Mazzola Giuseppe, Rondanelli Mariangela, Cattaneo Carlo, Lazzarotti Alessandro, Gasparri Clara, Barrile Gaetan Claude, Moroni Alessia, Mansueto Francesca, Minonne Leonardo, Perna Simone
Endocrinology and Nutrition Unit, Azienda di Servizi alla Persona "Istituto Santa Margherita", University of Pavia, 27100 Pavia, Italy.
Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy.
Nutrients. 2025 Jan 29;17(3):482. doi: 10.3390/nu17030482.
Existing resting energy expenditure (REE) predictive equations, including Mifflin-St Jeor and Harris-Benedict, show limited accuracy, particularly in patients with a BMI over 35, often leading to overestimation or underestimation of REE. This study aimed to develop a new predictive equation specifically designed to identify normometabolic status in patients with obesity, enabling more precise qualitative assessments of basal metabolism through indirect calorimetry. A cohort of 89 hospitalized patients with obesity (BMI > 30) underwent REE measurement and comprehensive anthropometric assessments. Patients were classified as normometabolic if their REE was within ±10% of the Mifflin-St Jeor prediction or if their fat-free mass-specific REE fell between 23 and 30 kcal/kg. The newly developed equation demonstrated high predictive accuracy (R = 0.923, root mean square error = 81.872 kcal/day), with a mean bias of -0.054 kcal/day and narrower limits of agreement (-156.834 to 156.725 kcal/day) compared to widely used models. These advancements could enhance follow-up and management of diet therapy in patients with obesity, allowing for a more tailored approach to their metabolic health over time.
现有的静息能量消耗（REE）预测方程，包括米夫林-圣乔尔方程和哈里斯-本尼迪克特方程，准确性有限，尤其是在体重指数（BMI）超过35的患者中，常常导致REE估计过高或过低。本研究旨在开发一种专门设计用于识别肥胖患者正常代谢状态的新预测方程，通过间接测热法对基础代谢进行更精确的定性评估。89名肥胖住院患者（BMI>30）接受了REE测量和全面的人体测量评估。如果患者的REE在米夫林-圣乔尔预测值的±10%以内，或者其去脂体重特异性REE在23至30千卡/千克之间，则被归类为正常代谢。新开发的方程显示出较高的预测准确性（R = 0.923，均方根误差 = 81.872千卡/天），与广泛使用的模型相比，平均偏差为-0.054千卡/天，一致性界限更窄（-156.834至156.725千卡/天）。这些进展可以加强肥胖患者饮食治疗的随访和管理，随着时间的推移，为他们的代谢健康提供更个性化的方法。
