WOLVERHAMPTON, UK—Easy-to-implement new resting energy expenditure (REE) equations that take rheumatoid arthritis (RA)-induced hypermetabolism into account may help better monitor resting metabolism in RA patients without relying on sophisticated, time-consuming, and expensive indirect calorimetry, according to a new report published online in Rheumatology.¹

"This may help improve the management of these patients with nutritional support particularly in prolonged disease flares, during which increased protein intake may counterbalance protein catabolism, restore the equilibrium between energy intake and expenditure, and possibly reduce the chances of increased fat deposition, which may be important in the high context of high cardiovascular morbidity and mortality associated with RA," conclude researchers led by George S. Metsios, at the University of Wolverhampton in the UK.

RA-specific equations allow for easier, more accurate monitoring

Current predictive equations can be misleading in RA because they do not take into account the metabolic alterations occurring in this autoimmune disease. REE is higher in RA patients than their RA-free counterparts due to the excessive production of inflammatory cytokines; the new equations factor in these differences.

Researchers assessed REE via indirect calorimetry and several predictive equations. They measured fat-free mass via bioelectrical impedance and disease activity using C-reactive protein (CRP) in RA patients and healthy controls. They relied on data from 60 RA patients to assess the accuracy of existing REE equations and to develop new equations, which were confirmed in an independent cross-validation group of 22 RA patients. The two RA groups were merged and the new final REE prediction equations developed from the total RA sample were

Model 1: REE (kcal/day) = 126.1 x FFM^0.638 x CRP^0.045 (R² = .70)
Model 2: REE (kcal/day) = 598.8 x weight^0.47 x age^-0.29 x CRP^0.066 (R² = .62).

Existing equations significantly underpredicted measured REE ranging from 15% to 18.2% (all P <.001) in the RA experimental group, but not in the controls.

"The RA-specific equations developed in the present study are accurate and valid (even when disease activity changes) and display a much improved REE prediction power," the researchers conclude. "These equations could be used for continuous clinical monitoring of RAA without a requirement for specialized equipment/personnel."

Reference

1. Metsios GS, Stavropoulos0, Kalinoglou A, et al. New resting energy expenditure prediction equations for patients with rheumatoid arthritis. Rheumatology. [published online ahead of print March 15, 2008]. 2008; doi:10.1093/rheumatology/ken022. http://rheumatology.oxfordjournals.org/cgi/content/abstract/ken022v2.