New resting energy expenditure prediction equations for patients with rheumatoid arthritis

Objectives. Resting energy expenditure (REE), one of the main components of total energy expenditure, can be measured via indirect calorimetry and/or predicted from equations. The latter may be misleading in RA, as they do not take into account the metabolic alterations occurring in RA. The objectives of this study are to evaluate the accuracy of widely used REE-predictive equations in RA patients against measured REE and to develop PA-specific equations. Methods. We assessed REE (via indirect calorimetry and several predictive equations), fat-free mass (FFM; via bioelectrical impedance) and disease activity (CRP) in RA pat:ants and healthy controls. Data from 30 RA patients (experimental group) were used to assess the accuracy of existing REE equations Find to develop new equations. The new equations were validated in an independent cross-validation group of 22 RA patients. These two groups were merged ani two final equations ware developed. Results. All equations significantly under-predicted measured PEE (from 15% to 18.2%, all at P < 0.091) in the RA experimental group, but not in the control group. After both equations demonstrated a high validity in the cross-validation croup, the new final REE prediction equations developed from the total RA sample (n=82) were: Model 1: REE (kcal/day) = 126.1 x FFM0.638 x CRP0.045 (R-2 = 0.70) and Model 2: REE (kcal/day) = 598.8 x weight 0.47 x age(-029) x CRP0.066 (R-2 = 0.62). Conclusion. The now equations provide an accurate prediction of REE in RA patients and could be used for clinical monitoring of resting metabolism of these patients without the requirement for specialized personnel.