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Validity, reliability and minimum detectable change of COSMED K5 portable gas exchange system in breath-by-breath mode

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  • Laura Guidetti
  • Marco Meucci
  • Francesco Bolletta
  • Gian Pietro Emerenziani
  • Maria Chiara Gallotta
  • Carlo Baldari

Abstract

Purpose: This study aimed to examine the validity, reliability and minimum detectable change (MDC) of the Cosmed K5 in breath by breath (BxB) mode, against VacuMed metabolic simulator. Intra and inter-units reliability was also assessed. Methods: Fourteen metabolic rates (from 0.9 to 4 L.min-1) were reproduced by a VacuMed system and pulmonary ventilation (VE), oxygen consumption (VO2) and carbon dioxide production (VCO2) were measured by two different K5 units. Validity was assessed by ordinary least products (OLP) regression analysis, Bland-Altman plots, intraclass correlation coefficients (ICC), mean percentage differences, technical errors (TE) and MDC for VE, VO2, and VCO2. Intra- and inter-K5 reliability was evaluated by absolute percentage differences between measurements (MAPE), ICCs, TE, and MDC. Results: Validity analysis from OLP regression data and Bland- Altman plots indicated high agreement between K5 and simulator. ICC values were excellent for all variables (>0.99). Mean percentage differences in VE (-0.50%, p = 0.11), VO2 (-0.04%, p = 0.80), and VCO2 (-1.03%, p = 0.09) showed no significant bias. The technical error (TE) ranged from 0.73% to 1.34% (VE and VCO2 respectively). MDC were lower than 4% (VE = 2.0%, VO2 = 3.8%, VCO2 = 3.7%). The intra and inter K5 reliability assessment reveled excellent ICCs (>0.99), MAPE

Suggested Citation

  • Laura Guidetti & Marco Meucci & Francesco Bolletta & Gian Pietro Emerenziani & Maria Chiara Gallotta & Carlo Baldari, 2018. "Validity, reliability and minimum detectable change of COSMED K5 portable gas exchange system in breath-by-breath mode," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-12, December.
    • Handle: RePEc:plo:pone00:0209925
    DOI: 10.1371/journal.pone.0209925
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    Cited by:

    1. Giovanna Zimatore & Maria Chiara Gallotta & Matteo Campanella & Piotr H. Skarzynski & Giuseppe Maulucci & Cassandra Serantoni & Marco De Spirito & Davide Curzi & Laura Guidetti & Carlo Baldari & Stavr, 2022. "Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review," IJERPH, MDPI, vol. 19(19), pages 1-24, October.

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