风险评估工具在预测球囊肺血管成形术后血流动力学结果方面的实用性:对比分析。

Postgraduate medicine Pub Date : 2024-05-01 Epub Date: 2024-05-30 DOI:10.1080/00325481.2024.2358745
Xin Li, Yi Zhang, Qing Zhao, Tao Yang, Qixian Zeng, Qi Jin, Anqi Duan, Zhihua Huang, Meixi Hu, Sicheng Zhang, Luyang Gao, Changming Xiong, Qin Luo, Zhihui Zhao, Zhihong Liu
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引用次数: 0

摘要

目的:广泛使用的肺动脉高压(PAH)风险评估工具的一些参数与球囊肺血管成形术(BPA)的血液动力学结果有关。因此,我们旨在确定这些风险评估工具是否可用于预测 BPA 术后的血液动力学结果:在这项回顾性研究中,我们纳入了 139 名接受过 BPA 的慢性血栓栓塞性肺动脉高压患者。我们比较了七种经过严格验证的风险评估工具预测 BPA 术后血流动力学结果的准确性。良好的血液动力学结果被定义为平均肺动脉压结果:不同风险评估工具的基线风险概况差异很大。美国早期和长期 PAH 疾病管理评估登记风险量表和法国风险评估工具将大多数患者评定为高风险,而肺动脉高压新疗法比较前瞻性登记(COMPERA)系列和基于实验室检查的风险量表将大多数患者归类为中度风险。在所有风险分层中,COMPERA 2.0(4层)的预测能力最高。无创风险分层(COMPERA 2.0 [3-strata])的预测能力与有创风险分层(COMPERA 1.0)相当(曲线下面积 0.649 vs. 0.648)。此外,将肺部一氧化碳弥散能力和三尖瓣反流速度纳入 COMPERA 2.0(4-strata)进一步提高了其预测能力(净重新分类指数 0.153,95% 置信区间 0.009-0.298,p = 0.038)。此外,改进后的 COMPERA 版本具有较高的校准准确性(斜率为 0.96):结论:尽管不同风险评估工具的风险分层分布各不相同,但在大多数模型中,随着风险分层的升级,获得良好血流动力学的患者比例有所下降。经过充分验证的 PAH 风险评估工具也能预测 BPA 后的血流动力学结果,其中改进后的 COMPERA 2.0 模型的预测能力最高。在 BPA 前应用风险评估工具有助于及早识别需要更密切监测和更强化干预的患者,从而改善 BPA 后的预后。
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Usefulness of risk assessment tools in predicting hemodynamic outcome after balloon pulmonary angioplasty: a comparative analysis.

Objectives: Several parameters of widely used risk assessment tools for pulmonary arterial hypertension (PAH) have been linked to hemodynamic outcomes of balloon pulmonary angioplasty (BPA). Therefore, we aimed to determine whether these risk assessment tools could be used to predict hemodynamic outcomes following BPA.

Methods: In this retrospective study, we included 139 patients with chronic thromboembolic pulmonary hypertension who had undergone BPA at Center for Pulmonary Vascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College (Beijing, China). We compared the accuracies of seven well-validated risk assessment tools for predicting hemodynamic outcomes following BPA. A favorable hemodynamic outcome was defined as a mean pulmonary arterial pressure < 30 mmHg at follow-up.

Results: The baseline risk profiles varied significantly among the risk assessment tools. The US Registry to Evaluate Early and Long-Term PAH Disease Management risk scales and the French risk assessment tools rated most patients as high-risk, while the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) series and laboratory examination-based risk scales categorized most patients as having intermediate-risk profile. COMPERA 2.0 (4-strata) exhibited the highest predictive power among all risk stratifications. Noninvasive risk stratification (COMPERA 2.0 [3-strata]) showed a comparable predictive ability to that of invasive risk stratification (COMPERA 1.0) (area under the curve 0.649 vs. 0.648). Moreover, incorporating diffusing capacity of the lungs for carbon monoxide and tricuspid regurgitation velocity into COMPERA 2.0 (4-strata) further enhanced its predictive power (net reclassification index 0.153, 95% confidence interval 0.009-0.298, p = 0.038). Additionally, this refined COMPERA version had a high calibration accuracy (slope 0.96).

Conclusion: Although the risk strata distribution varied among different risk assessment tools, the proportion of patients achieving favorable hemodynamics decreased with the escalation of risk stratification in most models. The well-validated risk assessment tools for PAH could also predict hemodynamic outcomes following BPA, and the refined COMPERA 2.0 model exhibited the highest predictive ability among these. Applying risk assessment tools before BPA can facilitate early identification of patients in need of closer monitoring and more intensive interventions, contributing to a better prognosis after BPA.

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