Predicting New-onset Exertional and Resting Hypoxemia in Fibrotic Interstitial Lung Disease

医学 低氧血症 间质性肺病 队列 心脏病学 内科学 特发性肺纤维化 肺活量 扩散能力 比例危险模型 危险系数 置信区间 肺功能
作者
Ferhan Saleem,Christopher J. Ryerson,Nandini Sarma,Kerri A. Johannson,Veronica Marcoux,Jolene H. Fisher,Deborah Assayag,H. Manganas,Nasreen Khalil,Julie Morisset,Ian Glaspole,Nicole Goh,Justin M. Oldham,Gerard Cox,Charlene D. Fell,Andrea S. Gershon,Andrew J. Halayko,Nathan Hambly,S.D. Lok,Shane Shapera,Teresa To,Pearce Wilcox,Alyson W. Wong,Martin Kolb,Yet H. Khor
出处
期刊:Annals of the American Thoracic Society [American Thoracic Society]
卷期号:20 (12): 1726-1734 被引量:3
标识
DOI:10.1513/annalsats.202303-208oc
摘要

Rationale: Hypoxemia in fibrotic interstitial lung disease (ILD) indicates disease progression and is of prognostic significance. The onset of hypoxemia signifies disease progression and predicts mortality in fibrotic ILD. Accurately predicting new-onset exertional and resting hypoxemia prompts appropriate patient discussion and timely consideration of home oxygen. Objectives: We derived and externally validated a risk prediction tool for both new-onset exertional and new-onset resting hypoxemia. Methods: This study used ILD registries from Canada for the derivation cohort and from Australia and the United States for the validation cohort. New-onset exertional and resting hypoxemia were defined as nadir oxyhemoglobin saturation < 88% during 6-minute-walk tests, resting oxyhemoglobin saturation < 88%, or the initiation of ambulatory or continuous oxygen. Candidate predictors included patient demographics, ILD subtypes, and pulmonary function. Time-varying Cox regression was used to identify the top-performing prediction model according to Akaike information criterion and clinical usability. Model performance was assessed using Harrell's C-index and goodness-of-fit (GoF) likelihood ratio test. A categorized risk prediction tool was developed. Results: The best-performing prediction model for both new-onset exertional and new-onset resting hypoxemia included age, body mass index, a diagnosis of idiopathic pulmonary fibrosis, and percent predicted forced vital capacity and diffusing capacity of carbon monoxide. The risk prediction tool exhibited good performance for exertional hypoxemia (C-index, 0.70; GoF, P = 0.85) and resting hypoxemia (C-index, 0.77; GoF, P = 0.27) in the derivation cohort, with similar performance in the validation cohort except calibration for resting hypoxemia (GoF, P = 0.001). Conclusions: This clinically applicable risk prediction tool predicted new-onset exertional and resting hypoxemia at 6 months in the derivation cohort and a diverse validation cohort. Suboptimal GoF in the validation cohort likely reflected overestimation of hypoxemia risk and indicated that the model is not flawed because of underestimation of hypoxemia.
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