Resting energy expenditure based on equation estimation can predict renal outcomes in patients with type 2 diabetes mellitus and biopsy-proven diabetic kidney disease.

Aims: The aim of this study was to investigate the relationship between resting energy expenditure (REE) based on equation estimation and renal outcomes in patients with diabetes kidney disease (DKD).

Methods: A total of 124 patients were enrolled from a retrospective cohort of Type 2 Diabetes mellitus (T2DM) patients with biopsy-proven DKD. Renal outcome defined as End-Stage Renal Disease (ESRD). To compare the predictive ability of different REE estimation equations on ESRD. Patients' REE was assessed according to the estimating equation with the best predictive power, and then the relationship between REE and ESRD risk was fitted using a restricted cubic spline curve (RCS) plot and REE cutoff values were obtained. Grouping using cutoff values, and ultimately evaluate the relationship between REE and the risk of ESRD using a Multivariate Cox regression model.

Results: The strongest predictive validity for renal outcomes was the NDCKD-equation. The patients were divided into the higher-REE group ( = 78) and the lower-REE group ( = 46), based on the cutoff value. During the follow-up, 30 of 124 patients (24.2%) proceeded to ESRD. Multivariate Cox regression models showed that the risk of ESRD in patients with lower REE was 6.08 times increased compared with that in those with higher REE (HR = 6.08; 95% CI, 1.28-28.80,  = 0.023).

Conclusion: These findings suggested that the lower REE was an independent risk factor for unfavorable renal outcomes in patients with DKD.