Kokkinos Peter, Kaminsky Leonard A, Arena Ross, Zhang Jiajia, Myers Jonathan
Department of Cardiology, Veterans Affairs Medical Center, Washington, DC; Department of Clinical Research and Leadership, George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Cardiology, Georgetown University School of Medicine, Washington, DC; Department of Exercise Science, University of South Carolina, Arnold School of Public Health, Columbia, South Carolina.
Fisher Institute of Health and Well-Being and Clinical Exercise Physiology, Ball State University, Muncie, Indiana.
Am J Cardiol. 2017 Aug 15;120(4):688-692. doi: 10.1016/j.amjcard.2017.05.037. Epub 2017 Jun 1.
Impaired cardiorespiratory fitness (CRF) is closely linked to chronic illness and associated with adverse events. The American College of Sports Medicine (ACSM) regression equations (ACSM equations) developed to estimate oxygen uptake have known limitations leading to well-documented overestimation of CRF, especially at higher work rates. Thus, there is a need to explore alternative equations to more accurately predict CRF. We assessed maximal oxygen uptake (VO max) obtained directly by open-circuit spirometry in 7,983 apparently healthy subjects who participated in the Fitness Registry and the Importance of Exercise National Database (FRIEND). We randomly sampled 70% of the participants from each of the following age categories: <40, 40 to 50, 50 to 70, and ≥70 and used the remaining 30% for validation. Multivariable linear regression analysis was applied to identify the most relevant variables and construct the best prediction model for VO max. Treadmill speed and treadmill speed × grade were considered in the final model as predictors of measured VO max and the following equation was generated: VO max in ml O/kg/min = speed (m/min) × (0.17 + fractional grade × 0.79) + 3.5. The FRIEND equation predicted VO max with an overall error >4 times lower than the error associated with the traditional ACSM equations (5.1 ± 18.3% vs 21.4 ± 24.9%, respectively). Overestimation associated with the ACSM equation was accentuated when different protocols were considered separately. In conclusion, The FRIEND equation predicts VO max more precisely than the traditional ACSM equations with an overall error >4 times lower than that associated with the ACSM equations.
心肺适能受损与慢性病密切相关，并与不良事件相关。美国运动医学学会（ACSM）开发的用于估计摄氧量的回归方程（ACSM方程）存在已知局限性，导致有充分记录的心肺适能高估，尤其是在较高工作强度下。因此，需要探索替代方程以更准确地预测心肺适能。我们评估了7983名明显健康的受试者通过开路肺量计直接测得的最大摄氧量（VO₂max），这些受试者参与了健身注册和运动国家数据库（FRIEND）。我们从以下每个年龄类别中随机抽取70%的参与者：<40岁、40至50岁、50至70岁和≥70岁，并将其余30%用于验证。应用多变量线性回归分析来确定最相关的变量，并构建VO₂max的最佳预测模型。跑步机速度和跑步机速度×坡度在最终模型中被视为实测VO₂max的预测因子，并生成了以下方程：VO₂max（ml O₂/kg/min）=速度（m/min）×（0.17 + 坡度分数×0.79）+ 3.5。FRIEND方程预测VO₂max的总体误差比传统ACSM方程低4倍以上（分别为5.1±18.3%和21.4±24.9%）。当分别考虑不同方案时，与ACSM方程相关的高估更为明显。总之，FRIEND方程比传统ACSM方程更精确地预测VO₂max，总体误差比ACSM方程低4倍以上。
