Multidisciplinary-derived clinical score for accurate prediction of long-term mortality in fibrotic lung disease patients

多学科综合临床评分可准确预测肺纤维化患者的长期死亡率

阅读:1

Abstract

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) stands out as one of the most aggressive forms of interstitial lung diseases (ILDs), currently without a definitive cure. Multidisciplinary discussion (MDD) is now considered a cornerstone in diagnosing and differentiating ILD subtypes. The Gender-Age-Physiology (GAP) score, developed to assess IPF prognosis based on sex, age, forced vital capacity, and diffusion capacity for carbon monoxide (DLCO), is limited in not considering dyspnea and functional impairment during the walking test. We proposed a MDD-based clinical score for mortality prediction among those patients. METHODS: From December 2018 to December 2019, we enrolled ILD patients with IPF and non-IPF and followed-up them till December 2020. Based on DLCO, modified Medical Research Council (mMRC) Dyspnea Scale, and six-minute walking test (6MWT) distance, a functional score was developed for mortality prediction. RESULTS: We enrolled 104 ILD patients, 12 (11.5%) died by the one-year follow-up. In receiver operating characteristic (ROC) curve analysis, DLCO (% predicted) was the most accurate variable predicting one-year mortality with an area under curve (AUC) of 0.88 (95% confidence interval [CI] = 0.80-0.94), followed by mMRC Dyspnea Score (AUC = 0.82 [95% CI = 0.73-0.89]), 6MWT distance (AUC = 0.80 [95% CI = 0.71-0.88]), and GAP score (AUC = 0.77 [95% CI = 0.67-0.84]). Only the GAP score (hazard ratio [HR] = 1.55, 95% CI = 1.03-2.34, p = 0.0.37) and functional score (HR = 3.45, 95% CI = 1.11-10.73, p = 0.032) were significantly associated with one-year mortality in multivariable analysis. CONCLUSION: The clinical score composite of DLCO, mMRC Dyspnea Scale, and 6MWT distance could provide an accurate prediction for long-term mortality in ILD patients, laying out a helpful tool for managing and following these patients.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。