Medicine, Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
Sleep Medicine, Atlanta VA Medical Center, Decatur, Georgia, USA.
J Investig Med. 2021 Jun;69(5):1027-1034. doi: 10.1136/jim-2020-001663. Epub 2021 Feb 11.
In pulmonary function testing by spirometry, bronchodilator responsiveness (BDR) evaluates the degree of volume and airflow improvement in response to an inhaled short-acting bronchodilator (BD). The traditional, binary categorization (present vs absent BDR) has multiple pitfalls and limitations. To overcome these limitations, a novel classification that defines five categories (negative, minimal, mild, moderate and marked BDR), and based on % and absolute changes in forced expiratory volume in 1 s (FEV), has been recently developed and validated in patients with chronic obstructive pulmonary disease, and against multiple objective and subjective measurements. In this study, working on several large spirometry cohorts from two different institutions (n=31 598 tests), we redefined the novel BDR categories based on delta post-BD-pre-BD FEV % predicted values. Our newly proposed BDR partition is based on several distinct intervals for delta post-BD-pre-BD % predicted FEV using Global Lung Initiative predictive equations. In testing, training and validation cohorts, the model performed well in all BDR categories. In a validation set that included only normal baseline spirometries, the partition model had a higher rate of misclassification, possibly due to unrestricted BD use prior to baseline testing. A partition that uses delta % predicted FEV with the following intervals ≤0%, 0%-2%, 2%-4%, 4%-8% and >8% may be a valid and easy-to-use tool for assessing BDR in spirometry. We confirmed in our cohorts that these thresholds are characterized by low variance and that they are generally gender-independent and race-independent. Future validation in other cohorts and in other populations is needed.
在肺功能测试中，支气管扩张剂反应性（BDR）评估了吸入短效支气管扩张剂（BD）后体积和气流改善的程度。传统的二元分类（BDR 存在或不存在）存在多个缺陷和局限性。为了克服这些局限性，最近开发了一种新的分类方法，该方法定义了五个类别（阴性、最小、轻度、中度和显著 BDR），并基于 1 秒用力呼气量（FEV）的百分比和绝对值变化，已经在慢性阻塞性肺疾病患者中进行了验证，并与多种客观和主观测量方法进行了比较。在这项研究中，我们在来自两个不同机构的几个大型肺功能测试队列中（n=31598 次测试）工作，根据支气管扩张剂后-支气管扩张剂前 FEV %预计值的变化，重新定义了新的 BDR 类别。我们新提出的 BDR 分区是基于 Global Lung Initiative 预测方程中几个不同的 delta 后-BD-前-BD %预测 FEV 间隔。在测试、训练和验证队列中，该模型在所有 BDR 类别中表现良好。在仅包括正常基线肺功能测试的验证集中，分区模型的分类错误率更高，这可能是由于在基线测试之前不受限制地使用了 BD。使用 delta %预测 FEV 的分区，其间隔为 ≤0%、0%-2%、2%-4%、4%-8%和 >8%，可能是评估肺功能测试中 BDR 的有效且易于使用的工具。我们在我们的队列中证实，这些阈值的方差较低，并且它们通常与性别无关，与种族无关。需要在其他队列和其他人群中进行进一步验证。
