Introduction
Automated metabolic systems are considered the gold standard for the assessment of aerobic capacity [1,2]. Historically, these systems have been designed to satisfy researchers’ needs to conduct cardiopulmonary exercise testing (CPET) in laboratory and in real-life conditions using stationary and portable systems [2–5]. Although appropriate for research applications, these machines can be complex and expensive for application in the fitness and performance industry [2,6]. Over the last 20 years, mobile devices have shown to be a valid alternative to stationary systems as their compact design, user-friendly characteristics, and more affordable price allow individuals with less skills and smaller budgets to conduct CPET in different environments [7–9].
The Q-NRG Max® (COSMED, Rome, Italy) is a mobile metabolic system that features a micro-dynamic mixing chamber technology, an oxygen (O2) and carbon dioxide (CO2) analyzer, a rapid calibration process, and an intuitive touchscreen interface. The Q-NRG Max conducts an automatic calibration before each measurement, offers portability due to its compact dimensions (12.2x8.3x10.6 in) and weight (10.3 lb), operates on either battery power or mains electricity, features an integrated 10“LCD touch screen, utilizes a simplified user interface to reduce the need for advanced technical skills, and integrates with ergometers and ANT+ devices to efficiently and accurately conduct CPET while enabling operators to support athletes and fitness enthusiasts. The seamless integration of these characteristics makes this machine the first system of its kind which is priced at less than half the cost of conventional metabolic carts. However, to our knowledge it’s accuracy and repeatability haven’t been validated yet. It is common practice to validate new metabolic systems against a metabolic simulator as they can effectively reproduce a wide variety of metabolic rates in a short time avoiding some of the drawbacks of the gold standard Douglas Bag method [10–13]. Although findings of research studies using metabolic simulators may not translate to real-world scenarios, they are necessary to assess measurement accuracy (technical validity) of an instrument. This is crucial to ensures that the instrument accurately measures what it is intended to measure guaranteeing that the results obtained from the instrument truly reflect the concept being studied rather than extraneous factors. The majority of validation studies have tested different metabolic systems against a range of metabolic rates with VO2 values from 0.5 to 4 L/min [11,14–16]. However, trained individuals and professional athletes can achieve maximal oxygen consumption (VO2max) up to 6 L/min [17,18]. Due to the potential application of mobile systems in sport and high-performance testing, a technical validation against a wide range of metabolic rates up to super-athletic VO2 is necessary [19–21]. This study aims at investigating the accuracy and of the Q-NRG Max® while measuring metabolic rates from 0.9 to 6 L/min of VO2.
Materials and methods
COSMED Q-NRG Max®
One Q-NRG Max® (COSMED srl, Italy) was used in this study. The system is equipped with a dynamic micro-mixing chamber, a galvanic O2 fuel cell, a non-dispersive infrared digital CO2 sensor, and an optoelectronic reader with high-performance T3 turbine flowmeter. Prior to each test and following a 30-min equipment warm-up, flowmeter and gas calibrations were performed. The flowmeter calibration was performed using the 3-L VacuMed syringe with a stroke rate of 20–25 stroke per minute. A gas calibration was performed using room air and a high precision reference gas mixture cylinder (16.00% O2, 5.00% CO2, balance N2) followed by a quality control check sampling 16.00% O2 and 5.00% CO2 from the cylinder and 20.93% O2 and 0.04% CO2 from the air. All measured values during the quality control were within ±0.03% of reference values. Before each test, the Q-NRG Max® performed an automatic calibration using room air following the machine’s standard procedures.
VacuMed metabolic simulator
A commercially available metabolic simulator (Model 17057; VacuMed, Ventura, CA) was used to simulate VO2, VCO2 and VE [12]. This system was upgraded, calibrated and certified (accuracy of ± 1.00% for simulated VO2 and VCO2 and ±0.5% for simulated stroke volume) by the manufacturer three months prior to this study. The upgrade allowed the motor-drive syringe pump to deliver stroke volumes from 1 to 5 L, in steps of 0.5 L maintaining the manufacturer’s stroke rates of 6 to 80 strokes.min−1. The digital mass flow control enables titration of a reference gas cylinder (21.00% CO2, 79.00% nitrogen) mixture and its consequent mixing with room air [12]. The VO2 and VCO2 are expressed in STPD, while the simulator system utilizes known mixtures of a dry tank gas and partially humidified room air. Therefore, the VacuMed software automatically corrects simulated volumes, accounting for temperature, barometric pressure, and humidity measured in room air.
Study design
The flowmeter and sampling line of the Q-NRG Max® were connected directly to the outlet of the VacuMed metabolic simulator (Fig 1). The Q-NRG Max® uses a patented measurement technology for O2 and CO2 measurement already adopted in other COSMED portable metabolic carts. Data was provided by the machine every 30 seconds and controlled in real time on the Q-NRG Max® screen during testing. Accuracy and repeatability of the Q-NRG Max® were assessed over 16 metabolic rates (VO2 from 0.9 to 6 L/min) lasting 5 minutes each, repeated for two times. Table 1 shows the protocols used for accuracy and repeatability. The selected protocols encompass a broad spectrum of metabolic rates, ranging from a low VO2 of 941 mL/min (representing light exercise intensity) to a high VO2 of 6063 mL/min (representing very intense exercise typical of athletes), with increments of 100–600 mL/min to simulate a 1–2 MET increase per stage. For each metabolic rate, the corresponding stroke volume and heart rate reflect the values most observed in humans achieving the respective VO2. All tests were performed over a one-week period, in the early morning hours, by a single qualified technician, within a well-ventilated laboratory under consistent atmospheric conditions. Protocol stages 1–3 were executed in duplicate on day 1, stages 4–7 were completed in duplicate on day 2, stages 8–10 were repeated twice on day 3, stages 11–13 were duplicated on day 4, and stages 14–16 were performed in duplicate on day 5. Raw data were exported from the Q-NRG Max® and reduced using Excel. Raw data were averaged every 60 seconds and then entered into a spreadsheet for later analysis. To ensure repeatability of results during different days, the tests were performed in an air-conditioned laboratory with consistent atmospheric pressure (690mmHg), ambient temperature (23°C), and relative humidity (25%). Atmospheric conditions were measured by the Q-NRG Max® before and after each test and values were compared to ensure consistency. A fan was placed near the outlet of the metabolic simulator to prevent accumulation of expired air around the Q-NRG Max®. The accuracy and of the Q-NRG Max® were assessed for: VO2 (mL/min), VCO2 (mL/min) and VE (L/min).
[Figure omitted. See PDF.]
[Figure omitted. See PDF.]
Statistical analysis
Accuracy.
To allow comparisons between the results of this study with previous validation research, measurements were analyzed considering the two ranges of metabolic rates most commonly used in the literature: VO2 from 0.9 to 4 mL/min (first 10 metabolic rates), and VO2 from 0.9 to 6 mL/min (all 16 metabolic rates). Agreement between the Q-NRG Max® and the VacuMed systems were assessed for VO2, VCO2 and VE parameters by ordinary least products (OLP) regression analysis, which account for measurement error in both devices [22]. In this analysis the coefficients of determination (R2) and slope and intercept with the 95% of confidence intervals (95% CI) were calculated to verify fixed and proportional biases. The hypothesis of proportional and fixed bias was rejected when the 95% CI contained the value 1 for the slope and the 0 for the intercept. Accuracy was quantified as the percentage differences (error) between the Q-NRG Max® and VacuMed simulator and reported as mean and range values, and as the mean absolute percent error (MAPE) between the two values calculated as . Mean differences were assessed using a paired samples t-test. The intraclass correlation coefficient (ICC) was calculated for criterion accuracy. A single measure, two-way random model, type absolute intra-class correlation coefficient was used to calculate ICCs [23]. Measurement error was expressed as “typical percentage error” (TE), calculated by dividing the standard deviation of the difference score by √ 2 [23], and by “minimum detectable change” (MDC), calculated as . Agreement between the Q-NRG Max® and the VacuMed systems were assessed using Bland-Altman plots and 95% CI between [24]. Analysis was performed using the first 10 metabolic rates (VO2 from 0.9 to 4 L/min, low-to-moderate VO2max range commonly used in research studies) and using all 16 metabolic rates (VO2 from 0.8 to 6 L/min, low-to-excellent VO2max range including metabolic rates obtained by high-performance athletes).
Repeatability
Sixteen metabolic rates (from 0.9 to 6 L/min) were reproduced by the metabolic simulator and measured by the Q-NRG Max® twice. The intra-device repeatability of the Q-NRG Max® was evaluated using a single measure, two-way mixed model to calculate ICCs for VO2, VCO2 and VE [25,26]. Due to the lack of a reference system, the difference between the two trials was quantified as MAPE between measurements of the same Q-NRG Max® as . The repeatability of the Q-NRG Max® was also assessed using a paired sample t-test for VO2, VCO2 and VE. Measurement error was expressed in TE% and MDC.
Statistical analyses were performed using the SPSS software (SPSS Inc., IBM, Chicago, IL, USA), with a significance level set at p < 0.05.
Results
Accuracy
The agreement between the VacuMed simulator and the Q-NRG Max® is reported in Table 2. The results of the OLP regression analysis and of the Bland-Altman plots are shown in Fig 2 (0.9–4 L/min VO2) and Fig 3 (0.9–6 L/min VO2). Each graph reports the OLP regression plot, with the linear regression (solid line), the identity (dashed line), the equation, the determination coefficient (R2) and the absolute mean differences, and the Bland-Altman plot (upper-left panel) with the mean percentage difference (solid lines) and the 95% CI (dashed line).
[Figure omitted. See PDF.]
[Figure omitted. See PDF.]
[Figure omitted. See PDF.]
0.9–4 L/min VO2 metabolic rates.
A very strong correlation was observed in VE, VO2 and VCO2 between the VacuMed and Q-NRG Max® with a R2 ranging from 0.999 (VO2 and VCO2) to 1.000 (VE). No fixed or proportional bias were observed in all variables (slope and intercept include 1 and 0, respectively). The mean percentage difference was 1.01% in VO2 (p = 0.1952), 0.89% in VCO2 (p = 0.1615), and 0.87% in VE (p < 0.05). ICC values and 95% CI were excellent for all variables (> 0.99). For VE, VO2 and VCO2 the TE were 0.67%, 1.07% and 0.97%, respectively. For VE, VO2 and VCO2 the MDC were 1.55%, 2.49% and 2.27%, respectively. Bland-Altman plots show a mean difference of 0.63 L (95% CI of −0.56 and 1.82 L) for VE, 17.73 mL (95% CI of −60.78 and 96.23 mL) for VO2, and 15.16 mL (95% CI of −46.43 and 76.74 mL) for VCO2.
0.9–6 L/min VO2 metabolic rates.
A very strong correlation was observed in VO2, VCO2 and VE between the VacuMed and Q-NRG Max® with a R2 ranging from 0.998 (VO2 and VCO2) to 1.000 (VE). No fixed or proportional bias were observed in VE (slope and intercept that include 1 and 0, respectively), while proportional bias was observed in VO2 and VCO2 (intercept values do not include 0). Mean percentage differences were significant for VE (0.65%, p < 0.05) and not significant for VO2 (0.03%, p = 0.3184) and VCO2 (−0.39%, p = 0.1246). ICC and 95% CI values were excellent for all variables (> 0.99). For VO2, VCO2 and VE the TE were 0.58%, 1.46% and 1.63%, respectively. For VO2, VCO2 and VE the MDC were 1.35%, 3.41% and 3.81%, respectively. Bland-Altman plots show a mean difference of 0.57 L (95% CI of −0.65 and 1.80 L) for VE, −23.23 mL (95% CI of −199.70 mL and 153.24 mL) for VO2, and −43.03 mL (95% CI of −250.42 and 164.36 mL) for VCO2.
Repeatability
The results of the repeatability analysis are reported in Table 3. The repeatability analysis was performed using all 16 metabolic rates (0.9-6 L/min VO2). No significant differences were found in VO2, VCO2 and VE between trials. For all variables, the MAPE was below 0.5% with the 95% CI values below 1%, the ICC was excellent (= 1.000), and the TE was below 1%. The MDC for VO2, VCO2 and VE was 1.02%, 1.99% and 2.11%, respectively.
[Figure omitted. See PDF.]
Discussion
The aim of this study was to assess the accuracy and repeatability of the Q-NRG Max® against a metabolic simulator using a wide range of metabolic rates up to super-athletic VO2 values. When investigating the accuracy of the machine, to compare results against previous studies, an analysis of the first 10 metabolic rates and one of all 16 metabolic rates was performed.
Accuracy
0.9–4 L/min VO2 metabolic rates.
The measurements of the Q-NRG Max® showed very high agreement with the simulated values for VO2, VCO2 and VE when considering metabolic rates with VO2 from 0.9 to 4 L/min. All the variables showed high correlation (R2 > 0.99), excellent ICC values (> 0.99) and high agreements from the OLP regression and Bland Altman plots. The mean percentage difference in VO2 was 1.01% (−2.32 to 2.75) which is lower than ranges reported by other studies conducted on the K5 (−2.55% to 3.52% and −7.27 to 0.03%), Oxycon Pro (5.8% to 10.5%) and COSMED Quark (9% to 12% and 5% to 7%) [11,14,15,27]. The 1.07% TE and the 2.49% MDC were lower than the 5% recommended threshold [1,11,28,29] and lower than the 1.37% TE and 3.79% MDC measured by Guidetti et al. (2018) [11]. The 0.89% (−1.78% to 2.79%) mean percentage difference in VCO2 was lower than the 10.5% to 11.7% obtained with the Oxycon pro, the 5% to 7% obtained with the COSMED Quark, and the −6.09% to 2.99% obtained with the COSMED K5 [14,15,27]. The 0.87% (−0.27% to 2.89%) mean percentage difference in VE was lower than the −4.7% to 3.3% reported by VmaxSTtm, and the 4.2% reported by the COSMED K4 b2 [19,20]. The TE and MDC for VCO2 (0.97% and 2.27%, respectively) and for VE (0.67% and 1.55%, respectively) were lower than the one reported by Guidetti et al. (2018) (VCO2 1.34% and 3.71%; VE 0.73% and 2.01%, respectively) [11].
0.9–6 L. min-1 VO2 metabolic rates.
A result of high relevance is that the Q-NRG Max® showed to be an accurate system also when considering metabolic rates with VO2 from 0.9 to 6 L/min. All variables showed high correlation (R2 > 0.99) and excellent ICC values (> 0.99). The mean percentage difference in VO2 was −0.03% (−3.98% to 2.75%) which is smaller than the −8.0% (−12.6 to −3.4) mean percentage error obtained with the VmaxSttm [19] and the 3.6% (up to 7%) obtained with the K4b2 [20], and the 7.8% to −3.0% percentage differences obtained with the Cortex MetaMax3B [21]. The greatest difference was observed at the two highest metabolic rates simulating extremely high metabolic conditions (VE and VO2 greater than 200 L. min−1 and 5.6 L/min, respectively). However, the TE (1.46%) and MDC (3.41%) were lower than the 5% recommended threshold showing acceptable values despite the proportional bias observed by the OLP regression [1,28,29]. This is in line with the results of previous research showing that the accuracy of a metabolic cart may decrease at very high ventilation rates and that the measurement errors are proportional to the magnitude of the simulated values [15,27]. Research indicates that metabolic simulators may lose accuracy at producing very high flow rates when operating near their maximum capacity [30]. This may be due to factors such as increased piston friction potentially altering the piston’s mechanical structure, elevated air temperatures, and the possibility of mechanical linkages occurring within the system. The VCO2 showed proportional bias but low TE (1.63%) and MDC (3.81%). The mean percentage difference was −0.39% (−4.98 to 2.79%), which is lower than the −4.6% (−12.0% to 2.8%) for the VmaxSTtm [19], the −2.2% for the K4b2 [20], and the −0.8% to 10.2% percentage differences for Cortex MetaMax3B [21] studies. The VE measured by the Q-NRG Max® showed a good agreement with the simulated values with no proportional or fixed bias and a mean percentage difference of 0.65% (−0.27% to 2.89%). These results are lower than the 2.5% to 4% reported by Vogler et al. (2010) testing the Cortex MetaMax3B with ventilations up to 240 L/min [21]. The TE (0.58%) and the MDC (1.35%) were lower than the reference values from literature [1].
Repeatability
The results of the repeatability analysis showed excellent results with ICC values equal to 1.00 in all variables over the 16 simulated metabolic rates. These values are similar to the 0.99–1.00 ICC observed with the COSMED K5 [11,16,27] and higher than the 0.76–0.93 ICC observed with the COSMED Fitmate [31]. The MAPE obtained in this study was below 0.5%, which is lower than the 1% relative error generated from an automated calibration system [10] and the 2% recommended reliability limits [1]. Moreover, this value is lower than what is reported by previous studies indicating a 0.7% to 1.2% MAPE in COSMED K5 and a −0.1% to 2.5% percentage difference in the Cortex Metamax 3B [11,32]. Finally, the Q-NRG Max® reported a 0.44% to 0.90% TE% and 1.02 to 2.11% MDC which is similar to the observed by previous research investigating the COSMED K5 [11,16,27].
Limitations
A limitation of the present study is the fact that the VacuMed simulator produces a gas mixture at room temperature and humidity [10], only mathematically corrected by the manufacturer’s software. Moreover, the intrinsic accuracy of the metabolic simulator (± 1.00% for VO2 and VCO2, ± 0.5% for stroke volume) and the lack of biological variability otherwise obtained during real-life measurements in humans affect the generalizability of the results. Therefore, additional validation studies with human subjects are necessary to investigate the validity and reliability of the Q-NRG Max® and confirm its applicability in real-world settings.
Conclusion
The high agreement, the very high correlation coefficient and the excellent ICC between the Q-NRG Max® and the simulator, together with below recommended threshold percentage difference, TE and MDC make the Q-NRG Max® a valid and reliable mobile system for the measurement of VE, VO2, and VCO2 up to super-athletic performance.
Supporting information
S1 File. Data.
https://doi.org/10.1371/journal.pone.0319394.s001
(XLSX)
References
1. 1. Hodges LD, Brodie DA, Bromley PD. Validity and reliability of selected commercially available metabolic analyzer systems. Scand J Med Sci Sports. 2005;15(5):271–9. pmid:16181250
* View Article
* PubMed/NCBI
* Google Scholar
2. 2. Macfarlane D. Automated metabolic gas analysis systems: a review. Sports Med. 2001;31(12):841–61.
* View Article
* Google Scholar
3. 3. Meyer T, Davison RCR, Kindermann W. Ambulatory gas exchange measurements--current status and future options. Int J Sports Med. 2005;26(Suppl 1):S19–27. pmid:15702452
* View Article
* PubMed/NCBI
* Google Scholar
4. 4. Perez-Suarez I, Martin-Rincon M, Gonzalez-Henriquez JJ, Fezzardi C, Perez-Regalado S, Galvan-Alvarez V, et al. Accuracy and precision of the COSMED K5 portable analyser. Front Physiol. 2018;9:1764. pmid:30622475
* View Article
* PubMed/NCBI
* Google Scholar
5. 5. Tsekouras YE, Tambalis KD, Sarras SE, Antoniou AK, Kokkinos P, Sidossis LS. Validity and reliability of the new portable metabolic analyzer PNOE. Front Sports Act Living. 2019;1:24. pmid:33344948
* View Article
* PubMed/NCBI
* Google Scholar
6. 6. Macfarlane DJ. Open-circuit respirometry: a historical review of portable gas analysis systems. Eur J Appl Physiol. 2017;117(12):2369–86. pmid:29043499
* View Article
* PubMed/NCBI
* Google Scholar
7. 7. Dieli-Conwright CM, Jensky NE, Battaglia GM, McCauley SA, Schroeder ET. Validation of the CardioCoachCO2 for submaximal and maximal metabolic exercise testing. J Strength Cond Res. 2009;23(4):1316–20. pmid:19528838
* View Article
* PubMed/NCBI
* Google Scholar
8. 8. Nieman D, Lasasso H, Austin M, Pearce S, McInnis T, Unick J. Validation of Cosmed’s FitMateTM in measuring exercise metabolism. Res Sports Med (Print). 2007 Mar 1;15:67–75.
* View Article
* Google Scholar
9. 9. Vehrs PR, Keller DM, George JD, Hager RL, Fellingham GW. Monitoring VO2max during fourteen weeks of endurance training using the CardioCoach. J Strength Cond Res. 2007;21(1):62–6. pmid:17313267
* View Article
* PubMed/NCBI
* Google Scholar
10. 10. Gore CJ, Catcheside PG, French SN, Bennett JM, Laforgia J. Automated VO2max calibrator for open-circuit indirect calorimetry systems. Med Sci Sports Exerc. 1997;29(8):1095–103. pmid:9268968
* View Article
* PubMed/NCBI
* Google Scholar
11. 11. Guidetti L, Meucci M, Bolletta F, Emerenziani GP, Gallotta MC, Baldari C. Validity, reliability and minimum detectable change of COSMED K5 portable gas exchange system in breath-by-breath mode. PLoS One. 2018;13(12):e0209925. pmid:30596748
* View Article
* PubMed/NCBI
* Google Scholar
12. 12. Huszczuk A, Whipp BJ, Wasserman K. A respiratory gas exchange simulator for routine calibration in metabolic studies. Eur Respir J. 1990;3(4):465–8. pmid:2114308
* View Article
* PubMed/NCBI
* Google Scholar
13. 13. Souren T, Rose E, Groepenhoff H. Comparison of two metabolic simulators used for gas exchange verification in cardiopulmonary exercise test carts. Front Physiol. 2021;12:667386. pmid:34149449
* View Article
* PubMed/NCBI
* Google Scholar
14. 14. Beijst C, Schep G, Breda E van, Wijn PFF, Pul C van. Accuracy and precision of CPET equipment: a comparison of breath-by-breath and mixing chamber systems. J Med Eng Technol. 2013;37(1):35–42. pmid:23110656
* View Article
* PubMed/NCBI
* Google Scholar
15. 15. Carter J, Jeukendrup AE. Validity and reliability of three commercially available breath-by-breath respiratory systems. Eur J Appl Physiol. 2002;86(5):435–41. pmid:11882930
* View Article
* PubMed/NCBI
* Google Scholar
16. 16. Winkert K, Kamnig R, Kirsten J, Steinacker JM, Treff G. Inter- and intra-unit reliability of the COSMED K5: Implications for multicentric and longitudinal testing. PLoS One. 2020;15(10):e0241079. pmid:33096546
* View Article
* PubMed/NCBI
* Google Scholar
17. 17. Alejo LB, Montalvo-Pérez A, Valenzuela PL, Revuelta C, Ozcoidi LM, de la Calle V, et al. Comparative analysis of endurance, strength and body composition indicators in professional, under-23 and junior cyclists. Front Physiol. 2022;13:945552. pmid:35991188
* View Article
* PubMed/NCBI
* Google Scholar
18. 18. Faria IE, Faria EW, Roberts S, Yoshimura D. Comparison of physical and physiological characteristics in elite young and mature cyclists. Res Q Exerc Sport. 1989;60(4):388–95. pmid:2489869
* View Article
* PubMed/NCBI
* Google Scholar
19. 19. Prieur F, Castells J, Denis C. A methodology to assess the accuracy of a portable metabolic system (VmaxST). Med Sci Sports Exerc. 2003;35(5):879–85. pmid:12750601
* View Article
* PubMed/NCBI
* Google Scholar
20. 20. Rodríguez FA, Keskinen KL, Kusch M, Hoffmann U. Validity of a swimming snorkel for metabolic testing. Int J Sports Med. 2008;29(2):120–8. pmid:17960507
* View Article
* PubMed/NCBI
* Google Scholar
21. 21. Vogler AJ, Rice AJ, Gore CJ. Validity and reliability of the Cortex MetaMax3B portable metabolic system. J Sports Sci. 2010;28(7):733–42. pmid:20419553
* View Article
* PubMed/NCBI
* Google Scholar
22. 22. Ludbrook J. Linear regression analysis for comparing two measurers or methods of measurement: but which regression? Clin Exp Pharmacol Physiol. 2010;37(7):692–9. pmid:20337658
* View Article
* PubMed/NCBI
* Google Scholar
23. 23. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1):1–15. pmid:10907753
* View Article
* PubMed/NCBI
* Google Scholar
24. 24. Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135–60.
* View Article
* Google Scholar
25. 25. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63. pmid:27330520
* View Article
* PubMed/NCBI
* Google Scholar
26. 26. McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Methods. 1996;1(1):30–46.
* View Article
* Google Scholar
27. 27. Winkert K, Kirsten J, Dreyhaupt J, Steinacker JM, Treff G. The COSMED K5 in breath-by-breath and mixing chamber mode at low to high intensities. Med Sci Sports Exerc. 2020;52(5):1153–62. pmid:31895296
* View Article
* PubMed/NCBI
* Google Scholar
28. 28. Babineau C, Léger L, Long A, Bosquet L. Variability of maximum oxygen consumption measurement in various metabolic systems. J Strength Condit Res. 1999;13(4):318–24.
* View Article
* Google Scholar
29. 29. Overstreet BS, Bassett DR Jr, Crouter SE, Rider BC, Parr BB. Portable open-circuit spirometry systems. J Sports Med Phys Fitness. 2017;57(3):227–37. pmid:26861831
* View Article
* PubMed/NCBI
* Google Scholar
30. 30. Souren T, Rose E, Groepenhoff H. Comparison of two metabolic simulators used for gas exchange verification in cardiopulmonary exercise test carts. Front Physiol. 2021 June;12.
* View Article
* Google Scholar
31. 31. Brisswalter J, Peikriszwili Tartaruga M. Comparison of COSMED’S FitMate (TM) and K4b2 metabolic systems reliability during graded cycling exercise. Scandinavian J Clin Lab Invest. 2014;74(11):722–4.
* View Article
* Google Scholar
32. 32. Macfarlane DJ, Wong P. Validity, reliability and stability of the portable Cortex Metamax 3B gas analysis system. Eur J Appl Physiol. 2012;112(7):2539–47. pmid:22075643
* View Article
* PubMed/NCBI
* Google Scholar
Citation: Falcioni L, Guidetti L, Baldari C, Posada AS, Wing C, Dover L, et al. (2025) Accuracy and repeatability of the COSMED® Q-NRG max mobile metabolic system. PLoS ONE 20(3): e0319394. https://doi.org/10.1371/journal.pone.0319394
About the Authors:
Lavinia Falcioni
Roles: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing
Affiliation: Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, United States of America
ORICD: https://orcid.org/0000-0001-8704-7044
Laura Guidetti
Roles: Conceptualization, Data curation, Methodology, Software, Writing – review & editing
Affiliation: Department of Humanities, Movement, and Education Sciences, University “Niccolò Cusano”, Rome, Italy
ORICD: https://orcid.org/0000-0002-1419-4550
Carlo Baldari
Roles: Conceptualization, Data curation, Methodology, Writing – review & editing
Affiliation: Psychology Department, eCampus University, Novedrate, Como, Italy
Andrey Sanko Posada
Roles: Investigation, Methodology, Project administration, Writing – review & editing
Affiliation: Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, United States of America
Chris Wing
Roles: Investigation, Methodology, Project administration, Writing – review & editing
Affiliation: Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, United States of America
ORICD: https://orcid.org/0009-0003-7761-9178
Luke Dover
Roles: Investigation, Methodology, Project administration, Writing – review & editing
Affiliation: Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, United States of America
Marco Meucci
Roles: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing
E-mail: [email protected]
Affiliation: Department of Public Health and Exercise Science, Appalachian State University, Boone, North Carolina, United States of America
ORICD: https://orcid.org/0000-0002-1549-2082
1. Hodges LD, Brodie DA, Bromley PD. Validity and reliability of selected commercially available metabolic analyzer systems. Scand J Med Sci Sports. 2005;15(5):271–9. pmid:16181250
2. Macfarlane D. Automated metabolic gas analysis systems: a review. Sports Med. 2001;31(12):841–61.
3. Meyer T, Davison RCR, Kindermann W. Ambulatory gas exchange measurements--current status and future options. Int J Sports Med. 2005;26(Suppl 1):S19–27. pmid:15702452
4. Perez-Suarez I, Martin-Rincon M, Gonzalez-Henriquez JJ, Fezzardi C, Perez-Regalado S, Galvan-Alvarez V, et al. Accuracy and precision of the COSMED K5 portable analyser. Front Physiol. 2018;9:1764. pmid:30622475
5. Tsekouras YE, Tambalis KD, Sarras SE, Antoniou AK, Kokkinos P, Sidossis LS. Validity and reliability of the new portable metabolic analyzer PNOE. Front Sports Act Living. 2019;1:24. pmid:33344948
6. Macfarlane DJ. Open-circuit respirometry: a historical review of portable gas analysis systems. Eur J Appl Physiol. 2017;117(12):2369–86. pmid:29043499
7. Dieli-Conwright CM, Jensky NE, Battaglia GM, McCauley SA, Schroeder ET. Validation of the CardioCoachCO2 for submaximal and maximal metabolic exercise testing. J Strength Cond Res. 2009;23(4):1316–20. pmid:19528838
8. Nieman D, Lasasso H, Austin M, Pearce S, McInnis T, Unick J. Validation of Cosmed’s FitMateTM in measuring exercise metabolism. Res Sports Med (Print). 2007 Mar 1;15:67–75.
9. Vehrs PR, Keller DM, George JD, Hager RL, Fellingham GW. Monitoring VO2max during fourteen weeks of endurance training using the CardioCoach. J Strength Cond Res. 2007;21(1):62–6. pmid:17313267
10. Gore CJ, Catcheside PG, French SN, Bennett JM, Laforgia J. Automated VO2max calibrator for open-circuit indirect calorimetry systems. Med Sci Sports Exerc. 1997;29(8):1095–103. pmid:9268968
11. Guidetti L, Meucci M, Bolletta F, Emerenziani GP, Gallotta MC, Baldari C. Validity, reliability and minimum detectable change of COSMED K5 portable gas exchange system in breath-by-breath mode. PLoS One. 2018;13(12):e0209925. pmid:30596748
12. Huszczuk A, Whipp BJ, Wasserman K. A respiratory gas exchange simulator for routine calibration in metabolic studies. Eur Respir J. 1990;3(4):465–8. pmid:2114308
13. Souren T, Rose E, Groepenhoff H. Comparison of two metabolic simulators used for gas exchange verification in cardiopulmonary exercise test carts. Front Physiol. 2021;12:667386. pmid:34149449
14. Beijst C, Schep G, Breda E van, Wijn PFF, Pul C van. Accuracy and precision of CPET equipment: a comparison of breath-by-breath and mixing chamber systems. J Med Eng Technol. 2013;37(1):35–42. pmid:23110656
15. Carter J, Jeukendrup AE. Validity and reliability of three commercially available breath-by-breath respiratory systems. Eur J Appl Physiol. 2002;86(5):435–41. pmid:11882930
16. Winkert K, Kamnig R, Kirsten J, Steinacker JM, Treff G. Inter- and intra-unit reliability of the COSMED K5: Implications for multicentric and longitudinal testing. PLoS One. 2020;15(10):e0241079. pmid:33096546
17. Alejo LB, Montalvo-Pérez A, Valenzuela PL, Revuelta C, Ozcoidi LM, de la Calle V, et al. Comparative analysis of endurance, strength and body composition indicators in professional, under-23 and junior cyclists. Front Physiol. 2022;13:945552. pmid:35991188
18. Faria IE, Faria EW, Roberts S, Yoshimura D. Comparison of physical and physiological characteristics in elite young and mature cyclists. Res Q Exerc Sport. 1989;60(4):388–95. pmid:2489869
19. Prieur F, Castells J, Denis C. A methodology to assess the accuracy of a portable metabolic system (VmaxST). Med Sci Sports Exerc. 2003;35(5):879–85. pmid:12750601
20. Rodríguez FA, Keskinen KL, Kusch M, Hoffmann U. Validity of a swimming snorkel for metabolic testing. Int J Sports Med. 2008;29(2):120–8. pmid:17960507
21. Vogler AJ, Rice AJ, Gore CJ. Validity and reliability of the Cortex MetaMax3B portable metabolic system. J Sports Sci. 2010;28(7):733–42. pmid:20419553
22. Ludbrook J. Linear regression analysis for comparing two measurers or methods of measurement: but which regression? Clin Exp Pharmacol Physiol. 2010;37(7):692–9. pmid:20337658
23. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000;30(1):1–15. pmid:10907753
24. Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999;8(2):135–60.
25. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. 2016;15(2):155–63. pmid:27330520
26. McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Methods. 1996;1(1):30–46.
27. Winkert K, Kirsten J, Dreyhaupt J, Steinacker JM, Treff G. The COSMED K5 in breath-by-breath and mixing chamber mode at low to high intensities. Med Sci Sports Exerc. 2020;52(5):1153–62. pmid:31895296
28. Babineau C, Léger L, Long A, Bosquet L. Variability of maximum oxygen consumption measurement in various metabolic systems. J Strength Condit Res. 1999;13(4):318–24.
29. Overstreet BS, Bassett DR Jr, Crouter SE, Rider BC, Parr BB. Portable open-circuit spirometry systems. J Sports Med Phys Fitness. 2017;57(3):227–37. pmid:26861831
30. Souren T, Rose E, Groepenhoff H. Comparison of two metabolic simulators used for gas exchange verification in cardiopulmonary exercise test carts. Front Physiol. 2021 June;12.
31. Brisswalter J, Peikriszwili Tartaruga M. Comparison of COSMED’S FitMate (TM) and K4b2 metabolic systems reliability during graded cycling exercise. Scandinavian J Clin Lab Invest. 2014;74(11):722–4.
32. Macfarlane DJ, Wong P. Validity, reliability and stability of the portable Cortex Metamax 3B gas analysis system. Eur J Appl Physiol. 2012;112(7):2539–47. pmid:22075643
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Abstract
Purpose
To investigate the accuracy and repeatability of the Q-NRG Max® metabolic system against a VacuMed metabolic simulator using a wide range of metabolic rates.
Methods
Sixteen metabolic rates (oxygen consumption 0.9–6 L/min), with different combinations of minute ventilation, oxygen consumption, and carbon dioxide production, were measured for 5 minutes, two times by a single Q-NRG Max® unit over the course of one week. Recordings were performed early in the morning, by the same trained technician, in a ventilated laboratory under the same atmospheric conditions. Accuracy was assessed by ordinary least products (OLP) regression analysis, Bland-Altman plots, intraclass correlation coefficients (ICC), mean percentage differences, technical errors (TE) and minimum detectable change (MDC) for all three variables. This analysis was performed using 10 metabolic rates (oxygen consumption 0.9–4 L/min) and 16 metabolic rates (oxygen consumption 0.9–6 L/min) to allow comparisons with previous research. Intra-device repeatability was performed by absolute percentage differences between measurements (MAPE), ICC, TE, and MDC for the same variables. Repeatability was investigated using 16 metabolic rates.
Results
High agreement and excellent ICCs (>0.998) were observed for all variables when considering both 10 and 16 metabolic rates. The mean percentage difference, TE and MDC were 0.87%–1.01%, 0.67%–1.07%, 1.55%–2.49%, respectively for the first 10 metabolic rates, and −0.39%–0.65%, 0.58%–1.63%, 1.35%–3.81%, respectively for the 16 metabolic rates. The intra-device repeatability results showed an excellent ICCs (=1.000), MAPE < 0.5%, TE < 1%, and MDC ≤ 2%.
Conclusion
The Q-NRG Max® is a valid and reliable mobile metabolic system for the measurement of ventilation, oxygen consumption, and carbon dioxide production. Measurements were below the 5% TE and MDC, and 2% MAPE recommended thresholds across a wide range of metabolic rates up to 6 L/min oxygen consumption.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
; Guidetti, Laura
; Baldari, Carlo; Andrey Sanko Posada; Wing, Chris
; Dover, Luke; Meucci, Marco