目的:根据2022年ESC/ERS指南,重新评估计算机断层扫描肺动脉造影(CTPA)的心血管指标在预测肺动脉高压(PH)中的价值。
方法:本观察性研究包括272例疑似PH患者(女性143例,平均年龄54.9±12.5岁)。对218例患者进行分组,以评估CTPA的心血管指标,并建立二元逻辑回归模型。其他54名患者被分组为验证组,以评估更新标准下预测模型的性能。基于平均肺动脉压(mPAP),患者分为三组:A组包括mPAP≤20mmHg的患者,B组包括20mmHg20mmHg方面的表现。
结果:主要肺动脉直径(MPAd),MPAd/升主动脉直径比(MPAd/AAd比),右室游离壁厚度(RVFWT)在三组之间差异有统计学意义(p<0.05)。MPAd的曲线下面积(AUC)大于MPAd/AAd比值和RVFWT。30.0mm的MPAd截止值具有83.1%的灵敏度和90.4%的特异性。二元逻辑回归模型的AUC(Z=-12.98187+0.31053MPAd+1.04863RVFWT)为0.938±0.018。在验证组中,AUC,灵敏度,特异性,预测模型的准确率分别为0.878,92.7%,76.9%,88.9%,分别。
结论:根据更新的标准,阈值为30.0mm的MPAd在预测PH方面具有较好的敏感性和特异性。二元逻辑回归模型可以提高诊断准确性。
■在更新的标准下,阈值为30.0mm的主肺动脉直径对预测肺动脉高压具有较好的敏感性和特异性。二元逻辑回归模型可以提高诊断准确性。
结论:•根据2022年ESC/ERS指南,30.0mm的MPAd临界值在预测mPAP>20mmHg时具有更好的敏感性和特异性•建立了二元逻辑回归模型(Z=-12.981870.31053MPAd1.04863RVFWT),并且具有敏感性,特异性,准确率为92.7%,76.9%,预测mPAP>20mmHg的比例为88.9%。•二元逻辑回归预测模型在预测mPAP>20mmHg方面优于MPAd。
OBJECTIVE: To re-assess cardiovascular metrics on computed tomography pulmonary angiography (CTPA) in predicting pulmonary hypertension (PH) under the 2022 ESC/ERS
guidelines.
METHODS: This observational study retrospectively included 272 patients (female 143, mean age = 54.9 ± 12.5 years old) with suspected PH. 218 patients were grouped to evaluate cardiovascular metrics on CTPA and develop a binary logistic regression model. The other 54 patients were grouped into the validation group to assess the performance of the prediction model under the updated criteria. Based on mean pulmonary artery pressure (mPAP), patients were divided into three groups: group A consisted of patients with mPAP ≤ 20 mmHg, group B included patients with 20 mmHg < mPAP < 25 mmHg, and group C comprised patients with mPAP ≥ 25 mmHg. Cardiovascular metrics among the three groups were compared, and receiver operating characteristic curves (ROCs) were used to evaluate the performance of cardiovascular metrics in predicting mPAP > 20 mmHg.
RESULTS: The main pulmonary arterial diameter (MPAd), MPAd/ascending aorta diameter ratio (MPAd/AAd ratio), and right ventricular free wall thickness (RVFWT) showed significant differences among the three groups (p < 0.05). The area under curve (AUC) of MPAd was larger than MPAd/AAd ratio and RVFWT. A MPAd cutoff value of 30.0 mm has a sensitivity of 83.1% and a specificity of 90.4%. The AUC of the binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was 0.938 ± 0.018. In the validation group, the AUC, sensitivity, specificity, and accuracy of the prediction model were 0.878, 92.7%, 76.9%, and 88.9%, respectively.
CONCLUSIONS: Under the updated criteria, MPAd with a threshold value of 30.0 mm has better sensitivity and specificity in predicting PH. The binary logistic regression model may improve the diagnostic accuracy.
UNASSIGNED: Under the updated criteria, the main pulmonary arterial diameter with a threshold value of 30.0 mm has better sensitivity and specificity in predicting pulmonary hypertension. The binary logistic regression model may improve diagnostic accuracy.
CONCLUSIONS: • According to 2022 ESC/ERS
guidelines, a MPAd cutoff value of 30.0 mm has better sensitivity and specificity in predicting mPAP > 20 mmHg • A binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was developed and had a sensitivity, specificity, and accuracy of 92.7%, 76.9%, and 88.9% in predicting mPAP > 20 mmHg. • A binary logistic regression prediction model outperforms MPAd in predicting mPAP > 20 mmHg.