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改善过期气体分析间接测热法数据处理的建议。

Recommendations for improved data processing from expired gas analysis indirect calorimetry.

机构信息

Exercise and Sports Sciences, University of Western Sydney, Sydney, New South Wales, Australia.

出版信息

Sports Med. 2010 Feb 1;40(2):95-111. doi: 10.2165/11319670-000000000-00000.

Abstract

There is currently no universally recommended and accepted method of data processing within the science of indirect calorimetry for either mixing chamber or breath-by-breath systems of expired gas analysis. Exercise physiologists were first surveyed to determine methods used to process oxygen consumption ((.)VO2) data, and current attitudes to data processing within the science of indirect calorimetry. Breath-by-breath datasets obtained from indirect calorimetry during incremental exercise were then used to demonstrate the consequences of commonly used time, breath and digital filter post-acquisition data processing strategies. Assessment of the variability in breath-by-breath data was determined using multiple regression based on the independent variables ventilation (VE), and the expired gas fractions for oxygen and carbon dioxide, FEO2 and FECO2, respectively. Based on the results of explanation of variance of the breath-by-breath (.)VO2 data, methods of processing to remove variability were proposed for time-averaged, breath-averaged and digital filter applications. Among exercise physiologists, the strategy used to remove the variability in (.)VO2 measurements varied widely, and consisted of time averages (30 sec [38%], 60 sec [18%], 20 sec [11%], 15 sec [8%]), a moving average of five to 11 breaths (10%), and the middle five of seven breaths (7%). Most respondents indicated that they used multiple criteria to establish maximum ((.)VO2 ((.)VO2max) including: the attainment of age-predicted maximum heart rate (HR(max)) [53%], respiratory exchange ratio (RER) >1.10 (49%) or RER >1.15 (27%) and a rating of perceived exertion (RPE) of >17, 18 or 19 (20%). The reasons stated for these strategies included their own beliefs (32%), what they were taught (26%), what they read in research articles (22%), tradition (13%) and the influence of their colleagues (7%). The combination of VE, FEO2 and FECO2 removed 96-98% of (.)VO2 breath-by-breath variability in incremental and steady-state exercise (.)VO2 data sets, respectively. Correction of residual error in (.)VO2 datasets to 10% of the raw variability results from application of a 30-second time average, 15-breath running average, or a 0.04 Hz low cut-off digital filter. Thus, we recommend that once these data processing strategies are used, the peak or maximal value becomes the highest processed datapoint. Exercise physiologists need to agree on, and continually refine through empirical research, a consistent process for analysing data from indirect calorimetry.

摘要

目前,间接量热法领域内并没有一种被广泛推荐和接受的混合室或呼吸气体分析逐口气方法的数据处理方法。首先,我们调查了运动生理学家用来处理耗氧量(VO2)数据的方法,以及当前他们对间接量热法领域内数据处理的态度。然后,我们使用间接量热法在递增运动期间获得的逐口气数据集来演示常用的时间、呼吸和数字滤波器后获取数据处理策略的后果。通过基于独立变量通气量(VE)和氧气和二氧化碳的呼出气体分数,FEO2 和 FECO2,对逐口气数据的可变性进行了多次回归评估。根据方差解释的结果,提出了用于去除时间平均、呼吸平均和数字滤波器应用中可变性的处理方法。在运动生理学家中,用于去除 VO2 测量值中可变性的策略差异很大,包括时间平均值(30 秒 [38%]、60 秒 [18%]、20 秒 [11%]、15 秒 [8%])、五到十一口气的移动平均值(10%)和七口气的中间五口气(7%)。大多数受访者表示,他们使用多种标准来确定最大 VO2(VO2max),包括达到预测的最大心率(HRmax)[53%]、呼吸交换比(RER)>1.10(49%)或 RER >1.15(27%)以及感知用力程度(RPE)>17、18 或 19(20%)。选择这些策略的原因包括他们自己的信念(32%)、他们所学的内容(26%)、他们在研究文章中读到的内容(22%)、传统(13%)和同事的影响(7%)。VE、FEO2 和 FECO2 分别去除递增和稳态运动 VO2 数据集的 96-98%的 VO2 逐口气可变性。通过应用 30 秒时间平均值、15 次呼吸平均值或 0.04 Hz 低截止数字滤波器,将 VO2 数据集的剩余误差校正为原始可变性的 10%。因此,我们建议一旦使用这些数据处理策略,峰值或最大值就成为最高处理的数据点。运动生理学家需要通过实证研究达成一致,并不断完善分析间接量热法数据的一致过程。

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