Eriksson Göran, Radner Finn, Peterson Stefan, Papapostolou Georgia, Jarenbäck Linnea, Jönsson Saga, Ankerst Jaro, Tunsäter Alf, Tufvesson Ellen, Bjermer Leif
Department of Clinical Sciences, Respiratory Medicine and Allergology, Lund University, Skane University Hospital, Lund, Sweden.
Regional Cancer Centre South, Region Skane, Lund, Sweden.
Eur Clin Respir J. 2019 Nov 20;7(1):1692645. doi: 10.1080/20018525.2019.1692645. eCollection 2020.
: Maximum exercise workload (W) is today assessed as the first part of Cardiopulmonary Exercise testing. The W test exposes patients with COPD, often having cardiovascular comorbidity, to risks. Our research project was initiated with the final aim to eliminate the W test and replace this test with a predicted value of W, based on a prediction algorithm of W derived from multicentre studies. : Baseline data (W, demography, lung function parameters) from 850 COPD patients from four multicentre studies were collected and standardized. A prediction algorithm was prepared using Random Forest modelling. Predicted values of W were used in a new W test, which used a linear increase in order to reach the predicted W within 8 min. The new W test was compared with the standard stepwise W test in a pilot study including 15 patients with mild/moderate COPD. : The best prediction algorithm of W included age, sex, height, weight, and six lung function parameters. FEV and DLCO were the most important predictors. The new W test had a better correlation (R = 0.84) between predicted and measured W than the standard W test (R = 0.66), with slopes of 0.50 and 0.46, respectively. The results from the new W test and the standard W test correlated well. : A prediction algorithm based on data from four large multicentre studies was used in a new W test. The prediction algorithm provided reliable values of predicted W. In comparison with the standard W test, the new W test provided similar overall results.
目前，最大运动负荷（W）被视为心肺运动测试的第一部分。W测试会使慢性阻塞性肺疾病（COPD）患者面临风险，这些患者往往还伴有心血管合并症。我们的研究项目旨在最终取消W测试，并基于多中心研究得出的W预测算法，用W的预测值取代该测试。
收集并标准化了来自四项多中心研究的850名COPD患者的基线数据（W、人口统计学数据、肺功能参数）。使用随机森林建模准备了一种预测算法。W的预测值用于新的W测试，该测试采用线性增加的方式，以便在8分钟内达到预测的W值。在一项包括15名轻度/中度COPD患者的试点研究中，将新的W测试与标准的逐步W测试进行了比较。
W的最佳预测算法包括年龄、性别、身高、体重和六个肺功能参数。第一秒用力呼气容积（FEV）和一氧化碳弥散量（DLCO）是最重要的预测指标。新的W测试在预测W值和实测W值之间的相关性（R = 0.84）优于标准W测试（R = 0.66），斜率分别为0.50和0.46。新的W测试结果与标准W测试结果相关性良好。
基于四项大型多中心研究数据的预测算法被用于新的W测试。该预测算法提供了可靠的W预测值。与标准W测试相比，新的W测试提供了相似的总体结果。
