Seok Joon Lee1, Hak-Jae Lee2, Yooun-Joong Jung2, Minkyu Han3, Sung-Gyu Lee4, Suk-Kyung Hong2. 1. College of Medicine, University of Ulsan, Songpa-gu, Seoul, South Korea. 2. Division of Acute Care Surgery, Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, Seoul, South Korea. 3. Department of Clinical Epidemiology and Biostatistics, University of Ulsan, Songpa-gu, Seoul, South Korea. 4. Division of Liver Transplantation and Hepatobiliary Surgery, Departments of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Abstract
BACKGROUND: To assess the appropriate energy expenditure requirement for liver transplant (LT) recipients in South Korea, 4 commonly used predictive equations were compared with indirect calorimetry (IC). METHODS: A prospective observational study was conducted in the surgical intensive care unit (ICU) of an academic tertiary hospital between December 2017 and September 2018. The study population comprised LT recipients expected to remain in the ICU >48 hours postoperatively. Resting energy expenditure (REE) was measured 48 hours after ICU admission using open-circuit IC. Theoretical REE was estimated using 4 predictive equations (simple weight-based equation [25 kcal/kg/day], Harris-Benedict, Ireton-Jones [ventilated], and Penn State 1988). Derived and measured REE values were compared using an intraclass correlation coefficient (ICC) and Bland-Altman plots. RESULTS: Of 50 patients screened, 46 were enrolled, were measured, and completed the study. The Penn State equation showed 65.0% agreement with IC (ICC, 0.65); the simple weight-based (25 kcal/kg/day), Harris-Benedict, and Ireton-Jones equations showed 62.0%, 56.0% and 39.0% agreement, respectively. Bland-Altman analysis showed that all 4 predictive equations had fixed bias, although the simple weight-based equation (25 kcal/kg/day) showed the least. CONCLUSION: Although predicted REE calculated using the Penn State method agreed with the measured REE, all 4 equations showed fixed bias and appeared to be inaccurate for predicting REE in LT recipients. Precise measurement using IC may be necessary when treating LT recipients to avoid underestimating or overestimating their metabolic needs.
BACKGROUND: To assess the appropriate energy expenditure requirement for liver transplant (LT) recipients in South Korea, 4 commonly used predictive equations were compared with indirect calorimetry (IC). METHODS: A prospective observational study was conducted in the surgical intensive care unit (ICU) of an academic tertiary hospital between December 2017 and September 2018. The study population comprised LT recipients expected to remain in the ICU >48 hours postoperatively. Resting energy expenditure (REE) was measured 48 hours after ICU admission using open-circuit IC. Theoretical REE was estimated using 4 predictive equations (simple weight-based equation [25 kcal/kg/day], Harris-Benedict, Ireton-Jones [ventilated], and Penn State 1988). Derived and measured REE values were compared using an intraclass correlation coefficient (ICC) and Bland-Altman plots. RESULTS: Of 50 patients screened, 46 were enrolled, were measured, and completed the study. The Penn State equation showed 65.0% agreement with IC (ICC, 0.65); the simple weight-based (25 kcal/kg/day), Harris-Benedict, and Ireton-Jones equations showed 62.0%, 56.0% and 39.0% agreement, respectively. Bland-Altman analysis showed that all 4 predictive equations had fixed bias, although the simple weight-based equation (25 kcal/kg/day) showed the least. CONCLUSION: Although predicted REE calculated using the Penn State method agreed with the measured REE, all 4 equations showed fixed bias and appeared to be inaccurate for predicting REE in LT recipients. Precise measurement using IC may be necessary when treating LT recipients to avoid underestimating or overestimating their metabolic needs.