Recommendations for improved data processing from expired gas analysis indirect calorimetry.
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 consum...
| Publicado en: | Sports Medicine Vol. 40; no. 2; pp. 95 - 112 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105120645&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105120645 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01121642 C5H jtl: Sports Medicine issn: 01121642 maglogo: N pubinfo: dt: 2010 vid: 40 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105120645 2010566367 10.2165/11319670-000000000-00000 NLM20092364 105120645 ppf: 95 ppct: 17 formats: tig: atl: Recommendations for improved data processing from expired gas analysis indirect calorimetry. aug: au: Robergs RA Dwyer D Astorino T affil: Exercise and Sports Sciences, University of Western Sydney, Sydney, New South Wales, Australia; r.robergs@uws.edu.au sug: subj: Calorimetry Data Analysis, Statistical Methods Exercise Test, Cardiopulmonary Oxygen Consumption Evaluation Pulmonary Gas Exchange Evaluation Attitude of Health Personnel Data Collection Methods Descriptive Statistics Exercise Physiology Expert Clinicians Human Internet Linear Regression Measurement Issues and Assessments Models, Theoretical Multiple Regression Nomenclature Questionnaires Respiratory Rate Signal Transduction Survey Research Time Factors Validity ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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