开发和验证用于预测卵圆孔闭锁相关中风的个性化提名图:基于裂孔形态学的分析。

IF 1.6 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Qin Zhang, Mochao Xiao, Wuzhu Lu, Yuhong Lin, Ziqing Gao, Yuzhuo Chen, Jiali Tian, Zhongzhen Su, Xiaobo Chen
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引用次数: 0

摘要

背景:我们曾报道过四种影响右向左分流(RLS)等级的卵圆孔孔(PFO)形态类型。在此,我们旨在研究 PFO 形态与隐源性卒中(CS)之间的关系。我们还根据四种 PFO 形态学类型和功能参数制定了一个提名图,以指导临床医生判断 PFO 相关性卒中的风险:这是一项回顾性观察研究,涉及 2020 年 1 月至 2022 年 11 月期间的 PFO 成年患者。患者被分为 PFO 相关中风组(CS 组)和无隐源性中风组(非 CS 组)。分析了四种类型的 PFO 和 RLS 等级。利用多变量逻辑回归分析制作了预测 PFO 相关中风的提名图。该模型的辨别性能经过内部验证,并使用接收器操作特征进行评估:我们共招募了 389 名 PFO 患者(男性,182 名;女性,207 名),平均年龄为 43.3 ± 8.1 岁。衍生队列由 293 名患者组成(CS 组,186 名患者;非 CS 组,107 名患者)。预测提名图包括 PFO 形态学类型、房间隔(IAS)移动距离、房间隔顶端厚度、静息时的 PFO 通道长度以及瓦尔萨尔瓦动作时的对比经胸超声心动图(c-TTE)RLS 分级。建立了一个验证队列(CS 组,61 名患者;非 CS 组,35 名患者)。推导队列的模型曲线下面积(AUC)为 0.891(95% 置信区间 = 0.855-0.928),验证队列的模型曲线下面积(AUC)为 0.935(95% 置信区间 = 0.885-0.986)。校准曲线分析表明,在推导队列中,提名图的 C 指数为 0.891,在验证队列中为 0.935。决策曲线分析(DCA)表明,提名图具有临床适用性:结论:增加四种 PFO 形态学类型提高了 PFO 相关中风的风险分层能力。该提名图可以识别高风险或低风险的 PFO 患者,并选择可能从介入装置闭合中获益的患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Development and Validation of an Individualized Nomogram for Predicting Patent Foramen Ovale-Associated Stroke: Patent Foramen Ovale Morphology-Based Analysis

Development and Validation of an Individualized Nomogram for Predicting Patent Foramen Ovale-Associated Stroke: Patent Foramen Ovale Morphology-Based Analysis

Background

We previously reported four patent foramen ovale (PFO) morphological types that influenced right-to-left shunt (RLS) grades. Herein, we aimed to study the relationship between PFO morphology and cryptogenic stroke (CS). We further developed a nomogram based on four PFO morphological types and functional parameters to guide clinicians in judging the risk of PFO-associated stroke.

Methods

This was a retrospective observational study involving adult patients with PFO between January 2020 and November 2022. Patients were divided into a PFO-associated stroke group (CS group) and a group without cryptogenic stroke (non-CS group). Four types of PFO and RLS grades were analyzed. Nomograms were made to predict PFO-associated stroke using multivariable logistic regression analysis. The discrimination performance of the model was internally validated and assessed using the receiver operating characteristic.

Results

We enrolled 389 patients (male, 182 patients; female, 207 patients) with PFO, the mean age was 43.3 ± 8.1 years. The derivation cohort comprised 293 patients (CS group, 186 patients; non-CS group, 107 patients). The predictive nomogram comprised PFO morphological types, interatrial septum (IAS) mobility distance, septum primum thickness, PFO channel length at rest, and contrast-transthoracic echocardiography (c-TTE) RLS grade during the Valsalva maneuver. A validation cohort was established (CS group, 61 patients; non-CS group, 35 patients). The model area under the curve (AUC) was 0.891 (95% confidence interval = 0.855−0.928) in the derivation cohort and 0.935 (95% confidence interval = 0.885−0.986) in the validation cohort. Calibration curve analysis showed that the nomogram had a C-index of 0.891 in the derivation cohort and 0.935 in the validation cohort. The decision curve analysis (DCA) indicated that the nomogram had clinical applicability.

Conclusions

Adding four PFO morphological types improved the risk stratification capability for PFO-associated stroke. The nomogram can identify high or low-risk PFO individuals and select patients who will likely benefit from interventional device closure.

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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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