Department of Cardiology, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China.
Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, China.
Echocardiography. 2024 Nov;41(11):e15932. doi: 10.1111/echo.15932.
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.
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.
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.
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.
我们之前报道了四种卵圆孔未闭（PFO）形态类型，它们影响右向左分流（RLS）程度。在此，我们旨在研究 PFO 形态与隐源性卒中（CS）之间的关系。我们进一步基于四种 PFO 形态类型和功能参数开发了一个列线图，以指导临床医生判断 PFO 相关卒中的风险。
这是一项回顾性观察性研究，纳入 2020 年 1 月至 2022 年 11 月期间患有 PFO 的成年患者。患者分为 PFO 相关卒中组（CS 组）和无隐源性卒中组（非 CS 组）。分析了四种 PFO 类型和 RLS 分级。使用多变量逻辑回归分析建立预测 PFO 相关卒中的列线图。使用接受者操作特征对内部分辨性能进行内部验证和评估。
我们纳入了 389 名患有 PFO 的患者（男性 182 名，女性 207 名），平均年龄为 43.3±8.1 岁。推导队列包括 293 名患者（CS 组 186 名，非 CS 组 107 名）。预测列线图包括 PFO 形态类型、房间隔（IAS）移动距离、卵圆窝瓣厚度、静息时 PFO 通道长度和对比经胸超声心动图（c-TTE）在瓦氏动作时的 RLS 分级。建立了验证队列（CS 组 61 名，非 CS 组 35 名）。该模型在推导队列中的曲线下面积（AUC）为 0.891（95%置信区间=0.855-0.928），在验证队列中的 AUC 为 0.935（95%置信区间=0.885-0.986）。校准曲线分析显示，该列线图在推导队列中的 C 指数为 0.891，在验证队列中的 C 指数为 0.935。决策曲线分析（DCA）表明该列线图具有临床适用性。
增加四种 PFO 形态类型可提高 PFO 相关卒中的风险分层能力。该列线图可识别 PFO 个体的高风险或低风险，并选择可能从介入器械闭合中获益的患者。
