiteScore
2.40
自引率
6.70%
发文量
211
审稿时长
3-6 weeks
期刊介绍: Echocardiography: A Journal of Cardiovascular Ultrasound and Allied Techniques is the official publication of the International Society of Cardiovascular Ultrasound. Widely recognized for its comprehensive peer-reviewed articles, case studies, original research, and reviews by international authors. Echocardiography keeps its readership of echocardiographers, ultrasound specialists, and cardiologists well informed of the latest developments in the field.
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