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使用百分位数生长曲线和对数线性异速生长法比较分钟通气量/二氧化碳产生斜率的个体差异和群体差异。

Comparing individual and population differences in minute ventilation/carbon dioxide production slopes using centile growth curves and log-linear allometry.

作者信息

Nevill Alan M, Myers Jonathan, Kaminsky Leonard A, Arena Ross, Myers Tony D

机构信息

Faculty of Education, Health and Wellbeing, University of Wolverhampton, Walsall, UK.

Division of Cardiology, VA Palo Alto Healthcare System, Palo Alto, CA, USA.

出版信息

ERJ Open Res. 2021 Jul 26;7(3). doi: 10.1183/23120541.00088-2021. eCollection 2021 Jul.

Abstract

Identifying vulnerable groups and/or individuals' cardiorespiratory fitness (CRF) is an important challenge for clinicians/researchers alike. To quantify CRF accurately, the assessment of several variables is now standard practice including maximal oxygen uptake (' ) and ventilatory efficiency, the latter assessed using the minute ventilation/carbon dioxide production ('/' ) slope. Recently, reference values (centiles) for '/' slopes for males and females aged 20 to 80 have been published, using cardiopulmonary exercise testing (CPX) data (treadmill protocol) from the Fitness Registry and the Importance of Exercise National Database (FRIEND Registry). In the current observational study we provide centile curves for the FRIEND Registry '/' slopes, fitted using the generalised additive model for location, scale and shape (GAMLSS), to provide individuals with a more precise estimate of where their '/' slopes fall within the population. We also confirm that by adopting allometric models (incorporating a log transformation), the resulting ANCOVAs provided more normal and homoscedastic residuals, with superior goodness-of-fit using the Akaike information criterion (AIC)=14 671 (compared with traditional ANCOVA's AIC=15 008) that confirms allometric models are vastly superior to traditional ANCOVA models. In conclusion, providing sex-by-age centile curves rather than referring to reference tables for ventilatory efficiency ('/' slopes) will provide more accurate estimates of where an individual's particular '/' slope falls within the population. Also, by adopting allometric models researchers are more likely to identify real and valid inferences when analysing population/group differences in '/' slopes.

摘要

识别弱势群体和/或个体的心肺适能(CRF)对临床医生和研究人员来说都是一项重大挑战。为了准确量化CRF,目前的标准做法是评估多个变量,包括最大摄氧量(' )和通气效率,后者通过分钟通气量/二氧化碳产生量('/' )斜率来评估。最近,利用健身注册与运动重要性国家数据库(FRIEND注册库)的心肺运动测试(CPX)数据(跑步机方案),公布了20至80岁男性和女性'/' 斜率的参考值(百分位数)。在当前的观察性研究中,我们提供了FRIEND注册库'/' 斜率的百分位数曲线,使用位置、尺度和形状的广义相加模型(GAMLSS)进行拟合,以便为个体提供更精确的估计,了解其'/' 斜率在人群中的位置。我们还证实,通过采用异速生长模型(纳入对数变换),得到的协方差分析提供了更正态和同方差的残差,使用赤池信息准则(AIC)=14 671时拟合优度更高(相比传统协方差分析的AIC=15 008),这证实了异速生长模型远优于传统协方差分析模型。总之,提供按性别和年龄划分的百分位数曲线,而不是参考通气效率('/' 斜率)的参考表,将能更准确地估计个体特定的'/' 斜率在人群中的位置。此外,通过采用异速生长模型,研究人员在分析人群/组间'/' 斜率差异时更有可能识别出真实有效的推断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/286c/8311134/a24ff93a1c56/00088-2021.01.jpg

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