The thermal equivalent is a value derived from your averaged respiratory exchange ratio that expresses the kilocalories burned per liter of oxygen consumed. Academic Calendar Administrative Offices Bookstore Campus Life Libraries Student Accounts Undergraduate Student Resources Law Student Affairs MBA Student Affairs Student Health Student Resources.

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Willamette University Home Undergraduate Programs Exercise and Health Science Laboratory-Testing Services Available Resting Metabolic Rate. Resting Metabolic Rate. Services Available MENU In this Section Aerobic Capacity VO2max Anaerobic Testing Body Composition Lactate Threshold Resting Metabolic Rate.

In general, individuals who are the least fit see the largest changes and individuals who are highly fit see the smallest changes. Significant amounts of research and public health data indicate that low aerobic fitness levels are correlated with an increased risk of premature death from many causes but in particular from cardiovascular disease.

Accordingly, higher aerobic fitness levels are associated with numerous health benefits e. longer lifespan, better quality of life, reduced risks for stroke, heart disease, diabetes and cancer, improved mood and self-esteem, and improved sleep patterns. To improve or maintain cardiovascular health an individual must engage in cardiovascular exercise run, walk, swim, bike, etc at least 3 times per week.

also playing a role. In general, however the higher a V̇O 2 max the more potential for a successful performance in an aerobic endurance event.

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Metabolic, nutritional and inflammatory characteristics in elderly women with advanced cancer. J Geriatr Oncol. Yeung SSY, Reijnierse EM, Trappenburg MC, Meskers CGM, Maier AB. Clinical determinants of resting metabolic rate in geriatric outpatients.

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Even though our models performed better than other formulae in predicting V̇ o 2 in this particular population, the limits of agreement were wide, particularly in older individuals with shorter stature, higher heart rate, and lower MVV.

Oxygen consumption is an essential measurement for the calculation of cardiac output by the accepted standard, Fick methodology; however, in the cardiac catheterization laboratories, V̇ o 2 is commonly estimated instead of measured, given that it is time-consuming and requires especial equipment ie, breath-by-breath metabolic cart analysis and expertise.

As a result, in clinical practice, V̇ o 2 is often estimated by a variety of equations that generally use a combination of variables such as BSA, age, gender, and heart rate. Several investigators have noted poor agreement between measured and estimated V̇ o 2 in different groups of adult patients.

In fact, many factors can affect the measured V̇ o 2 including age, 8 , 11 gender, 8 , 11 , 13 , 23 , 25 BSA, 8 , 11 , 13 , 23 , 25 fat-free mass, heart rate, 11 , 13 , 25 degree of sedation, 9 , 14 , 25 temperature of the patient and environment , 25 time of day, prior food intake, level of activity, 25 and position.

Although several parameters were associated with resting V̇ o 2 in multivariate models, only BSA, gender, heart rate, breathing frequency, need for supplementary O 2 , and minute ventilation were significant predictors. Because V̇ o 2 directly depends on the body size of a person, BSA is the most commonly used variable in available equations.

In fact, BSA was used in all but two 10 , 12 of the tested formulae for resting V̇ o 2 estimation. The formulae proposed by Krovetz et al 10 uses height and weight and the equation by Lindahl 12 only weight.

Men have a higher V̇ o 2 than women, given the higher fat-free mass. Therefore, gender was selected in three 8 , 11 , 13 out of the 7 formulae tested. Similarly, heart rate, an indicator of stress that changes in relation to the metabolic rate, was used in 2 out of the 7 equations.

Breathing frequency, need for supplementary O 2 , and minute ventilation were not included in prior equations that estimate resting V̇ o 2 , likely because these parameters are more applicable to our particular group of subjects with respiratory symptoms.

It is important to consider that, immediately before cardiopulmonary exercise testing or cardiac catheterization, patients are not in a strictly basal state as they may be anxious, a condition that may lead to an increase in minute ventilation, heart rate, and V̇ o 2.

Age, as log e age , was used in two 8 , 11 formulae, obtained in cohorts that included children and adults. Furthermore, specific determinations of general value in pulmonary patients, that is, arterial blood gases or spirometry, did not add prognostic value.

This could reflect that F IO 2 model 1 , breathing frequency model 2 , and minute ventilation model 3 are better and probably more comprehensive estimates of V̇ o 2 than other more specific parameters obtained from spirometry or arterial blood gases.

In general, the formulae that estimate V̇ o 2 are associated with systematic error as they tend to underestimate the higher V̇ o 2 values and overestimate the lower determinations. In our study, we observed that the estimated V̇ o 2 was mostly inaccurate in older individuals with shorter stature, higher heart rate, and lower MVV.

The reasons for the greater discrepancies between measured and estimated V̇ o 2 in this group of subjects remain unclear. A potential explanation include a nonlinear relationship between V̇ o 2 and age, height, MVV, or heart rate.

It is possible that, due to the limited number of subjects at the end of these spectra, our model was not sensitive enough to detect this nonlinear association. Future studies testing particular subgroups of subjects may be of value to refine our equations. The V̇ o 2 variance not captured in our study might be explained by variables that we did not measure, such as fat-free mass, core temperature, and general level of activity.

It is also likely that there are unknown factors that might be responsible for the V̇ o 2 variation. Given that V̇ o 2 varies greatly and estimations are still generally inaccurate, we support the direct measurement of V̇ o 2 instead of its estimation.

It is also important to point out that V̇ o 2 varies in patients with sepsis, 26 , 27 hypovolemia, 28 pulmonary hypertension, 29 congestive heart failure, 30 or COPD, 31 both at baseline and with treatment. Notwithstanding these limitations, our study emphasizes the lack of accuracy of formulae to predict V̇ o 2 and is the first to generate different models to estimate resting V̇ o 2 in subjects with respiratory symptoms or conditions, and to compare them with available formulae.

This study would not have been possible without the hard work of Cleveland Clinic respiratory therapists who performed the cardiopulmonary exercise test and contributed to the database. This publication was supported by CTSA KL2 grant TR to Dr Tonelli from the National Center for Research Resources, a component of the National Institutes of Health, and by National Institutes of Health Roadmap for Medical Research.

The authors have disclosed no other conflicts of interest. NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail.

We do not capture any email address. Skip to main content. Research Article Original Research. Adriano R Tonelli , Xiao-Feng Wang , Anara Abbay , Qi Zhang , José Ramos and Kevin McCarthy.

Adriano R Tonelli. Department of Pulmonary, Allergy and Critical Care Medicine, Respiratory Institute, Cleveland Clinic. Respiratory Institute Biostatistics Core, Quantitative Health Sciences, Cleveland Clinic. Medicine Institute, Cleveland Clinic, Cleveland, Ohio.

Introduction The available equations to estimate oxygen consumption V̇ o 2 were obtained from selected populations eg, children with congenital heart diseases that commonly differ from the patients encountered in clinical practice Table 1.

Table 1. Formulae to Estimate V̇ o 2. QUICK LOOK Current knowledge Equations to estimate oxygen consumption V̇ o 2 have not been systematically studied in patients with lung diseases or respiratory symptoms.

What this paper contributes to our knowledge New formulae to predict V̇ o 2 in subjects undergoing cardiopulmonary exercise testing for respiratory symptoms were developed using F IO 2 , minute volume, and breathing frequency.

Methods Subject Selection and Study Design The research protocol was approved by the Cleveland Clinic institutional review board study Statistical Analysis Continuous data are presented as mean ± SD or median interquartile range where appropriate.

Results Overall Characteristics of the Study Population We included subjects, of whom subjects formed part of the training cohort used to build the lineal regression models and of the validation group used to test the proposed and available formulae to estimate V̇ o 2.

View this table: View inline View popup Download powerpoint. Table 2. Characteristics of the Testing and Validation Cohorts. Table 3. Comparison of the New Models to Predict V̇ o 2 with Established Ones In the validation cohort, we compared our 3 models with 7 other available formulae that estimate resting V̇ o 2 Table 4.

Table 4. Discussion In the present study, we noted a poor accuracy between the measured and estimated V̇ o 2 in subjects with respiratory symptoms. Acknowledgments This study would not have been possible without the hard work of Cleveland Clinic respiratory therapists who performed the cardiopulmonary exercise test and contributed to the database.

Footnotes Correspondence: Adriano Tonelli MD, Euclid Avenue A, Cleveland, OH E-mail: tonella{at}ccf. References 1. Inaccuracy of estimated resting oxygen uptake in the clinical setting.

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Assumed oxygen consumption based on calculation from dye dilution cardiac output: an improved formula. Wear comfortable clothing, the test itself takes approximately 20 min.

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