Oxygen uptake efficiency slope as a useful measure of cardiorespiratory fitness in morbidly obese women

Tatiana Onofre; Nicole Oliver; Renata Carlos; Amanda Felismino; Renata Cristina Corte; Eliane Silva; Selma Bruno

doi:10.1371/journal.pone.0172894

Abstract

Cardiopulmonary assessment through oxygen uptake efficiency slope (OUES) data has shown encouraging results, revealing that we can obtain important clinical information about functional status. Until now, the use of OUES has not been established as a measure of cardiorespiratory capacity in an obese adult population, only in cardiac and pulmonary diseases or pediatric patients. The aim of this study was to characterize submaximal and maximal levels of OUES in a sample of morbidly obese women and analyze its relationship with traditional measures of cardiorespiratory fitness, anthropometry and pulmonary function. Thirty-three morbidly obese women (age 39.1 ± 9.2 years) performed Cardiopulmonary Exercise Testing (CPX) on a treadmill using the ramp protocol. In addition, anthropometric measurements and pulmonary function were also evaluated. Maximal and submaximal OUES were measured, being calculated from data obtained in the first 50% (OUES_50%) and 75% (OUES_75%) of total CPX duration. In one-way ANOVA analysis, OUES did not significantly differ between the three different exercise intensities, as observed through a Bland-Altman concordance of 58.9 mL/min/log(L/min) between OUES_75% and OUES_100%, and 0.49 mL/kg/min/log(l/min) between OUES/kg_75% and OUES/kg_100%. A strong positive correlation between the maximal (r = 0.79) and submaximal (r = 0.81) OUES/kg with oxygen consumption at peak exercise (VO_2peak) and ventilatory anaerobic threshold (VO_2VAT) was observed, and a moderate negative correlation with hip circumference (r = -0.46) and body adiposity index (r = -0.50) was also verified. There was no significant difference between maximal and submaximal OUES, showing strong correlations with each other and oxygen consumption (peak and VAT). These results indicate that OUES can be a useful parameter which could be used as a cardiopulmonary fitness index in subjects with severe limitations to perform CPX, as for morbidly obese women.

Citation: Onofre T, Oliver N, Carlos R, Felismino A, Corte RC, Silva E, et al. (2017) Oxygen uptake efficiency slope as a useful measure of cardiorespiratory fitness in morbidly obese women. PLoS ONE 12(4): e0172894. https://doi.org/10.1371/journal.pone.0172894

Editor: Tiago M. Barbosa, Nanyang Technological University, SINGAPORE

Received: October 21, 2016; Accepted: February 10, 2017; Published: April 6, 2017

Copyright: © 2017 Onofre et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Cardiopulmonary Exercise Testing (CPX) has been widely applied to assess the cardiopulmonary fitness of morbidly obese individuals [1–3]. Similar to other clinical incapacitating conditions, the obese are more susceptible to develop several alterations and diminished response during CPX [4,5]. The main finding is reduced oxygen consumption relative to body weight at exercise peak (VO_2peak, mL/kg/min) when compared to lean individuals [6,7]. This low capacity for exercise can be influenced by cardiovascular, pulmonary or peripheral reasons [8,9]. Furthermore, individuals with extreme obesity can present energy inefficiencies and biomechanical abnormalities, mainly due to alterated walking pattern and/or orthopedic pain which can limit their maximal physical effort [10,11]; in turn, it contributes to abnormal response with early interruption of CPX [5].

In addition to the primary clinically and scientifically accepted key variables, other additional variables based on emerging scientific evidence have been gaining acceptance in cardiorespiratory assessment during CPX. Considering this, oxygen uptake efficiency slope (OUES) was first proposed by Baba et al. [12] as a submaximal index of cardiopulmonary functional reserve. OUES is derived from the relationship between oxygen consumption (VO₂, mL/min; plotted on the y axis) and the log transformation of minute ventilation (VE, L/min; x axis). Thus, it is a metric that expresses the ventilatory requirement for a given VO₂. OUES has been extensively assessed and correlated with VO_2peak in cardiac diseases [13–15], indicating it as a valid index for exercise tolerance. A consistent body of literature [14,16–18] has demonstrated that exercise intensity (submaximal or maximal) does not affect OUES values, thus being a reason for the expressive use of this index in clinical conditions which prevent patients from being able to perform an entire CPX.

OUES has been extensively applied in heart [13,14,19] or pulmonary disease [18,20,21], or both [22], and has revealed significantly lower OUES according to the disease severity. Reference equations for OUES have been proposed [23,24], however until now the use of OUES has not been established as a measure of cardiorespiratory fitness in an obese adult population. Only two studies have been conducted with OUES in obese, albeit using a pediatric sample [25,26]. The cardiopulmonary condition through OUES data have demonstrated clinical promise, revealing that we can obtain important clinical information using OUES about functional status and disease severity without necessarily exposing the patient to maximal physical effort [14,16,27].

Thus, the main aim of this study was to characterize submaximal and maximal OUES in morbidly obese women; secondly, to analyse the relationship among OUES and the traditional measures of cardiorespiratory fitness, anthropometry and pulmonary function, and lastly to understand if these results produce the same clinical information in other populations. Taking into account that morbidly obese individuals have extreme physical limitations and cannot sustain exercise at maximal level and due to a lack of data in this specific population, we hypothesized that OUES can be potentially useful to assess functional capacity in these subjects.

Materials and methods

Subjects and procedures

All participants signed an informed consent before start the research procedure. With Human Research Ethics Committee approval from the Federal University of Rio Grande do Norte-UFRN (488.283), signature of free informed consent form and trial registration number (RBR-7m2756) in ReBEC, we prospectively assessed the anthropometry, pulmonary function and aerobic capacity as a preoperative routine of bariatric surgery in the Cardiopulmonary Rehabilitation and Metabolic Unit of University Hospital-UH/UFRN. Thirty-three morbidly obese women (mean±SD age of 39.1±9.2years; weight 117.7±16.6kg; height 158.1±6.2cm) were selected by convenience from Obesity Surgery and Related Disease Service of the UH and met the inclusion criteria of the study, being: adult females (age range between 20 and 59 years), and having body mass index (BMI) ≥ 40kg/m². Women with orthopedic limitations, chronic renal failure requiring dialysis, diagnosed pulmonary or cardiovascular diseases were excluded.

Outcome measures

Anthropometric measures of general (weight, height) and peripheral adiposity (neck—NC, waist—WC, and hip—HC circumferences) were taken to calculate BMI, body adiposity index (BAI) [28] and waist-to-hip ratio (WHR). Spirometric function [29] was assessed according to acceptability and reproducibility of the American Thoracic Society (ATS) [30], using a previously calibrated DATOSPIR 120 C spirometer (SIBELMED, Barcelona, Spain W20).

Symptom-limited CPX was performed on a treadmill (Centurion 300, Micromed) using a breath-by-breath gas analyzer (Cortex Metamax3B Biophysik, Germany). Ramp protocol [31] up to the tolerable limit for the patient was implemented and the subjects were continuously monitored by electrocardiographic 12-lead tracing (ErgoPC Elite 3.4). Blood pressure measurements, peripheral O₂ saturation and perceived exertion using the Borg Scale were recorded every 2 minutes. Metabolic/ventilatory variables (VO₂; carbon dioxide production, VCO₂ and VE-minute ventilation) were measured continuously. Derived variables such as respiratory exchange ratio (RER) and ventilatory equivalent for oxygen (VE/VO₂) and carbon dioxide (VE/VCO₂) were also analyzed, as well as VE/VCO_2slope and partial pressures of expired oxygen (PetO₂) and carbon dioxide (PetCO₂). VO_2peak was expressed as the highest VO₂ reached during the last 10 seconds of the test. Ventilatory anaerobic threshold (VAT) was determined through VE/VO₂ and VE/VCO₂ curves, considering the beginning of the turning point boundary in the VE/VO₂ graph, as the VE/VCO₂ remained constant, or by using the V-slope method [32]. Each test was preceded by daily calibration of the apparatus. The criteria for CPX interruption were strictly followed in accordance with the standardization of ATS [33]. We used the equations proposed by Wasserman et al. [34] to analyze the predicted VO_2peak values. OUES resulted from linear regression analysis from the following equation: which the constant "a" is the value of OUES, which represents the rate of increase in VO₂ in response to a given increase in VE, and "b" is the intercept (Fig 1). In order to assess its usefulness as a cardiopulmonary index derived from a submaximal exercise test, OUES was also calculated from data obtained in the first 50% (OUES_50%) and 75% (OUES_75%) of the total CPX duration. The prediction equation used for OUES values was recently proposed by Buys et al. [35]. As body weight directly affects the relative VO₂ values reached, and OUES results from a regression analysis involving VO₂, we also calculated OUES relative to body weight (OUES/kg).

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Fig 1. The relationship between VO₂ and VE during cardiopulmonary exercise testing in a single 36-year old morbidly obese woman.

A, Linear x-axis. B, Semilog x-axis (OUES). VO₂, oxygen consumption; VE, minute ventilation; OUES, oxygen uptake efficiency slope; SEE, standard error.

https://doi.org/10.1371/journal.pone.0172894.g001

Statistical analysis

Were estimated power and sample size based on effect magnitude among OUES/mL 100% and 75%. It was necessary 36 women to detect 30.6mL of difference considering α (two sided, 0,05%) and β (error type I) of 20%.

Unless otherwise specified, the data were presented as mean and standard deviation. Pearson correlation coefficients were calculated to test the possibility and magnitude of association between the three intensities of OUES (50%, 75%, 100%) and CPX respiratory/metabolic parameters, anthropometric measurements and pulmonary function. Linear regression analysis was used to investigate the relationships of OUES values with each other and the variables that were significant in the initial correlation model, meaning as a variable influencing the other. In order to verify the existence of significant differences between the OUES means and the three different levels of exercise (factor), an analysis of variance (one-way ANOVA) was performed. ANCOVA was performed to test effect of age and WHR as potencial confounding on final OUES. Bland-Altman plot (SPSS for Windows, Version 20.0, Chicago, IL, USA) was used to assess the level of agreement between maximal and submaximal OUES (including confidence interval-CI) and other analyzes were performed using the Statistica version 10.0 software (StatSoft, USA). A level of P<0.05 was considered to be statistically significant.

Results

In total, 45 morbidly obese women were recruited; however, 12 were excluded for the following reasons: chronic renal failure requiring dialysis, n = 2; uncontrolled arrhythmias, n = 2; orthopedic impairments, n = 5; and asthma, n = 3. Thus, 33 patients remained (mean±SD age = 39.1±9.2years; height = 158.1±6.2cm; BMI = 47.1±5.8kg/m²), with their clinical and anthropometric characteristics and pulmomary function shown in Table 1. Self-reported dyspnea was the main cause of interrupting CPX, corresponding to 60.6% of the sample, followed by fatigue of the lower limbs (30.3%), maximum heart rate-HRmax>predicted (6.1%) and systolic blood pressure>220mmHg associated with hemodynamic repercussions (3.0%).

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Table 1. Clinical and anthropometric characteristics and pulmonary function of study population.

https://doi.org/10.1371/journal.pone.0172894.t001

The cardiorespiratory parameters including the maximal and submaximal OUES values during CPX are shown in Table 2. Using one-way ANOVA and ANCOVA analysis, we observed there was no significant difference in mean OUES values (P = 0.420) or OUES/kg (P = 0.430) between three different exercise intensities (50%, 75%, 100%). ANCOVA do not showed effect on OUES/kg by age (P = 0.876), and WHR (P = 0.960). Using Bland-Altman plotting, we also observed an agreement of 58.9 mL/min /log(L/min) (95%; CI: -282.7–400.5) between OUES_75% and OUES_100%, and of 0.49 mL/kg/min/log(L/min) (95%; CI: -2.09–3.07) between OUES/kg_75% and OUES/kg_100% (Fig 2).

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Table 2. Distribution of cardiorespiratory parameters during CPX in 33 morbidly obese women.

https://doi.org/10.1371/journal.pone.0172894.t002

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Fig 2. Bland-Altman plots of the relationship of OUES_75% and OUES_100%.

Each dot corresponds to a subject. Horizontal lines represent the bias and the upper and lower limits of agreement.

https://doi.org/10.1371/journal.pone.0172894.g002

Weak correlations were found between OUES_100% and anthropometric measures, however, when adjusted for body weight, OUES/kg_100% moderately correlated with HC (r = -0.46, P<0.05) and BAI (r = -0.50, P<0.01). There were no significant correlations between OUES values with pulmonary function (FEV₁ and FVC), only a weak correlation between OUES_75% and MVV (r = 0.39, P<0.05). However, maximal and submaximal OUES were strongly correlated with VO_2peak, VO_2VAT and predicted% OUES values, while being moderately correlated with VE/VO_2peak (Table 3). Some of these relationships may be seen in Fig 3, also showing (through equations generated by simple linear regression analysis) the variability between cardiorespiratory parameters in the three OUES intensities, as well as a strong positive correlation between OUES_100% and OUES_75% (r = 0.95, P <0.01).

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Table 3. Pearson correlation coefficients showing the relationship between OUES and anthropometric variables and CPX parameters.

https://doi.org/10.1371/journal.pone.0172894.t003

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Fig 3. Simple linear regression equation and correlation coefficient showing the relationship between OUES (50%, 75%, 100%) and cardiorespiratory variables during CPX in morbidly obese women.

A, OUES_100%-OUES_75%. B, OUES/kg_50%,_75%,_100%-VO_2VAT. C, OUES_50%,_75%,100%-VO_2peak. D, OUES/kg_50%,75%,100%-VE/VO_2peak. OUES, oxygen uptake efficiency slope; VO_2VAT, oxygen consumption at ventilatory anaerobic threshold; VO_2peak, oxygen consumption at peak exercise; VE/VO_2peak, ventilatory equivalent ratio for oxygen at peak exercise.

https://doi.org/10.1371/journal.pone.0172894.g003

Discussion

This is the first study that has investigated the usefulness of OUES in evaluating maximal and submaximal physical effort in morbidly obese women. We tested OUES at 50%, 75% and in the complete test (100%), and its relationship among metabolic, ventilatory and anthropometric variables. The main finding shows that the OUES values did not significantly change independent of exercise intensity, showing strong correlation between OUES (maximal and submaximal) and VO_2peak. On the other hand, both VO_2peak as well as OUES_100% decreased, representing 75.5% of predicted values.

Although VO_2peak is considered the best standard to measure aerobic fitness for several health or clinical conditions, some limited patients such as those with heart failure, multiple sclerosis or being morbidly obese could have a limited VO_2peak from being in such poor physical condition, having impaired pulmonary function, skeletal muscle injuries or having a very heavy body. Due to these conditions, medical illnesses induce a low exercise capacity and VO_2peak cannot be accurately assessed. From the clinical exercise and sports medicine perspective, other submaximal exercise variables could be considered in morbidly obese patients; for example, using OUES as a functional reserve index. Similar to other clinical conditions [14,15,36], or even considering three different exercise intensities, we have shown a low influence of intensity on OUES outcome. When we extrapolate the analysis for the submaximal and maximal levels of OUES, we notice a strong positive correlation between VO2_peak and OUES in the complete test and for the 50% and 75% tests (Fig 3C). This fit occurs even when OUES was normalized for body weight and did not differ among the three exercise intensities. Also, there was only 2.7% variance between OUES_75% and OUES_100%. Furthermore, the Band-Altman plot showed good agreement between them with a difference of only 58.9 mL/min/log(L/min) for OUES and 0.49 mL/kg/min/log(L/min) for OUES/kg. Our results confirm the previous findings of Laethem et al. [14] who found a 3.0% difference using the same intensity of our OUES in heart failure. Initially, these findings were also reproducible in 429 healthy adult subjects [16]. Bongers et al. [18] found similar results (4.3%) for children with cystic fibrosis using the same OUES intensity as in our study. One of the important aspects to consider is that even though Bland–Altman analysis is designed to overcome some of the limitations of the correlation approach for the purpose of agreement assessment, we don’t know if 0.49 or 58.9 are acceptable clinical limits to attribute as being good agreement. Until now there has not been any data for morbidly obese patients.

Our study corroborates many previous studies [15,18,26] regarding the strong correlation between the maximal (r = 0.76) and submaximal OUES (r = 0.82) with VO_2peak. In obese children [26], OUES_100% and OUES_VAT were correlated with VO_2peak (L/min) as 0.91 and 0.71, respectively. For heart congenital disease [15], similar results of 0.89 were found for OUES maximal and 0.71 at 50%, also related to VO_2peak. In our data, both OUES (r = 0.77) and OUES/kg (r = 0.79) were also strongly correlated with VO_2VAT. From the physiological perspective, VAT is used as a submaximal estimate of aerobic potential; however, in severe obesity, this event seems to be difficult to reach. OUES is more easily detected than VTA, and unlike VO_2peak, it is less influenced by motivational patient factors which affects performance in CPX [14,21]. This is a point where OUES has a huge advantage because it is independent of exercise intensity and the patient's motivation, which allows for it to be used as a cardiorespiratory functional reserve index.

The maximal level of effort should be certified by RER ≥ 1.10 during CPX [37]. Our data for the mean effort at peak exercise was 1.03, and 75.8% did not reach this level. This differed from de DeJong et al. [4], where out of 76 morbidly obese (69.3% female), only 43.0% did not reach RER ≥ 1.10 at the end of CPX. Miller et al. [38] found that 33% of 64 morbidly obese (78.0% female) did not reach RER ≥ 1.10. Two possible reasons could explain these findings. First, data from men could raise the RER, since they tend to have more fitness than women [39]. Second, the type of protocol implemented was different from our ramp protocol, where those authors used the modified Bruce protocol which increments work every three minutes, allowing the respiratory, cardiac and musculoskeletal systems more time to adapt and avoids the early interruption of the test. However, more studies are needed to better assess this theory.

Several studies [14,21,26] in other populations have shown that OUES and OUES/kg are divergent from ours; this shows the importance of studying OUES in the obese population. For example, the women in our study had 21.3% less OUES than obese girls shown by Breithaupt et al. [26]. Two large studies involving prediction equations for OUES [23,24] showed that age is a factor that can negatively influence OUES values. However, as our sample did not have large variations in age, we could not observe a significant relationship between OUES and age. The obese subjects in our study had 22.2% more OUES than patients with cardiac sarcoidosis, as shown by Ammenwerth et al. [21]. Several aspects should be considered for assesssing OUES. Higher values of OUES depend on adequate heart rate, oxygen extraction and utilization by peripheral muscles, and later lactic acidosis [14,16]. It is known that ventilation of physiological dead space which depends on the structural integrity of lungs and adequate lung perfusion can influence the ventilatory response to exercise, and consequently the values of OUES [16]. A maximal effort by the heart, respiratory and musculoskeletal system is necessary. However, individuals in poor physical condition (such as morbidly obese) or patients who are affected by some chronic illness have a high probability to develop early lactic acidosis during exercise [32]. In this way they became unable to maintain the CPX at a maximal level, thus presenting reduced VO_2peak values, and consequently lower OUES than predicted.

As a second objective, we were able to establish a negative influence of OUES on BAI (r = -0.40) and OUES/kg on BAI (r = -0.50) and HC (r = -0.46). In other words, the higher the body fat/adiposity index and hip circumference, the lower the OUES of our sample, since it was an extremely obese population (BMI = 47.1) with high hip circumference values (HC = 140.7) and indirectly calculated fat percentage (BAI = 52.9%). As defined by Bergman et al. [29], BAI is an alternative measurement which is easy to apply and useful to quantify the percentage of body fat. It showed a positive correlation (0.85) with Dual-energy X-Ray Absorptiometry (DXA), being a gold standard for this assessment [29]. The vast amount of fat around the hips is believed to hinder the walking ability of obese and is associated with higher perception of effort, leading to early exhaustion [40,41]. This reduced exercise tolerance is reflected by low values of VO_2peak (mL/kg/min) during CPX, thereby affecting OUES.

Until now, little has been studied on the relationship between OUES and VE/VO₂. Only one study [42] in heart failure disease showed moderate correlation (r = -0.58) between these variables. Our findings demonstrate higher values to explain this relationship, where the VE/VO₂ correlated negatively with OUES and OUES/kg at -0.66 and -0.70, respectively. Different from heart failure, severe obesity causes significant inefficiency in respiratory and body mechanics caused by excess body fat around the thorax and abdomen, being responsible for increasing respiratory work and pulmonary ventilation [43,44]. In addition, a high demand of ventilation during exercise in obese individuals will reflect an increase in metabolic expenditure and inadequate ventilatory reserves [45,46]. Taken together, these alterations could justify the strong negative correlation between OUES and VE/VO₂, where it seems that OUES is a variable obtained by the inclination curve of VE and VO₂, and could be considered a marker of ventilatory efficiency.

The following limitations should be considered in our study. First, a relatively small and homogeneous sample makes it difficult to extrapolate these results to other obesity profiles, but the inclusion of only morbidly obese women removes bias. If we had included men, the sample could be contaminated due to their greater aerobic capacity, and we chose obese women with high BMI because it is generally not possible to evaluate their maximum effort. Another strong aspect of our data is that we included sedentary women with healthy pulmonary function and reasonable ventilatory endurance, which ensured that respiratory function was minimally preserved during CPX. We also recognize that we did not evaluate the reproducibility of OUES. However, OUES has previously seemed to be well reproducible in pediatric populations [12] and healthy adults [47,48]. Finally, given the huge lack of studies with OUES in the morbidly obese, our primary intention was to improve the physiological understanding and typical profile of OUES, and because of this we did not include a control group.

Conclusions

Taking into account the results and limitations of our study, we conclude that OUES is a favorable parameter that can be applied to morbidly obese women without difference between maximal (OUES_100%) and submaximal (OUES_50%, OUES_75%) levels, showing a strong positive correlation with measures of physical functioning (VO_2peak and VO_2VAT). We suggest that OUES is a useful index of cardiorespiratory fitness and could be used as an alternative for aerobic capacity by providing an objective measure of cardiopulmonary function, mainly in evaluating individuals with limitations or incapacity to perform maximal physical effort during CPX, such as in the case of morbidly obese women. However, this does not take away the need for complete CPX when there are other mandatory clinical reasons or to prescribe exercise.

Supporting information

S1 File. Minimal data.

https://doi.org/10.1371/journal.pone.0172894.s001

(XLSX)

Author Contributions

Conceptualization: TO NO RC SB.
Data curation: TO NO RC SB.
Formal analysis: TO NO RC RC.
Investigation: TO NO RC RCC AF ES SB.
Methodology: TO SB.
Project administration: SB.
Resources: TO SB ES.
Software: TO NO RC RCC.
Supervision: SB.
Validation: SB TO.
Visualization: TO SB NO.
Writing – original draft: TO SB.
Writing – review & editing: NO RC RCC AF.

References

1. Lorenzo S, Babb TG. Ventilatory responses at peak exercise in endurance-trained obese adults. Chest. 2013;144:1330–9. pmid:23722607
- View Article
- PubMed/NCBI
- Google Scholar
2. Evans RA, Dolmage TE, Robles PG, Goldstein RS, Brooks D. Do field walking tests produce similar cardiopulmonary demands to an incremental treadmill test in obese individuals with treated OSA? Chest. 2014;146:81–7. pmid:24577643
- View Article
- PubMed/NCBI
- Google Scholar
3. Oliver N, Onofre T, Carlos R, Barbosa J, Godoy E, Pereira E, et al. Ventilatory and Metabolic Response in the Incremental Shuttle and 6-Min Walking Tests Measured by Telemetry in Obese Patients Prior to Bariatric Surgery. Obes Surg. 2015;25:1658–65. pmid:25573458
- View Article
- PubMed/NCBI
- Google Scholar
4. deJong AT, Gallagher MJ, Sandberg KR, Lillystone MA, Spring T, Franklin BA, et al. Peak oxygen consumption and the minute ventilation/carbon dioxide production relation slope in morbidly obese men and women: influence of subject effort and body mass index. Prev Cardiol. 2008 Spring;11:100–5. pmid:18401238
- View Article
- PubMed/NCBI
- Google Scholar
5. Arena R, Cahalin LP. Evaluation of Cardiorespiratory Fitness and Respiratory Muscle Function in the Obese Population. Int J Cardiol. 2014;56:457–64.
- View Article
- Google Scholar
6. Hulens M, Vansant G, Lysens R, Claessens AL, Muls E. Exercise capacity in lean versus obese women. Scand J Med Sci Sports. 2001;11:305–9. pmid:11696216
- View Article
- PubMed/NCBI
- Google Scholar
7. Di Thommazo-Luporini L, Jurgensen SP, Castello-Simoes V, Catai AM, Arena R, Borghi-Silva A. Metabolic and clinical comparative analysis of treadmill six-minute walking test and cardiopulmonary exercise testing in obese and eutrophic women. Rev Bras Fisioter. 2012;16:469–78. pmid:22832701
- View Article
- PubMed/NCBI
- Google Scholar
8. He J, Watkins S, Kelley DE. Skeletal muscle lipid content and oxidative enzyme activity in relation to muscle fiber type in type 2 diabetes and obesity. Diabetes. 2001;50:817–23. pmid:11289047
- View Article
- PubMed/NCBI
- Google Scholar
9. Kelley DE. Skeletal muscle fat oxidation: timing and flexibility are everything. J Clin Invest. 2005;115:1699–702. pmid:16007246
- View Article
- PubMed/NCBI
- Google Scholar
10. Correia de Faria Santarém G, de Cleva R, Santo MA, Bernhard AB, Gadducci AV, Greve JM, et al. Correlation between Body Composition and Walking Capacity in Severe Obesity. PLoS One. 2015;10(6):e0130268. pmid:26098769
- View Article
- PubMed/NCBI
- Google Scholar
11. Runhaar J, Koes BW, Clockaerts S, Bierma-Zeinstra SM. A systematic review on changed biomechanics of lower extremities in obese individuals: a possible role in development of osteoarthritis. Obes Rev. 2011;12:1071–82. pmid:21812903
- View Article
- PubMed/NCBI
- Google Scholar
12. Baba R, Nagashima M, Goto M, Nagano Y, Yokota M, Tauchi N, et al. Oxygen uptake efficiency slope: a new index of cardiorespiratory functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. J Am Coll Cardiol. 1996;28:1567–72. pmid:8917273
- View Article
- PubMed/NCBI
- Google Scholar
13. Baba R, Tsuyuki K, Kimura Y, Ninomiya K, Aihara M, Ebine K, et al. Oxygen uptake efficiency slope as a useful measure of cardiorespiratory functional reserve in adult cardiac patients. Eur J Appl Physiol Occup Physiol. 1999;80:397–401. pmid:10502072
- View Article
- PubMed/NCBI
- Google Scholar
14. Van Laethem C, Bartunek J, Goethals M, Nellens P, Andries E, Vanderheyden M. Oxygen uptake efficiency slope, a new submaximal parameter in evaluating exercise capacity in chronic heart failure patients. Am Heart J. 2005;149:175–80. pmid:15660050
- View Article
- PubMed/NCBI
- Google Scholar
15. Giardini A, Specchia S, Gargiulo G, Sangiorgi D, Picchio FM. Accuracy of oxygen uptake efficiency slope in adults with congenital heart disease. Int J Cardiol. 2009;133:74–9. pmid:18242739
- View Article
- PubMed/NCBI
- Google Scholar
16. Hollenberg M, Tager IB. Oxygen uptake efficiency slope: an index of exercise performance and cardiopulmonary reserve requiring only submaximal exercise. J Am Coll Cardiol. 2000;36:194–201. pmid:10898434
- View Article
- PubMed/NCBI
- Google Scholar
17. Arena R, Arrowood JA, Fei DY, Helm S, Kraft KA. Maximal aerobic capacity and the oxygen uptake efficiency slope as predictors of large artery stiffness in apparently healthy subjects. J Cardiopulm Rehabil Prev. 2009;29:248–54. pmid:19451829
- View Article
- PubMed/NCBI
- Google Scholar
18. Bongers BC, Hulzebos EH, Arets BG, Takken T. Validity of the oxygen uptake efficiency slope in children with cystic fibrosis and mild-to-moderate airflow obstruction. Pediatr Exerc Sci. 2012;24:129–41. pmid:22433258
- View Article
- PubMed/NCBI
- Google Scholar
19. Antoine-Jonville S, Pichon A, Vazir A, Polkey MI, Dayer MJ. Oxygen uptake efficiency slope, aerobic fitness, and V(E)-VCO2 slope in heart failure. Med Sci Sports Exerc. 2012;44:428–34. pmid:21808213
- View Article
- PubMed/NCBI
- Google Scholar
20. Ramos RP, Ota-Arakaki JS, Alencar MC, Ferreira EV, Nery LE, Neder JA. Exercise oxygen uptake efficiency slope independently predicts poor outcome in pulmonary arterial hypertension. Eur Respir J. 2014;43:1510–2. pmid:24311768
- View Article
- PubMed/NCBI
- Google Scholar
21. Ammenwerth W, Wurps H, Klemens MA, Crolow C, Schulz-Menger J, Schönfeld N, et al. Reduced oxygen uptake efficiency slope in patients with cardiac sarcoidosis. PLoS One. 2014;9:e102333. pmid:25029031
- View Article
- PubMed/NCBI
- Google Scholar
22. Barron A, Francis DP, Mayet J, Ewert R, Obst A, Mason M, et al. Oxygen Uptake Efficiency Slope and Breathing Reserve, Not Anaerobic Threshold, Discriminate Between Patients With Cardiovascular Disease Over Chronic Obstructive Pulmonary Disease. JACC Heart Fail. 2016;4:252–61. pmid:26874378
- View Article
- PubMed/NCBI
- Google Scholar
23. Sun XG, Hansen JE, Stringer WW. Oxygen uptake efficiency plateau: physiology and reference values. Eur J Appl Physiol. 2012;112:919–28. pmid:21695524
- View Article
- PubMed/NCBI
- Google Scholar
24. Buys R, Coeckelberghs E, Vanhees L, Cornelissen VA. The oxygen uptake efficiency slope in 1411 Caucasian healthy men and women aged 20–60 years: reference values. Eur J Prev Cardiol. 2015;22:356–63. pmid:25147346
- View Article
- PubMed/NCBI
- Google Scholar
25. Marinov B, Kostianev S. Exercise performance and oxygen uptake efficiency slope in obese children performing standardized exercise. Acta Physiol Pharmacol Bulg. 2003;27:59–64. pmid:14570149
- View Article
- PubMed/NCBI
- Google Scholar
26. Breithaupt PG, Colley RC, Adamo KB. Using the oxygen uptake efficiency slope as an indicator of cardiorespiratory fitness in the obese pediatric population. Pediatr Exerc Sci. 2012;24:357–68. pmid:22971553
- View Article
- PubMed/NCBI
- Google Scholar
27. Arena R, Brubaker P, Moore B, Kitzman D. The oxygen uptake efficiency slope is reduced in older patients with heart failure and a normal ejection fraction. Int J Cardiol. 2010;144:101–2. pmid:19174312
- View Article
- PubMed/NCBI
- Google Scholar
28. Bergman RN, Stefanovski D, Buchanan DA, Sumner AE, Reynolds JC, Sebring NG, et al. A Better Index of Body Adiposity. Obesity. 2011;19:1083–9. pmid:21372804
- View Article
- PubMed/NCBI
- Google Scholar
29. Pereira CAC, Sato T, Rodrigues SC. New reference values for forced spirometry in white adults in Brazil. J Bras Pneumol. 2007;33:397–406. pmid:17982531
- View Article
- PubMed/NCBI
- Google Scholar
30. Laszlo G. Standardisation of lung function testing: helpful guidance from the ATS/ERS Task Force. Thorax. 2006;61:744–6. pmid:16936234
- View Article
- PubMed/NCBI
- Google Scholar
31. Barbosa e Silva O, Sobral DC. Uma nova Proposta para Orientar a Velocidade e Inclinação no Protocolo em Rampa na Esteira Ergométrica. Ar Bras Cardio. 2003;81:42–7.
- View Article
- Google Scholar
32. Wasserman K, Beaver WL, Whipp BJ. Gas exchange theory and the lactic acidosis (anaerobic) treshold. Circulation. 1990;81:II14–30. pmid:2403868
- View Article
- PubMed/NCBI
- Google Scholar
33. ATS/ACCP Statement on cardiopulmonary exercise testing. Am J Respir Crit Care Med. 2003;167:211–77. pmid:12524257
- View Article
- PubMed/NCBI
- Google Scholar
34. Wasserman K, Hansen JE, Dy Sue, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2005.
35. Buys R, Coeckelberghs E, Vanhees L, Cornelissen VA. Oxygen uptake efficiency slope in 1411 Caucasian healthy men and women aged 20–60 years: reference values. Eur J Prev Cardiol. 2015;22:356–63. pmid:25147346
- View Article
- PubMed/NCBI
- Google Scholar
36. Heine M, Verschuren O, Kwakkel G. Validity of Oxygen Uptake Efficiency Slope in patients with multiple sclerosis. J Rehabil Med. 2014;46:656–61. pmid:24850225
- View Article
- PubMed/NCBI
- Google Scholar
37. Balady GJ, Arena R, Sietsema K, Myers J, Coke L, Fletcher GF, et al. Clinician's Guide to Cardiopulmonary Exercise Testing in Adults: A Scientific Statement. Circulation. 2010;122:191–225. pmid:20585013
- View Article
- PubMed/NCBI
- Google Scholar
38. Miller WM, Spring TJ, Zalesin KC, Kaeding KR, Nori Janosz KE, McCullough PA, et al. Lower than predicted resting metabolic rate is associated with severely impaired cardiorespiratory fitness in obese individuals. Obesity (Silver Spring). 2012;20:505–11.
- View Article
- Google Scholar
39. Herdy AH, Caixeta A. Brazilian Cardiorespiratory Fitness Classification Based on Maximum Oxygen Consumption. Arq Bras Cardiol. 2016;106:389–95. pmid:27305285
- View Article
- PubMed/NCBI
- Google Scholar
40. de Souza SA, Faintuch J, Valezi AC, Sant'Anna AF, Gama-Rodrigues JJ, de Batista Fonseca IC, et al. Gait cinematic analysis in morbidly obese patients. Obes Surg. 2005;15:1238–42. pmid:16259878
- View Article
- PubMed/NCBI
- Google Scholar
41. King WC, Engel SG, Elder KA, Chapman WH, Eid GM, Wolfe BM, et al. Walking capacity of bariatric surgery candidates. Surg Obes Relat Dis. 2012;8:48–59. pmid:21937285
- View Article
- PubMed/NCBI
- Google Scholar
42. Arena R, Guazzi M, Myers J, Chase P, Bensimhon D, Cahalin LP, et al. The relationship between minute ventilation and oxygen consumption in heart failure: comparing peak VE/VO₂ and the oxygen uptake efficiency slope. Int J Cardiol. 2012;154:384–5. pmid:22188985
- View Article
- PubMed/NCBI
- Google Scholar
43. Babb TG, Wyrick BL, DeLorey DS, Chase PJ, Feng MY. Fat distribution and end-expiratory lung volume in lean and obese men and women. Chest. 2008;134:704–11. pmid:18641101
- View Article
- PubMed/NCBI
- Google Scholar
44. O'Donnell DE, O'Donnell CD, Webb KA, Guenette JA. Respiratory Consequences of Mild-to-Moderate Obesity: Impact on Exercise Performance in Health and in Chronic Obstructive Pulmonary Disease. Pulm Med. 2012;2012:818925. pmid:23097698
- View Article
- PubMed/NCBI
- Google Scholar
45. Kress JP, Pohlman AS, Alverdy J, Hall JB. The impact of morbid obesity on oxygen cost of breathing (VO(2RESP)) at rest. Am J Respir Crit Care Med. 1999;160:883–6. pmid:10471613
- View Article
- PubMed/NCBI
- Google Scholar
46. Ofir D, Laveneziana P, Webb KA, O'Donnell DE. Ventilatory and perceptual responses to cycle exercise in obese women. J Appl Physiol (1985). 2007;102:2217–26.
- View Article
- Google Scholar
47. Baba R, Kubo N, Morotome Y, Iwagaki S. Reproducibility of the oxygen uptake efficiency slope in normal healthy subjects. J Sports Med Phys Fitness. 1999;39:202–6. pmid:10573661
- View Article
- PubMed/NCBI
- Google Scholar
48. Van Laethem C, De Sutter J, Peersman W, Calders P. Intratest reliability and test–retest reproducibility of the oxygen uptake efficiency slope in healthy participants. Eur J Cardiovasc Prev Rehabil. 2009;16:493–8. pmid:19483619
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. Lorenzo S, Babb TG. Ventilatory responses at peak exercise in endurance-trained obese adults. Chest. 2013;144:1330–9. pmid:23722607
View Article
PubMed/NCBI
Google Scholar

[2] View Article

[3] PubMed/NCBI

[4] Google Scholar

[ref2] 2. Evans RA, Dolmage TE, Robles PG, Goldstein RS, Brooks D. Do field walking tests produce similar cardiopulmonary demands to an incremental treadmill test in obese individuals with treated OSA? Chest. 2014;146:81–7. pmid:24577643
View Article
PubMed/NCBI
Google Scholar

[6] View Article

[7] PubMed/NCBI

[8] Google Scholar

[ref3] 3. Oliver N, Onofre T, Carlos R, Barbosa J, Godoy E, Pereira E, et al. Ventilatory and Metabolic Response in the Incremental Shuttle and 6-Min Walking Tests Measured by Telemetry in Obese Patients Prior to Bariatric Surgery. Obes Surg. 2015;25:1658–65. pmid:25573458
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref4] 4. deJong AT, Gallagher MJ, Sandberg KR, Lillystone MA, Spring T, Franklin BA, et al. Peak oxygen consumption and the minute ventilation/carbon dioxide production relation slope in morbidly obese men and women: influence of subject effort and body mass index. Prev Cardiol. 2008 Spring;11:100–5. pmid:18401238
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref5] 5. Arena R, Cahalin LP. Evaluation of Cardiorespiratory Fitness and Respiratory Muscle Function in the Obese Population. Int J Cardiol. 2014;56:457–64.
View Article
Google Scholar

[18] View Article

[19] Google Scholar

[ref6] 6. Hulens M, Vansant G, Lysens R, Claessens AL, Muls E. Exercise capacity in lean versus obese women. Scand J Med Sci Sports. 2001;11:305–9. pmid:11696216
View Article
PubMed/NCBI
Google Scholar

[21] View Article

[22] PubMed/NCBI

[23] Google Scholar

[ref7] 7. Di Thommazo-Luporini L, Jurgensen SP, Castello-Simoes V, Catai AM, Arena R, Borghi-Silva A. Metabolic and clinical comparative analysis of treadmill six-minute walking test and cardiopulmonary exercise testing in obese and eutrophic women. Rev Bras Fisioter. 2012;16:469–78. pmid:22832701
View Article
PubMed/NCBI
Google Scholar

[25] View Article

[26] PubMed/NCBI

[27] Google Scholar

[ref8] 8. He J, Watkins S, Kelley DE. Skeletal muscle lipid content and oxidative enzyme activity in relation to muscle fiber type in type 2 diabetes and obesity. Diabetes. 2001;50:817–23. pmid:11289047
View Article
PubMed/NCBI
Google Scholar

[29] View Article

[30] PubMed/NCBI

[31] Google Scholar

[ref9] 9. Kelley DE. Skeletal muscle fat oxidation: timing and flexibility are everything. J Clin Invest. 2005;115:1699–702. pmid:16007246
View Article
PubMed/NCBI
Google Scholar

[33] View Article

[34] PubMed/NCBI

[35] Google Scholar

[ref10] 10. Correia de Faria Santarém G, de Cleva R, Santo MA, Bernhard AB, Gadducci AV, Greve JM, et al. Correlation between Body Composition and Walking Capacity in Severe Obesity. PLoS One. 2015;10(6):e0130268. pmid:26098769
View Article
PubMed/NCBI
Google Scholar

[37] View Article

[38] PubMed/NCBI

[39] Google Scholar

[ref11] 11. Runhaar J, Koes BW, Clockaerts S, Bierma-Zeinstra SM. A systematic review on changed biomechanics of lower extremities in obese individuals: a possible role in development of osteoarthritis. Obes Rev. 2011;12:1071–82. pmid:21812903
View Article
PubMed/NCBI
Google Scholar

[41] View Article

[42] PubMed/NCBI

[43] Google Scholar

[ref12] 12. Baba R, Nagashima M, Goto M, Nagano Y, Yokota M, Tauchi N, et al. Oxygen uptake efficiency slope: a new index of cardiorespiratory functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. J Am Coll Cardiol. 1996;28:1567–72. pmid:8917273
View Article
PubMed/NCBI
Google Scholar

[45] View Article

[46] PubMed/NCBI

[47] Google Scholar

[ref13] 13. Baba R, Tsuyuki K, Kimura Y, Ninomiya K, Aihara M, Ebine K, et al. Oxygen uptake efficiency slope as a useful measure of cardiorespiratory functional reserve in adult cardiac patients. Eur J Appl Physiol Occup Physiol. 1999;80:397–401. pmid:10502072
View Article
PubMed/NCBI
Google Scholar

[49] View Article

[50] PubMed/NCBI

[51] Google Scholar

[ref14] 14. Van Laethem C, Bartunek J, Goethals M, Nellens P, Andries E, Vanderheyden M. Oxygen uptake efficiency slope, a new submaximal parameter in evaluating exercise capacity in chronic heart failure patients. Am Heart J. 2005;149:175–80. pmid:15660050
View Article
PubMed/NCBI
Google Scholar

[53] View Article

[54] PubMed/NCBI

[55] Google Scholar

[ref15] 15. Giardini A, Specchia S, Gargiulo G, Sangiorgi D, Picchio FM. Accuracy of oxygen uptake efficiency slope in adults with congenital heart disease. Int J Cardiol. 2009;133:74–9. pmid:18242739
View Article
PubMed/NCBI
Google Scholar

[57] View Article

[58] PubMed/NCBI

[59] Google Scholar

[ref16] 16. Hollenberg M, Tager IB. Oxygen uptake efficiency slope: an index of exercise performance and cardiopulmonary reserve requiring only submaximal exercise. J Am Coll Cardiol. 2000;36:194–201. pmid:10898434
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref17] 17. Arena R, Arrowood JA, Fei DY, Helm S, Kraft KA. Maximal aerobic capacity and the oxygen uptake efficiency slope as predictors of large artery stiffness in apparently healthy subjects. J Cardiopulm Rehabil Prev. 2009;29:248–54. pmid:19451829
View Article
PubMed/NCBI
Google Scholar

[65] View Article

[66] PubMed/NCBI

[67] Google Scholar

[ref18] 18. Bongers BC, Hulzebos EH, Arets BG, Takken T. Validity of the oxygen uptake efficiency slope in children with cystic fibrosis and mild-to-moderate airflow obstruction. Pediatr Exerc Sci. 2012;24:129–41. pmid:22433258
View Article
PubMed/NCBI
Google Scholar

[69] View Article

[70] PubMed/NCBI

[71] Google Scholar

[ref19] 19. Antoine-Jonville S, Pichon A, Vazir A, Polkey MI, Dayer MJ. Oxygen uptake efficiency slope, aerobic fitness, and V(E)-VCO2 slope in heart failure. Med Sci Sports Exerc. 2012;44:428–34. pmid:21808213
View Article
PubMed/NCBI
Google Scholar

[73] View Article

[74] PubMed/NCBI

[75] Google Scholar

[ref20] 20. Ramos RP, Ota-Arakaki JS, Alencar MC, Ferreira EV, Nery LE, Neder JA. Exercise oxygen uptake efficiency slope independently predicts poor outcome in pulmonary arterial hypertension. Eur Respir J. 2014;43:1510–2. pmid:24311768
View Article
PubMed/NCBI
Google Scholar

[77] View Article

[78] PubMed/NCBI

[79] Google Scholar

[ref21] 21. Ammenwerth W, Wurps H, Klemens MA, Crolow C, Schulz-Menger J, Schönfeld N, et al. Reduced oxygen uptake efficiency slope in patients with cardiac sarcoidosis. PLoS One. 2014;9:e102333. pmid:25029031
View Article
PubMed/NCBI
Google Scholar

[81] View Article

[82] PubMed/NCBI

[83] Google Scholar

[ref22] 22. Barron A, Francis DP, Mayet J, Ewert R, Obst A, Mason M, et al. Oxygen Uptake Efficiency Slope and Breathing Reserve, Not Anaerobic Threshold, Discriminate Between Patients With Cardiovascular Disease Over Chronic Obstructive Pulmonary Disease. JACC Heart Fail. 2016;4:252–61. pmid:26874378
View Article
PubMed/NCBI
Google Scholar

[85] View Article

[86] PubMed/NCBI

[87] Google Scholar

[ref23] 23. Sun XG, Hansen JE, Stringer WW. Oxygen uptake efficiency plateau: physiology and reference values. Eur J Appl Physiol. 2012;112:919–28. pmid:21695524
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref24] 24. Buys R, Coeckelberghs E, Vanhees L, Cornelissen VA. The oxygen uptake efficiency slope in 1411 Caucasian healthy men and women aged 20–60 years: reference values. Eur J Prev Cardiol. 2015;22:356–63. pmid:25147346
View Article
PubMed/NCBI
Google Scholar

[93] View Article

[94] PubMed/NCBI

[95] Google Scholar

[ref25] 25. Marinov B, Kostianev S. Exercise performance and oxygen uptake efficiency slope in obese children performing standardized exercise. Acta Physiol Pharmacol Bulg. 2003;27:59–64. pmid:14570149
View Article
PubMed/NCBI
Google Scholar

[97] View Article

[98] PubMed/NCBI

[99] Google Scholar

[ref26] 26. Breithaupt PG, Colley RC, Adamo KB. Using the oxygen uptake efficiency slope as an indicator of cardiorespiratory fitness in the obese pediatric population. Pediatr Exerc Sci. 2012;24:357–68. pmid:22971553
View Article
PubMed/NCBI
Google Scholar

[101] View Article

[102] PubMed/NCBI

[103] Google Scholar

[ref27] 27. Arena R, Brubaker P, Moore B, Kitzman D. The oxygen uptake efficiency slope is reduced in older patients with heart failure and a normal ejection fraction. Int J Cardiol. 2010;144:101–2. pmid:19174312
View Article
PubMed/NCBI
Google Scholar

[105] View Article

[106] PubMed/NCBI

[107] Google Scholar

[ref28] 28. Bergman RN, Stefanovski D, Buchanan DA, Sumner AE, Reynolds JC, Sebring NG, et al. A Better Index of Body Adiposity. Obesity. 2011;19:1083–9. pmid:21372804
View Article
PubMed/NCBI
Google Scholar

[109] View Article

[110] PubMed/NCBI

[111] Google Scholar

[ref29] 29. Pereira CAC, Sato T, Rodrigues SC. New reference values for forced spirometry in white adults in Brazil. J Bras Pneumol. 2007;33:397–406. pmid:17982531
View Article
PubMed/NCBI
Google Scholar

[113] View Article

[114] PubMed/NCBI

[115] Google Scholar

[ref30] 30. Laszlo G. Standardisation of lung function testing: helpful guidance from the ATS/ERS Task Force. Thorax. 2006;61:744–6. pmid:16936234
View Article
PubMed/NCBI
Google Scholar

[117] View Article

[118] PubMed/NCBI

[119] Google Scholar

[ref31] 31. Barbosa e Silva O, Sobral DC. Uma nova Proposta para Orientar a Velocidade e Inclinação no Protocolo em Rampa na Esteira Ergométrica. Ar Bras Cardio. 2003;81:42–7.
View Article
Google Scholar

[121] View Article

[122] Google Scholar

[ref32] 32. Wasserman K, Beaver WL, Whipp BJ. Gas exchange theory and the lactic acidosis (anaerobic) treshold. Circulation. 1990;81:II14–30. pmid:2403868
View Article
PubMed/NCBI
Google Scholar

[124] View Article

[125] PubMed/NCBI

[126] Google Scholar

[ref33] 33. ATS/ACCP Statement on cardiopulmonary exercise testing. Am J Respir Crit Care Med. 2003;167:211–77. pmid:12524257
View Article
PubMed/NCBI
Google Scholar

[128] View Article

[129] PubMed/NCBI

[130] Google Scholar

[ref34] 34. Wasserman K, Hansen JE, Dy Sue, Stringer WW, Whipp BJ. Principles of exercise testing and interpretation. 4th ed. Philadelphia: Lippincott Williams & Wilkins; 2005.

[ref35] 35. Buys R, Coeckelberghs E, Vanhees L, Cornelissen VA. Oxygen uptake efficiency slope in 1411 Caucasian healthy men and women aged 20–60 years: reference values. Eur J Prev Cardiol. 2015;22:356–63. pmid:25147346
View Article
PubMed/NCBI
Google Scholar

[133] View Article

[134] PubMed/NCBI

[135] Google Scholar

[ref36] 36. Heine M, Verschuren O, Kwakkel G. Validity of Oxygen Uptake Efficiency Slope in patients with multiple sclerosis. J Rehabil Med. 2014;46:656–61. pmid:24850225
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref37] 37. Balady GJ, Arena R, Sietsema K, Myers J, Coke L, Fletcher GF, et al. Clinician's Guide to Cardiopulmonary Exercise Testing in Adults: A Scientific Statement. Circulation. 2010;122:191–225. pmid:20585013
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref38] 38. Miller WM, Spring TJ, Zalesin KC, Kaeding KR, Nori Janosz KE, McCullough PA, et al. Lower than predicted resting metabolic rate is associated with severely impaired cardiorespiratory fitness in obese individuals. Obesity (Silver Spring). 2012;20:505–11.
View Article
Google Scholar

[145] View Article

[146] Google Scholar

[ref39] 39. Herdy AH, Caixeta A. Brazilian Cardiorespiratory Fitness Classification Based on Maximum Oxygen Consumption. Arq Bras Cardiol. 2016;106:389–95. pmid:27305285
View Article
PubMed/NCBI
Google Scholar

[148] View Article

[149] PubMed/NCBI

[150] Google Scholar

[ref40] 40. de Souza SA, Faintuch J, Valezi AC, Sant'Anna AF, Gama-Rodrigues JJ, de Batista Fonseca IC, et al. Gait cinematic analysis in morbidly obese patients. Obes Surg. 2005;15:1238–42. pmid:16259878
View Article
PubMed/NCBI
Google Scholar

[152] View Article

[153] PubMed/NCBI

[154] Google Scholar

[ref41] 41. King WC, Engel SG, Elder KA, Chapman WH, Eid GM, Wolfe BM, et al. Walking capacity of bariatric surgery candidates. Surg Obes Relat Dis. 2012;8:48–59. pmid:21937285
View Article
PubMed/NCBI
Google Scholar

[156] View Article

[157] PubMed/NCBI

[158] Google Scholar

[ref42] 42. Arena R, Guazzi M, Myers J, Chase P, Bensimhon D, Cahalin LP, et al. The relationship between minute ventilation and oxygen consumption in heart failure: comparing peak VE/VO₂ and the oxygen uptake efficiency slope. Int J Cardiol. 2012;154:384–5. pmid:22188985
View Article
PubMed/NCBI
Google Scholar

[160] View Article

[161] PubMed/NCBI

[162] Google Scholar

[ref43] 43. Babb TG, Wyrick BL, DeLorey DS, Chase PJ, Feng MY. Fat distribution and end-expiratory lung volume in lean and obese men and women. Chest. 2008;134:704–11. pmid:18641101
View Article
PubMed/NCBI
Google Scholar

[164] View Article

[165] PubMed/NCBI

[166] Google Scholar

[ref44] 44. O'Donnell DE, O'Donnell CD, Webb KA, Guenette JA. Respiratory Consequences of Mild-to-Moderate Obesity: Impact on Exercise Performance in Health and in Chronic Obstructive Pulmonary Disease. Pulm Med. 2012;2012:818925. pmid:23097698
View Article
PubMed/NCBI
Google Scholar

[168] View Article

[169] PubMed/NCBI

[170] Google Scholar

[ref45] 45. Kress JP, Pohlman AS, Alverdy J, Hall JB. The impact of morbid obesity on oxygen cost of breathing (VO(2RESP)) at rest. Am J Respir Crit Care Med. 1999;160:883–6. pmid:10471613
View Article
PubMed/NCBI
Google Scholar

[172] View Article

[173] PubMed/NCBI

[174] Google Scholar

[ref46] 46. Ofir D, Laveneziana P, Webb KA, O'Donnell DE. Ventilatory and perceptual responses to cycle exercise in obese women. J Appl Physiol (1985). 2007;102:2217–26.
View Article
Google Scholar

[176] View Article

[177] Google Scholar

[ref47] 47. Baba R, Kubo N, Morotome Y, Iwagaki S. Reproducibility of the oxygen uptake efficiency slope in normal healthy subjects. J Sports Med Phys Fitness. 1999;39:202–6. pmid:10573661
View Article
PubMed/NCBI
Google Scholar

[179] View Article

[180] PubMed/NCBI

[181] Google Scholar

[ref48] 48. Van Laethem C, De Sutter J, Peersman W, Calders P. Intratest reliability and test–retest reproducibility of the oxygen uptake efficiency slope in healthy participants. Eur J Cardiovasc Prev Rehabil. 2009;16:493–8. pmid:19483619
View Article
PubMed/NCBI
Google Scholar

[183] View Article

[184] PubMed/NCBI

[185] Google Scholar

Figures

Abstract

Introduction

Materials and methods

Subjects and procedures

Outcome measures

Statistical analysis

Results

Discussion

Conclusions

Supporting information

S1 File. Minimal data.

Author Contributions

References