当前静息代谢率预测方程缺乏敏感性和特异性,以表明运动中相对能量不足:一项针对优秀运动员的大型队列研究。

IF 3 3区 医学 Q2 NUTRITION & DIETETICS
Ida A Heikura, Ming-Chang Tsai, Erik Sesbreno, Walter T P McCluskey, Liz Johnson, Holly Murray, Trent Stellingwerff
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引用次数: 0

摘要

目的:将测量的静息代谢率(RMR)与预测的RMR方程(RMRratio)进行比较,以了解低RMRratio是否与运动中相对能量缺乏症(red)临床评估工具2 (CAT2)严重程度/风险评分相关。方法:根据CAT2对3-5等级的运动员进行绿/黄/橙/红灯评分,女127名,男53名。通过间接量热法在同一天早晨禁食时评估RMR和亚最大运动能量消耗(通过循环测力计)。低RMR被定义为RMR比值< 0.90,并对11个RMR预测方程进行了对CAT2的敏感性、特异性和预测有效性的测试。结果:RMRratio (Cunningham)仅在红光下低于绿光(0.90±0.07∶0.99±0.10;P = 0.023;但只有44%的红灯运动员的rmrr较低)。低RMRratio的患病率从1% (Owen方程)到68% (van Hooren方程)不等,尽管总体的red患病率为46%。作为一种诊断方法(无red[绿色]vs. red[黄色+橙色+红色]),Cunningham方程在RMRratio为1.00时的敏感性(真阳性)为0.77,在RMRratio为0.70时的特异性(真阴性)为1.00。绿色组的运动能量消耗明显低于橙色组(0.131±0.013 vs 0.142±0.008 kcal·kg无脂质量-1·min-1;P < 0.001),但红色高于橙色(0.127±0.011)。结论:预测方程的选择从根本上影响RMRratio的解释。尽管通过RMR比值在横断面检测极端红血球病例(红灯)方面可能有一定的效用,但需要更多的研究,重点关注运动/表型特异性预测方程和不同的风险阈值,以加强RMR作为红血球诊断的有效性和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Current Resting Metabolic Rate Prediction Equations Lack Sensitivity and Specificity to Indicate Relative Energy Deficiency in Sport: A Large Cohort Study in Elite Athletes.

Objectives: Measured resting metabolic rate (RMR) was compared to predicted RMR equations (RMRratio) to see whether a low RMRratio relates to the Relative Energy Deficiency in Sport (REDs) Clinical Assessment Tool 2 (CAT2) severity/risk score.

Methods: Female (n = 127) and male (n = 53) athletes (performance Tiers 3-5) were assigned green/yellow/orange/red light according to CAT2. RMR and submaximal exercise energy expenditure (via cycle ergometer) were assessed fasted on the same morning via indirect calorimetry. Low RMR was defined as RMRratio < 0.90, with 11 RMR prediction equations tested for sensitivity, specificity, and predictive validity against the CAT2.

Results: RMRratio (Cunningham) was only lower in red versus green light (0.90 ± 0.07 vs. 0.99 ± 0.10; p = .023; but RMRratio was only low in 44% of red light athletes). The prevalence of low RMRratio ranged from 1% (Owen equation) to 68% (van Hooren equation) despite the overall prevalence of REDs being 46%. As a diagnostic (no REDs [green] vs. REDs [yellow + orange + red]), Cunningham equation reported sensitivity (true positives) of 0.77 at RMRratio of 1.00 and specificity (true negatives) of 1.00 at RMRratio of 0.70. Exercise energy expenditure was significantly lower in green versus orange (0.131 ± 0.013 vs. 0.142 ± 0.008 kcal·kg fat-free mass-1·min-1; p < .001) but was greater in red (0.127 ± 0.011) versus orange.

Conclusion: Interpretation of RMRratio is radically impacted by choice of prediction equation. Although there may be some utility in cross-sectionally detecting extreme REDs cases (red light) via RMRratio, more research with a focus on sport/phenotype-specific prediction equations and varying risk thresholds is required to strengthen the validity and reliability of RMR as a part of REDs diagnostics.

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来源期刊
CiteScore
5.00
自引率
8.00%
发文量
50
审稿时长
6-12 weeks
期刊介绍: The International Journal of Sport Nutrition and Exercise Metabolism (IJSNEM) publishes original scientific investigations and scholarly reviews offering new insights into sport nutrition and exercise metabolism, as well as articles focusing on the application of the principles of biochemistry, physiology, and nutrition to sport and exercise. The journal also offers editorials, digests of related articles from other fields, research notes, and reviews of books, videos, and other media releases. To subscribe to either the print or e-version of IJSNEM, press the Subscribe or Renew button at the top of your screen.
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