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ASIG 算法在接受年度肺动脉高压筛查的系统性硬化症前瞻性队列中的预测准确性。

Predictive accuracy of the ASIG algorithm in a prospective systemic sclerosis cohort undergoing annual screening for pulmonary arterial hypertension.

机构信息

Department of Medicine, The University of Melbourne at St Vincent's Hospital, Melbourne, Victoria, Australia.

Department of Rheumatology, St Vincent's Hospital (Melbourne), Melbourne, Victoria, Australia.

出版信息

Intern Med J. 2024 Sep;54(9):1561-1566. doi: 10.1111/imj.16468. Epub 2024 Aug 13.

Abstract

The Australian Scleroderma Interest Group (ASIG) algorithm for screening pulmonary arterial hypertension (PAH) in systemic sclerosis (SSc) requires only respiratory function tests and serum N-terminal pro-brain natriuretic peptide as first-tier tests, and is recommended in international guidelines. In this communication, we present the findings of the application of the ASIG screening algorithm to a Singaporean cohort undergoing prospective annual screening for PAH, which shows a high negative predictive value. The ASIG algorithm may offer an alternative to more complex and costly SSc-PAH screening algorithms.

摘要

澳大利亚硬皮病兴趣小组(ASIG)的肺动脉高压(PAH)筛查算法在系统性硬化症(SSc)中仅需要进行呼吸功能测试和血清 N 端脑利钠肽前体作为一线检测,这一方法已被国际指南推荐。在本通讯中,我们报告了 ASIG 筛查算法在新加坡队列中进行年度前瞻性 PAH 筛查的应用结果,该算法具有较高的阴性预测值。ASIG 算法可能为更复杂和昂贵的 SSc-PAH 筛查算法提供了替代方案。

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