{"title":"Standardizing and predicting results from cardiopulmonary exercise testing in patients with heart failure.","authors":"Robert L Bard, John M Nicklas","doi":"10.1097/00008483-200611000-00008","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Cardiopulmonary exercise testing is a common prognostic tool in heart failure, yet it is not standardized. The purpose of this study was to evaluate a means of standardizing oxygen consumption (VO(2)) measurement and to evaluate the ability to predict peak VO(2) from submaximal exercise.</p><p><strong>Methods: </strong>Fifty consecutive exercise tests with a respiratory exchange ratio > or =1.10 were evaluated. VO(2) was graphed against respiratory exchange ratio and the peak VO(2) was determined with logarithmic, linear, power, and exponential regression lines. To predict a peak VO(2), each patient's submaximal exercise data (respiratory exchange ratio < or =0.98) were fitted to each regression line. The mean of the last 30 seconds of un-averaged breath-by-breath data was used as the reference value. Peak VO(2) assessments are also provided from the metabolic cart, a rolling time average, and the graphical method.</p><p><strong>Results: </strong>Logarithmic regression best standardized peak VO(2). Mean absolute bias (mL x kg x min) was 0.60 +/- 0.44 for logarithmic, 0.61 +/- 0.47 for linear, 0.85 +/- 0.67 for power, and 1.44 +/- 2.22 for exponential. The mean absolute bias between the peak logarithmic predicted VO(2) and the reference peak VO(2) was 1.62 +/- 1.20 mL x kg x min (9.5% of the peak VO(2)).</p><p><strong>Conclusion: </strong>Among the methods studied, logarithmic regression analysis was the best method to standardize and predict peak VO(2) in this cohort of patients with heart failure.</p>","PeriodicalId":15203,"journal":{"name":"Journal of Cardiopulmonary Rehabilitation","volume":"26 6","pages":"384-90"},"PeriodicalIF":0.0000,"publicationDate":"2006-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1097/00008483-200611000-00008","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cardiopulmonary Rehabilitation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/00008483-200611000-00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Cardiopulmonary exercise testing is a common prognostic tool in heart failure, yet it is not standardized. The purpose of this study was to evaluate a means of standardizing oxygen consumption (VO(2)) measurement and to evaluate the ability to predict peak VO(2) from submaximal exercise.
Methods: Fifty consecutive exercise tests with a respiratory exchange ratio > or =1.10 were evaluated. VO(2) was graphed against respiratory exchange ratio and the peak VO(2) was determined with logarithmic, linear, power, and exponential regression lines. To predict a peak VO(2), each patient's submaximal exercise data (respiratory exchange ratio < or =0.98) were fitted to each regression line. The mean of the last 30 seconds of un-averaged breath-by-breath data was used as the reference value. Peak VO(2) assessments are also provided from the metabolic cart, a rolling time average, and the graphical method.
Results: Logarithmic regression best standardized peak VO(2). Mean absolute bias (mL x kg x min) was 0.60 +/- 0.44 for logarithmic, 0.61 +/- 0.47 for linear, 0.85 +/- 0.67 for power, and 1.44 +/- 2.22 for exponential. The mean absolute bias between the peak logarithmic predicted VO(2) and the reference peak VO(2) was 1.62 +/- 1.20 mL x kg x min (9.5% of the peak VO(2)).
Conclusion: Among the methods studied, logarithmic regression analysis was the best method to standardize and predict peak VO(2) in this cohort of patients with heart failure.
目的:心肺运动试验是一种常见的心衰预后工具,但尚未标准化。本研究的目的是评估一种标准化的耗氧量(VO(2))测量方法,并评估从次最大运动中预测VO(2)峰值的能力。方法:对50例呼吸交换比>或=1.10的连续运动试验进行评价。将VO(2)与呼吸交换比作图,并采用对数、线性、功率和指数回归线确定VO(2)峰值。为了预测VO峰值(2),将每个患者的次最大运动数据(呼吸交换比<或=0.98)拟合到每条回归线上。最后30秒非平均呼吸数据的平均值被用作参考值。峰值VO(2)评估也提供了从代谢车,滚动时间平均值和图形方法。结果:对数回归最佳标准化峰值VO(2)。平均绝对偏差(mL x kg x min)对数为0.60 +/- 0.44,线性为0.61 +/- 0.47,功率为0.85 +/- 0.67,指数为1.44 +/- 2.22。峰值对数预测VO(2)与参考峰VO(2)之间的平均绝对偏差为1.62±1.20 mL × kg × min(峰值VO(2)的9.5%)。结论:在研究的方法中,对数回归分析是标准化和预测该心衰患者VO(2)峰值的最佳方法。