Saure Eirunn Waatevik, Eagan Tomas Mikal Lind, Jensen Robert Leroy, Voll-Aanerud Marianne, Aukrust Pål, Bakke Per Sigvald, Hardie Jon Andrew
Section of Pulmonary Medicine, Institute of Medicine, University of Bergen, Bergen, Norway.
Clin Respir J. 2012 Apr;6(2):72-80. doi: 10.1111/j.1752-699X.2011.00248.x. Epub 2011 Aug 3.
Variation of blood gas levels in chronic obstructive pulmonary disease (COPD) patients has not been extensively reported and there is limited knowledge about predictors of chronic respiratory failure in COPD patients.
The aim of this study was to identify predictors of hypoxemia, hypercapnia and increased alveolar-arterial oxygen difference in COPD patients. We hypothesized that prediction of arterial blood gases will be improved in multivariate models including measurements of lung function, anthropometry and systemic inflammation.
A cross-sectional sample of 382 Norwegian COPD patients, age 40-76, Global Initiative for Chronic Obstructive Lung Disease stage II-IV, with a smoking history of at least 10 pack-years, underwent extensive measurements, including medical examination, arterial blood gases, systemic inflammatory markers, spirometry, plethysmography, respiratory impedance and bioelectrical impedance. Possible predictors of arterial oxygen (PaO(2)), arterial carbon dioxide (PaCO(2)) and alveolar-arterial oxygen difference (AaO(2)) were analyzed with both bivariate and multiple regression methods.
We found that various lung function measurements were significantly associated with PaO2, PaCO(2) and AaO(2). In addition, heart rate and Fat Mass Index were predictors of PaO(2) and AaO(2), while heart failure and current smoking status were associated with PaCO(2). The explained variance (R(2)) in the final multivariate regression models was 0.14-0.20.
With a wide assortment of possible clinical predictors, we could explain 14-20% of the variation in blood gas measurements in COPD patients.
慢性阻塞性肺疾病（COPD）患者血气水平的变化尚未得到广泛报道，且对于COPD患者慢性呼吸衰竭的预测因素了解有限。
本研究旨在确定COPD患者低氧血症、高碳酸血症和肺泡-动脉血氧分压差增加的预测因素。我们假设，在包含肺功能、人体测量学和全身炎症测量指标的多变量模型中，动脉血气的预测效果会得到改善。
对382名年龄在40 - 76岁、慢性阻塞性肺疾病全球倡议组织（GOLD）分级为II - IV级、吸烟史至少10包年的挪威COPD患者进行横断面抽样研究，这些患者接受了广泛的测量，包括医学检查、动脉血气分析、全身炎症标志物检测、肺量计检查、体积描记法、呼吸阻抗和生物电阻抗测量。采用双变量和多元回归方法分析动脉血氧分压（PaO₂）、动脉血二氧化碳分压（PaCO₂）和肺泡-动脉血氧分压差（AaO₂）的可能预测因素。
我们发现各种肺功能测量指标与PaO₂、PaCO₂和AaO₂显著相关。此外，心率和脂肪质量指数是PaO₂和AaO₂的预测因素，而心力衰竭和当前吸烟状态与PaCO₂相关。最终多变量回归模型中的解释方差（R²）为0.14 - 0.20。
通过多种可能的临床预测因素，我们能够解释COPD患者血气测量值中14% - 20%的变异。
