J Am Soc Nephrol 15: 3134–3143, 2004 Resting Energy Expenditure and Subsequent Mortality Risk in Peritoneal Dialysis Patients

ANGELA YEE-MOON WANG,* MANDY MAN-MEI SEA,† NELSON TANG,‡ JOHN E. SANDERSON,* SIU-FAI LUI,* PHILIP KAM-TAO LI,* and JEAN WOO† *Department of Medicine & Therapeutics, †Center for Nutritional Studies, ‡Department of Chemical Pathology, Prince of Wales Hospital, Chinese University of Hong Kong, Shatin. N.T., Hong Kong

Abstract. Cardiovascular disease is the leading cause of death C-reactive protein (P ϭ 0.009). At 2 yr, the overall survival in ESRD patients and is strongly associated with malnutrition. was 63.3, 73.6, and 95.9% (P Ͻ 0.0001), and cardiovascular The mechanism of malnutrition is not clear, but hypermetab- event-free survival was 72.3, 84.6, and 97.2% (P ϭ 0.0003), olism is suggested to contribute to cardiac cachexia. This study respectively, for patients in the upper, middle, and lower ter- examined resting energy expenditure (REE) in relation to the tiles of REE. Adjusting for age, gender, diabetes, and cardio- clinical outcomes of ESRD patients who receive continuous vascular disease, patients in the upper and middle tertiles ambulatory peritoneal dialysis (CAPD) treatment. A prospec- showed a 4.19-fold (95% confidence interval, 2.15 to 8.16; P tive observational cohort study was performed in 251 CAPD Ͻ 0.001) and a 2.90-fold (95% confidence interval, 1.49, 5.63; patients. REE was measured at study baseline using indirect P ϭ 0.002) respective increase in the risk of all-cause mortality calorimetry together with other clinical, nutritional, and dialy- compared with those in the lower tertile. However, the signif- sis parameters. Patients were followed up for a mean Ϯ SD icance of REE in predicting mortality was gradually reduced duration of 28.7 Ϯ 14.3 mo. REE was 39.1 Ϯ 9.6 and 40.1 Ϯ when additional adjustment was made for C-reactive protein, 9.0 kcal/kg fat-free edema-free body mass per day for men and serum albumin, and residual GFR in a stepwise manner. In women, respectively (P ϭ 0.391). Using multiple regression conclusion, a higher REE is associated with increased mortal- analysis, fat-free edema-free body mass–adjusted REE was ity and cardiovascular death in CAPD patients and is partly negatively associated with residual GFR (P Ͻ 0.001) and related to its close correlations with residual kidney function, serum albumin (P ϭ 0.046) and positively associated with cardiovascular disease, inflammation, and malnutrition in these diabetes (P ϭ 0.002), cardiovascular disease (P ϭ 0.009), and patients.

Malnutrition is usually the consequence of energy imbalance and diseases such as AIDS (9), chronic obstructive pulmonary disease can be attributed to changes in dietary intake or energy expendi- (10), and malignancy (4), it is not known whether a higher resting ture or both. Sustained hypermetabolism can lead to energy im- energy expenditure (REE) is also a marker of inflammation or balance and wasting if not compensated for by an increase in malnutrition in ESRD patients, in whom high prevalence of these energy intake. Indeed, hypermetabolism was suggested to be one complications is observed. of the contributory factors for cachexia in disease states such as Studies that examined REE in patients with ESRD showed cardiac failure (1), chronic obstructive pulmonary disease (2), and conflicting data. Ikizler et al. (11) reported resting hypermetabo- malignancy (3,4). However, its association with protein-energy lism in chronic hemodialysis patients that was noted to increase malnutrition in ESRD patients has not been established. further during hemodialysis procedure. Recent study showed Protein-energy malnutrition is a significant complication and higher REE in patients who receive dialysis, regardless of the predicts mortality in ESRD patients (5,6). However, malnutrition modality, than chronic renal failure patients who did not yet is well known to be associated with inflammation and atheroscle- require dialysis (12). Conversely, other studies showed that REE rotic vascular disease in ESRD patients (7,8). Whereas the sever- of chronic renal failure patients were either reduced (13) or no ity of inflammation as denoted by the acute-phase response or different from normal control subjects (14,15). In this prospective proinflammatory cytokine is related to resting hypermetabolism in follow-up study, we evaluated factors associated with REE in a large cohort of ESRD patients who were receiving continuous ambulatory peritoneal dialysis (CAPD) therapy and determined Received May 27, 2004. Accepted August 17, 2004. whether a single measurement of REE is related to the clinical Correspondence to Dr. Angela Yee-Moon Wang, Department of Medicine & outcomes of these peritoneal dialysis (PD) patients. Therapeutics, Prince of Wales Hospital, Chinese University of Hong Kong, Shatin, N.T. Hong Kong. Phone: 852-2632-3023; Fax: 852-2637-5396; E- mail: [email protected] Materials and Methods 1046-6673/1512-3134 Study Population Journal of the American Society of Nephrology This study was approved by the Human Research Ethics Commit- Copyright © 2004 by the American Society of Nephrology tee of the Chinese University of Hong Kong. Altogether, 251 patients DOI: 10.1097/01.ASN.0000144206.29951.B2 who were receiving CAPD treatment for Ն3 mo were recruited from J Am Soc Nephrol 15: 3134–3143, 2004 Resting Metabolic Rate and Mortality 3135 the Prince of Wales Hospital in Hong Kong and represented 90% of was measured using the Tina-quant CRP (Latex) ultrasensitive assay the total PD patient pool in our hospital. The remaining 10% of (Roche Diagnostics GmbH, Mannheim, Germany). patients were excluded because of underlying malignancy; systemic inflammatory disease such as systemic lupus erythematosus, active Assessment of Indices of Dialysis Adequacy infections, chronic liver disease, or chronic obstructive airway dis- Patients were asked to bring back 24-h urine and dialysate on the Ͻ ease; or because they received PD treatment for 3 mo. Informed same day of assessing REE and SGA for measurement of urea and consent was obtained from all patients. At the time of study entry, creatinine production. Total weekly urea and creatinine clearance clinical and demographic information including time on dialysis be- were then calculated using standard methods (22). Contribution of fore enrollment into the study, smoking habits, underlying cause of urea clearance by PD was estimated separately. Residual GFR was renal failure, history of diabetes, and cardiovascular disease were calculated as the average of 24-h urine urea and creatinine clearance recorded. Cardiovascular disease was defined as the presence of (23). Creatinine concentration in dialysate was corrected for interfer- angina; previous myocardial infarction with or without angiographi- ence by glucose according to a reference formula determined in our cally confirmed coronary artery disease; history of coronary artery laboratory (24). Total body water was derived using Watson formula bypass surgery or stenting procedure; or history of congestive heart (25). Protein equivalent nitrogen appearance (PNA) was calculated by failure, cerebrovascular, disease, or peripheral vascular disease. Dry the method described by Randerson et al. (26). weight was measured to the nearest 0.1 kg by a weighing scale, with patients’ abdomen drained dry of peritoneal fluid. Body height was measured to the nearest 0.5 cm. Body mass index was calculated as Study Outcome weight in kilograms divided by height in meters squared. Patients were followed up prospectively to an end point of death, kidney transplant, or permanent transfer to hemodialysis after baseline assessment of REE. No patients were lost to follow-up. Patients who Measurement of REE underwent kidney transplantation or switched to permanent hemodialysis REE was measured by indirect calorimetry using DeltatracII, were censored at the time of transfer to alternative renal replacement MBM-200, Metabolic monitor (Datex, Helsinki, Finland) at study therapy. All deaths were recorded accurately with the exact cause of baseline. It was conducted under standardized conditions in the morn- death provided by the attending physician, who had no knowledge of the ing in all patients. Patients fasted overnight for at least 10 h, and all REE results. In the case of death out of hospital, family members were medications were omitted on the morning before undergoing indirect interviewed by telephone to ascertain the circumstances surrounding calorimetry. Patients were asked to avoid all strenuous exercise for at death. The primary end point was death from all causes, which is an least 12 h before the measurement of REE. On arrival, patients were objective, clinically relevant, and unbiased end point (27). Death from asked to lie down for a mandatory 15-min rest period. REE was then cardiovascular causes included death associated with a definite myocar- measured for ~30 min with patients lying supine at complete physical dial ischemic event, heart failure, arrhythmia, peripheral vascular acci- rest, alone and undisturbed in a quiet room. The REE was determined dent, and cerebrovascular accident, all of which were defined according from the rate of oxygen consumption and carbon dioxide production. to standard clinical criteria, and sudden death, which was defined as Readings from the first 5 min were discarded. An average was taken unexpected natural death within 1 h from the symptom onset and without from the subsequent readings of 25 min of steady state and was used any previous condition that would seem to be fatal (28,29). for the calculation of REE. The within-subject coefficient of variation of the REE measurement was 5.1%. REE was adjusted per kilogram Statistical Analyses of fat-free edema-free body mass or lean body mass (16). Continuous variables were tested for normal distribution with the Kolmogorov-Smirnov test before further statistical analysis. The as- sociations of fat-free edema-free body mass–adjusted REE with the Assessment of Nutrition Status and Degree different clinical and biochemical parameters were tested by the of Inflammation Spearman rank correlation analysis and multiple linear regression Fat-free, edema-free body mass or lean body mass was calculated analysis. The study cohort was stratified into tertiles according to the using creatinine kinetics. Total daily creatinine production was mea- fat-free edema-free–adjusted REE. The significance of differences sured as the sum of daily creatinine excreted in the dialysate and urine among tertiles was tested by the one-way ANOVA or Kruskal-Wallis plus the estimated daily creatinine lost in the gut (17). Fat-free or ␹2 test where appropriate. Post hoc analysis was performed by the edema-free body mass was then computed according to the following Bonferroni method. Characteristics of patients who remained alive equation (18,19): fat-free, edema-free body mass (kg) ϭ 0.029*total and those who died were compared by the unpaired t test, Mann- creatinine production in mg/d ϩ 7.38. Whitney test, or ␹2 test where appropriate. Survival curves of the three Subjective global assessment (SGA) was used to evaluate the tertiles were generated according to the Kaplan-Meier method and overall protein-energy nutritional status (20,21) and was performed by compared by the Mantel log-rank test. Factors with P Ͻ 0.25 on a single experienced research assistant who was blinded to other univariate analysis for all-cause and cardiovascular mortality were details of patients. It includes assessing the patient’s history of weight further considered in the multivariable Cox regression analysis. The loss, presence of anorexia and vomiting, and grading of muscle all-cause and cardiovascular mortality of patients in the upper and wasting and loss of subcutaneous fat. Edema is not used in grading of middle tertiles compared with that of the lower tertile (reference SGA, but its presence or absence has to be taken into account when group) were first tested controlling for covariates with P Ͻ 0.25 on assessing changes in body weight. On the basis of these assessments, univariate analysis (not including inflammation, malnutrition, and each patient was graded a score that reflected the nutrition status: 1 ϭ residual GFR; basic model). To examine whether inflammation, mal- normal nutrition, 2 ϭ mild malnutrition, 3 ϭ moderate malnutrition, nutrition, and residual renal function further modify the relationships and 4 ϭ severe malnutrition (21). Serum albumin and C-reactive between REE and all-cause and cardiovascular mortality, we made protein (CRP) were measured at the time of assessing REE and SGA. additional adjustments for inflammatory marker, CRP, nutritional Serum albumin was measured by the bromcresol purple method. CRP parameter, serum albumin, and residual GFR in a stepwise manner in 3136 Journal of the American Society of Nephrology J Am Soc Nephrol 15: 3134–3143, 2004 multivariable Cox regression models. Statistical analysis was per- PϽ 0.001) and residual GFR (r ϭϪ0.488, P Ͻ 0.001) but formed using SPSS software, version 10.0 (SPSS, Inc., Chicago, IL). positively correlated with CRP (r ϭ 0.266, P Ͻ 0.001). Pa- Ͻ P 0.05 was considered statistically significant. tients were stratified into tertiles according to the fat-free Results edema-free body mass–adjusted REE, namely those with REE Ͻ The baseline characteristics of study patients are presented 34.3 kcal/kg fat-free edema-free body mass per day (lower in Table 1. The mean Ϯ SD REE was 39.1 Ϯ 9.6 and 40.1 Ϯ tertile), those between 34.3 and 42.4 kcal/kg fat-free edema- 9.0 kcal/kg fat-free edema-free body mass per day for men and free body mass per day (middle tertile), and those Ն42.4 women, respectively (P ϭ 0.391). Using Spearman rank cor- kcal/kg fat-free edema-free body mass per day (upper tertile). relation analysis, fat-free edema-free body mass–adjusted REE Characteristics of study participants stratified in tertiles of REE was negatively correlated with serum albumin (r ϭϪ0.281, are shown in Table 1. Using multiple linear regression analy-

Table 1. Baseline characteristics according to tertiles of REEa

REE in Tertiles Total P (N ϭ 251) Lower Middle Upper (n ϭ 84) (n ϭ 83) (n ϭ 84) Demographic and clinical characteristics gender distribution (M/F) 130/121 48/36 43/40 39/45 0.381 age (yr) 55 Ϯ 12 53 Ϯ 13 57 Ϯ 11 56 Ϯ 11 0.046 Duration of dialysis (mo)b 26 (14–51) 22 (11–49) 26 (18–55) 32 (18–53)c 0.035 smoking status (n [%]) former smoker 62 (24.7) 22 (26.2) 18 (21.7)c 22 (26.2) 0.074 current smoker 30 (12) 4 (4.8) 16 (19.3) 10 (11.9) nonsmoker 159 (63.3) 58 (68) 49 (63) 52 (59) underlying renal diagnosis (n [%]) chronic glomerulonephritis 81 (32.3) 34 (40.5) 24 (28.9) 23 (27.4) 0.048 diabetic nephropathy 61 (24.3) 14 (16.7) 18 (21.7) 29 (34.5) hypertensive nephrosclerosis 34 (13.5) 15 (17.9) 10 (12.0) 9 (10.7) others 75 (29.9) 21 (25) 31 (37.3) 23 (27.4) diabetes (n [%]) 76 (30.3) 16 (19.0) 26 (31.3) 34 (40.5)d 0.010 presence of cardiovascular disease (n [%]) 110 (44.0) 29 (34.5) 29 (34.9)h 52 (61.9)e Ͻ0.001 systolic blood pressure (mmHg) 147 Ϯ 17 143 Ϯ 16 149 Ϯ 16c 148 Ϯ 18 0.032 diastolic blood pressure (mmHg) 82 Ϯ 10 82 Ϯ 983Ϯ 983Ϯ 11 0.664 pulse pressure (mmHg) 64 Ϯ 10 61 Ϯ 13 66 Ϯ 13c 66 Ϯ 14 0.033 Dialysis parameters total weekly urea clearance 1.81 Ϯ 0.46 1.99 Ϯ 0.53 1.79 Ϯ 0.41d 1.65 Ϯ 0.35e Ͻ0.001 peritoneal dialysis urea clearance 1.52 Ϯ 0.37 1.48 Ϯ 0.34 1.57 Ϯ 0.35 1.50 Ϯ 0.41 0.334 total weekly creatinine clearance 57 Ϯ 22 69 Ϯ 27 54 Ϯ 19e 47 Ϯ 10e Ͻ0.001 (L/wk per 1.73 m2) with residual renal function, (n [%]) 135 (54) 67 (80) 38 (46)e 30 (36)e Ͻ0.001 residual GFR (mL/min per 1.73 m2)b 0.63 (0–1.94) 1.77 (0.65–3.15) 0.29 (0–1.60)e 0 (0–0.82)e Ͻ0.001 Nutritional and biochemical parameters body weight (kg) 58.0 Ϯ 10.2 58.1 Ϯ 9.3 58.0 Ϯ 10.4 57.9 Ϯ 10.9 0.987 body height (m) 1.58 Ϯ 0.08 1.59 Ϯ 0.08 1.58 Ϯ 0.08 1.58 Ϯ 0.08 0.587 body mass index (kg/m2) 23.2 Ϯ 3.4 23.0 Ϯ 3.1 23.2 Ϯ 3.4 23.2 Ϯ 3.8 0.922 lean body mass by creatinine kinetics (kg) 32.0 Ϯ 7.6 37.6 Ϯ 7.6 31.0 Ϯ 5.7e,h 27.2 Ϯ 5.2e Ͻ0.001 PNA (g/kg body wt per day) 0.96 Ϯ 0.20 1.03 Ϯ 0.21 0.97 Ϯ 0.19g 0.89 Ϯ 0.17e Ͻ0.001 Subjective global assessment (n [%]) normal 140 (55.8) 56 (66.7) 45 (54.2) 39 (46.4)c 0.020 mild 69 (27.5) 21 (25.0) 25 (30.1) 23 (27.4) moderate/severe 42 (16.7) 7 (8.3) 13 (15.7) 22 (26.2) serum albumin (g/L) 28.5 Ϯ 5.1 30.0 Ϯ 4.9 28.4 Ϯ 4.2 27.5 Ϯ 5.7f 0.005 hemoglobin (g/dL) 9.23 Ϯ 1.69 9.49 Ϯ 1.61 9.52 Ϯ 1.71i 8.69 Ϯ 1.62d 0.001 CRP (mg/L)b 2.84 (0.92–9.09) 1.32 (0.61–3.54) 3.56 (0.95–10.95)c 4.22 (1.37–13.23)e Ͻ0.001 Ϯ Ϯ Ϯ c,h Ϯ e Ͻ VO2 (ml/min) 176 36 162 31 172 32 195 37 0.001 Ϯ Ϯ Ϯ h Ϯ e Ͻ VCO2 (ml/min) 155 31 141 29 153 27 170 30 0.001 a Data are mean Ϯ SD unless stated otherwise. Percentages may not add up to 100 because of rounding off of decimal places. REE, resting energy expenditure; PNA, protein equivalent nitrogen appearance; CRP, C-reactive proteine; VO2, rate of oxygen production; VCO2, rate of carbon dioxide production. b Median (interquartile range). c P Ͻ 0.05, d P Ͻ 0.01, e P Ͻ 0.001, f P Ͻ 0.005, versus lower tertile by Bonferroni post hoc test. g P Ͻ 0.05, h P Ͻ 0.001, i P Ͻ 0.005, middle versus upper tertile by Bonferroni post hoc test. J Am Soc Nephrol 15: 3134–3143, 2004 Resting Metabolic Rate and Mortality 3137

Table 2. Multiple regression analysis showing factors independently associated with REE in dialysis patientsa

Unstandardized Standardized 95% Confidence P Factors Coefficient, B Coefficient, ␤ Interval

Residual GFR (every 1 ml/min per 1.73 m2) Ϫ2.236 Ϫ0.418 Ϫ2.878 to Ϫ1.594 Ͻ0.001 Diabetes 3.907 0.195 1.428 to 6.385 0.002 Presence of cardiovascular disease 2.915 0.157 0.730 to 5.100 0.009 CRP (every 1-mg/L increase) 0.104 0.151 0.026 to 0.181 0.009 Serum albumin (every 1-g/L increase) Ϫ0.213 Ϫ0.117 Ϫ0.422 to Ϫ0.004 0.046

Multiple R ϭ 0.573, P Ͻ 0.001. Out of the model with age (P ϭ 0.260), gender (P ϭ 0.247), duration of dialysis (P ϭ 0.484), hemoglobin (P ϭ 0.839), systolic blood pressure (P ϭ 0.939), and diastolic blood pressure (P ϭ 0.112). sis,residual GFR, diabetes, cardiovascular disease, serum albu- mortality in CAPD patients are detailed in Tables 5 and 6. min, and CRP were independent factors associated with fat- Adjusting for covariates including age, male gender, diabetes, free edema-free body mass–adjusted REE (Table 2). and cardiovascular disease (basic model, Table 5), patients in Our study cohort was followed for a mean duration of 28.7 the upper and middle tertiles had 4.19-fold (95% confidence (SD, 14.3) months after baseline assessment of REE. During interval [CI], 2.15 to 8.16) and 2.90-fold (95% CI, 1.49 to 5.63) the follow-up period, 47 men and 40 women died. Twenty- increased risk of all-cause mortality than those in the lower eight (11.2%) patients were transferred to long-term hemodi- tertile, respectively. However, the significance of REE in pre- alysis, and 31 (12.4%) patients underwent kidney transplanta- dicting all-cause mortality was gradually reduced when addi- tion. Excluding patients who underwent kidney transplantation tional adjustments were made for inflammatory marker CRP, and those who were permanently transferred to hemodialysis (n nutritional marker serum albumin. and residual GFR in a ϭ 59), we compared the baseline characteristics of patients stepwise manner in the multivariable Cox regression models who survived (n ϭ 105) versus those who died (n ϭ 87) during (models 1 to 3, Table 5). follow-up (Table 3). The nonsurvivors were older (P Ͻ 0.001), Table 6 shows the risk of cardiovascular mortality in relation were dialyzed for longer (P ϭ 0.051), had greater prevalence to the REE. Adjusting for age, diabetes, and cardiovascular ϭ ϭ of diabetes (P 0.030) and cardiovascular disease (P disease, patients in the upper tertile of REE had a 3.01-fold ϭ 0.001), had lower total weekly urea (P 0.015) and creatinine (95% CI, 1.43 to 6.35) higher risk of cardiovascular mortality ϭ ϭ clearance (P 0.017), and had lower residual GFR (P than those in the lower tertile (basic model, Table 6). However, 0.003). The nonsurvivors were more malnourished according the significance of REE was gradually lost in a stepwise ϭ to a number of nutrition indices, including SGA (P 0.002), manner when additionally adjusting for CRP, serum albumin, ϭ fat-free edema-free body mass (P 0.002), and serum albumin and residual GFR in multivariable Cox regression models Ͻ (P 0.001). They also showed more inflammation as denoted (models 1 to 3, Table 6). by higher CRP (P Ͻ 0.001) and had higher fat-free edema-free body mass–adjusted REE (P Ͻ 0.001) than the survivors. Causes of death of our study cohort are shown in Table 4. Discussion Cardiovascular causes accounted for 63% of all deaths, fol- The effects of energy metabolism on the clinical outcomes lowed by peritonitis in 14%, other infections or sepsis in 14%, were previously explored in different disease states, but results and other miscellaneous causes in 9%. Six patients died outside so far remained inconclusive. Whereas some studies suggested the hospital, and all of them had sudden cardiac death. The that hypermetabolism was associated with decreased survival overall mortality during the follow-up period was 47.6 and in cancer patients (3), others observed longer survival in hy- 42.2%, respectively, for patients in the upper and middle permetabolic patients (30). In this prospective study, we pro- tertiles compared with 14.3% for the lower tertile (P Ͻ 0.001). vide important evidence that a higher REE is associated with Death from cardiovascular causes was 33.3% for patients in the greater mortality and cardiovascular death in ESRD patients on upper tertile compared with 20.5 and 11.9% for patients in the CAPD. This extends further the observations from a previous middle and lower tertiles, respectively (P Ͻ 0.001). The over- study showing that an elevated REE is predictive of future all survival and cardiovascular event-free survival of patients mortality in apparently healthy humans (31). Although the in the three tertiles are illustrated in the Kaplan-Meier curves in exact mechanism for the association between REE and mor- Figure 1. At 2 yr, the overall survival was 63.3, 73.6, and tality remains to be elucidated, our current study provides 95.9% for patients in the upper, middle, and lower tertiles, important evidence that loss of residual renal function, cardio- respectively (P Ͻ 0.0001). Cardiovascular event-free survival vascular disease, inflammation, and malnutrition, all well- was 72.3, 84.6, and 97.2% for patients in the upper, middle, known predictors for mortality, show significant and indepen- and lower tertiles, respectively (P ϭ 0.0003). dent associations with higher REE, indicating that loss of Univariate analysis results for all-cause and cardiovascular residual kidney function, cardiovascular disease, malnutrition, 3138 Journal of the American Society of Nephrology J Am Soc Nephrol 15: 3134–3143, 2004

Table 3. Characteristics of survivors on PD versus nonsurvivorsa

Survivors on PD Nonsurvivors P (n ϭ 105) (n ϭ 87)

Age (yr) 54 Ϯ 12 61 Ϯ 10 Ͻ0.001 Male gender (n [%]) 50 (47.6) 47 (54.0) 0.377 Months on dialysisb 23 (13–48) 31 (15–50) 0.051 Body mass index (kg/m2) 23.0 Ϯ 3.3 23.1 Ϯ 3.7 0.850 Positive smoking history (n [%]) 35 (33.3) 37 (42.5) 0.190 Diabetes (n [%]) 29 (27.6) 37 (42.5) 0.030 Renal diagnosis (n [%]) chronic glomerulonephritis 37 (35.2) 18 (20.7) 0.030 diabetic nephropathy 22 (21.0) 33 (37.9) hypertensive nephropathy 14 (13.3) 12 (13.8) other 32 (30.5) 24 (27.6) Presence of cardiovascular disease (n [%]) 37 (35.2) 51 (58.6) 0.001 Receiving erythropoietin treatment (n [%]) 38 (36.2) 31 (35.6) 0.916 Total weekly urea clearance 1.87 Ϯ 0.44 1.72 Ϯ 0.42 0.015 Weekly peritoneal dialysis urea clearance 1.55 Ϯ 0.37 1.51 Ϯ 0.39 0.570 Total weekly creatinine clearance (L/wk per 1.73 m2) 59 Ϯ 23 52 Ϯ 17 0.017 Residual GFR (mL/min per 1.73 m2)b 0.84 (0–2.03) 0 (0–1.29) 0.003 Nutrition status according to SGA (n [%]) well nourished 70 (66.7) 37 (42.5) 0.002 mild malnutrition 23 (21.9) 27 (31.0) moderate and severe malnutrition 12 (11.4) 23 (26.4) Fat-free edema-free body mass (kg) 32.7 Ϯ 7.9 29.5 Ϯ 6.0 0.002 Hemoglobin (g/dl) 9.38 Ϯ 1.59 9.15 Ϯ 1.81 0.369 Serum albumin (g/L) 29.7 Ϯ 4.7 26.7 Ϯ 4.5 Ͻ0.001 CRP (mg/L)b 1.51 (0.65–5.18) 5.32 (2.07–12.71) Ͻ0.001 REE (kcal/kg fat-free edema-free body mass per day) 37.4 Ϯ 8.8 43.3 Ϯ 9.2 Ͻ0.001

a Data are mean Ϯ SD unless stated otherwise. SGA, subjective global assessment. b Median (interquartile range). and inflammation might have an important contribution to the presence of higher REE is matched by a greater degree of association between REE and mortality in dialysis patients. inflammatory activity and well accords with studies showing Previous studies showed that REE is increased in patients an important association between resting hypermetabolism and with heart failure (1,32) and that the clinical severity of heart chronic immune activation in diseases such as chronic obstruc- failure as reflected by the New York Heart Association clas- tive pulmonary disease (10) and malignancy (4,38). Although sification corresponds to the magnitude of increase in resting the exact dynamic relationships between inflammation and energy demand (33). This well accords with our study showing resting hypermetabolism remains poorly understood, studies in also an independent positive association between cardiovascu- both animals (39,40) and humans (41,42) indicated that exces- lar disease and higher REE. The higher systolic and pulse sive production of proinflammatory cytokines was linked to pressure across the three tertiles of increasing REE are addi- hypermetabolism and loss of body cell mass. tional evidence to indicate an elevated REE in patients with REE accounts for 60 to 80% of the total energy expenditure. underlying cardiovascular abnormality. The exact mechanism Hence, its increase contributes significantly to the development for this association is not clear, but increased myocardial of cachexia and is indeed observed in patients with heart failure oxygen consumption and increased metabolic cost of breathing (1,32) and in the elderly (43). In this study, patients with higher have been suggested as contributing factors to resting hyper- REE were not only more inflamed but also clinically more metabolism in patients with cardiovascular disease (1,34). In- malnourished according to a number of different nutrition creased circulating tumor necrosis factor are noted in cachectic indices. Furthermore, the association between REE and mor- heart failure patients (35), but their relation to alteration in tality was partly reduced after adjusting for nutrition indices energy metabolism remains speculative. Inflammation is a and inflammatory marker, suggesting that the association be- powerful predictor of mortality in ESRD patients who are on tween REE and mortality may in part be related to malnutrition maintenance dialysis (36,37). A previous study also showed an and inflammation. Taken together, our results suggest that a important link among cardiovascular disease, inflammation, higher REE should be considered as an important component and malnutrition in ESRD patients (7). In this study, the of the malnutrition-inflammation syndrome that frequently ac- J Am Soc Nephrol 15: 3134–3143, 2004 Resting Metabolic Rate and Mortality 3139

Table 4. Clinical outcomes of study participants according to REE at baselinea

REE in Tertiles Total (N ϭ 251) Lower Middle Upper (n ϭ 84) (n ϭ 83) (n ϭ 84)

Outcome (n [%]) died 87 (34.7) 12 (14.3) 35 (42.2) 40 (47.6) alive on peritoneal dialysis 105 (41.8) 47 (56.0) 32 (38.5) 26 (31.0) transferred to hemodialysis 28 (11.2) 10 (11.9) 8 (9.6) 10 (11.9) received transplant 31 (12.4) 15 (17.9) 8 (9.6) 8 (9.5) Causes of death (n [%]) cardiovascular deaths 55 (21.9) 10 (11.9) 17 (20.5) 28 (33.3) ischemic heart disease 6 (2.4) 0 (0) 3 (3.6) 3 (3.6) heart failure 4 (1.6) 1 (1.2) 0 (0) 3 (3.6) sudden death 26 (10.4) 6 (7.1) 6 (7.2) 14 (16.7) arrhythmia/peripheral vascular disease 6 (2.4) 0 (0) 3 (3.6) 3 (3.6) ischemic or hemorrhage stroke 13 (5.2) 3 (3.6) 5 (6.0) 5 (6.0) noncardiovascular deaths 32 (12.7) 2 (2.4) 18 (21.7) 12 (14.3) peritonitis 12 (4.8) 1 (1.2) 5 (6.0) 6 (7.1) other infections or sepsis 12 (4.8) 1 (1.2) 8 (9.6) 3 (3.6) other miscellaneous causes 8 (3.2) 0 (0) 5 (6.0) 3 (3.6)

a Percentages may not add up to 100 because of rounding off of decimal places. companies ESRD patients with underlying cardiovascular dialysis patients, and the REE increased further during the disease. hemodialysis procedure (11). In this study, no significant dif- One key and novel finding of this study is the significant ference was observed in the PD clearance across the three negative association between REE and residual renal function tertiles of increasing REE, giving evidence that the loss in in patients who are on CAPD. The kidneys, in healthy indi- residual renal function but not changes in the dialysis clearance viduals, may account for up to 20% of REE. Hence, functional contributes to the increased REE of our patients. Study has also alteration of the kidney may lead to disturbance in energy showed no effect of intra-abdominal fluid on the REE (49). metabolism. However, the status of energy expenditure in renal Residual renal function has been shown to contribute sig- failure has remained controversial. Whereas some experimen- nificantly to the overall nutrition status of PD patients (50). tal studies suggested that both acute and chronic renal failure However, recent study also observed an increased inflamma- was associated with hypometabolism (44,45), another study tory activity with a decline in residual renal function (51,52). noted either hypermetabolism in patients with acute renal fail- Together with the current observation of higher REE among ure (46) or energy metabolism that was no different from patients with lower residual renal function, this suggests that a normal (14,15). Two other recent studies that examined the greater REE and inflammation are associated phenomena and resting metabolic rate in relation to renal function have also parallel the decline in residual renal function. The greater yielded conflicting data. One study suggested a decrease in resting metabolic state and associated inflammation might also REE with decline in renal function and was assumed to occur contribute to a greater degree of malnutrition observed in as a result of decreased oxygen consumption of the kidneys anuric patients. Generally speaking, a greater lean body mass (47), whereas the other study showed normal REE with dete- should be associated with a higher REE. However, in this riorating excretory function of the kidneys, suggesting an in- study, we observed an inverse relationship between lean body crease in energy expenditure per body cell mass (48). Our mass and REE. In other words, patients with greater REE had current study indicates that despite loss of excretory function, lower lean body mass. This suggests that some lean body mass the kidneys in ESRD patients may retain important metabolic loss may develop in response to the higher REE, greater functions as evidenced by the strong and negative correlation inflammation, or loss of residual renal function as supported by between the degree of residual renal function and REE. Fur- the positive correlations between REE and CRP and its nega- thermore, the significance of REE in predicting all-cause mor- tive correlations with serum albumin and residual renal func- tality was substantially reduced and its significance in predict- tion. We also studied whether the association between REE ing cardiovascular mortality was virtually lost after also and lean body mass was influenced by the vintage of dialysis adjusting for residual renal function. This suggests that the by testing for the lean body mass ϫ vintage interaction term. association between higher REE and higher mortality in CAPD Lean body mass showed no significant interaction with vintage patients is indeed partly related to the loss of residual renal of dialysis in relation to the REE (P ϭ 0.817). This indicates function. A previous study demonstrated higher REE in hemo- that the association between lean body mass and REE was not 3140 Journal of the American Society of Nephrology J Am Soc Nephrol 15: 3134–3143, 2004 0.006 0.001 0.039 0.058 0.016 0.418 0.134 0.001 0.007 ϭ ϭ ϭ ϭ ϭ ϭ ϭ ϭ ϭ P P P P P P P P P Model 3 (Adding Residual GFR) a 0.009 0.93 (0.88–0.98), 0.005 1.02 (1.01–1.03), 0.001 2.16 (1.04–4.48), 0.006 1.94 (0.98–3.86), 0.030 1.83 (1.12–3.01), 0.774 1.22 (0.76–1.96), 0.275 1.41 (0.90–2.22), 0.001 1.04 (1.02–1.07), ϭ ϭ Ͻ ϭ ϭ ϭ ϭ ϭ P P P P P P P P Model 2 (Adding Serum Albumin) 0.003 1.02 (1.01–1.03), 0.001 3.38 (1.71–6.67), 0.003 2.55 (1.31–4.97), 0.004 1.75 (1.05–2.90), 0.963 1.07 (0.67–1.73), 0.259 1.28 (0.82–2.01), 0.001 1.04 (1.02–1.07), ϭ Ͻ ϭ ϭ ϭ ϭ Ͻ P P P P P P P Multivariable Cox Regression Analysis Model 1 (Adding CRP)

Figure 1. Kaplan-Meier estimates of overall survival (A) and cardio- vascular event-free survival (B) of the study population in relation to tertiles of fat-free edema-free body mass–adjusted resting energy 0.001 3.89 (1.99–7.60), 0.002 2.75 (1.42–5.34), 0.005 2.04 (1.26–3.31), 0.793 1.01 (0.63–1.62), 0.344 1.29 (0.83–2.01), 0.001 1.05 (1.02–1.07), expenditure (REE). Tertiles of adjusted REE: lower ϭ 16.4 to 34.3 Ͻ ϭ ϭ ϭ ϭ Ͻ P P P P P kcal/kg fat-free edema-free body mass per day; middle ϭ 34.3 to P 42.3 kcal/kg fat-free edema-free body mass per day; upper ϭ 42.4 to 74.7 kcal/kg fat-free edema-free body mass per day. Log-rank test

showed significant difference in overall survival between lower and Basic Model middle tertiles (P ϭ 0.0001) and between lower and upper tertiles (P Ͻ 0.0001) but not between middle and upper tertiles (P ϭ 0.1692). Cardiovascular event-free survival showed significant difference be- tween lower and upper tertiles (P ϭ 0.0001) and between middle and upper tertiles (P ϭ 0.0264) but not between lower and middle tertiles 0.001 — — 0.93 (0.88–0.98), 0.001 — 1.02 (1.01–1.03), 0.001 4.19 (2.15–8.16), 0.001 2.90 (1.49–5.63), 0.001 1.97 (1.22–3.18), 0.007 0.94 (0.59–1.50), 0.227 1.24 (0.80–1.91), 0.659 — — — — 0.001 1.05 (1.03–1.08), (P ϭ 0.0791). 0.003 — — — 0.77 (0.64–0.93), Ͻ Ͻ Ͻ Ͻ Ͻ ϭ ϭ ϭ Ͻ ϭ P P P P P P P P P P related to dialysis vintage. It is important to caution that the associations observed with REE are cross-sectional. Serial measurements of REE with changes in lean body mass will be Univariate Analysis 0.89 (0.85–0.93), 1.03 (1.02–1.04), 4.63 (2.43–8.83), 3.33 (1.73–6.43), 0.88 (0.51–1.54), needed to evaluate a possible causal link between REE and 0.77 (0.64–0.91), lean body mass. Higher REE was observed in diabetic PD patients. This is in keeping with previous studies showing that ) patients with poorly controlled diabetes have enhanced REE 2 (53,54) and that the REE is reduced after glucose control is versus improved (55). Insulin deficiency or hyperglucagonemia is versus suggested as the underlying mechanism that promotes an in- Risk of all-cause mortality in relation to REE in univariate and multivariable Cox regression analysis in peritoneal dialysis patients Increase) crease in REE by increasing the rate of gluconeogenesis, a high min per 1.73 m albumin (1 g/L) mg/L) lower tertile) lower tertile) V (1 unit/wk) Variables (Units of Mortality risk expressed as hazards ratio (95% confidence interval).

energy-consuming process (56,57). a Residual GFR (1 ml/ Malnutrition—serum Inflammation—CRP (1 REE (upper REE (middle Cardiovascular disease 2.25 (1.46–3.46), Diabetes 1.79 (1.17–2.74), Male gender 1.30 (0.85–1.98), Peritoneal dialysis Kt/ Age (1 yr) 1.05 (1.03–1.08),

Some limitations of this study are noteworthy. In this study, Table 5. J Am Soc Nephrol 15: 3134–3143, 2004 Resting Metabolic Rate and Mortality 3141

prevalent but not incident patients were included and may introduce survival bias. Moreover, a single measurement of 0.204 0.032 0.210 0.770 0.005 0.187 0.001 0.055 REE was done at study baseline and may not reflect changes ϭ ϭ ϭ ϭ ϭ ϭ ϭ ϭ P P P P P P P P over long periods. Serial evaluations of REE with changes observed in sequence with changes in CRP and albumin may be more useful in establishing the association more strongly Model 3

a and may even generate new, important hypotheses. Further- more, only patients who were on PD treatment were studied as

(Adding Residual GFR) it accounts Ͼ75% of the dialysis population in Hong Kong. Whether our results are also applicable to hemodialysis or predialysis chronic renal failure patients requires further 0.265 0.96 (0.89–1.02), 0.060 1.02 (1.00–1.04), 0.014 1.72 (0.74–3.98), 0.327 1.13 (0.49–2.59), 0.007 2.52 (1.33–4.79), 0.364 1.49 (0.83–2.68), 0.002 1.05 (1.02–1.08), investigation. ϭ ϭ ϭ ϭ ϭ ϭ ϭ Our results have several potentially important implications. P P P P P P P First, the finding that a higher REE shows important associa- tions with residual renal function, inflammation, malnutrition,

Model 2 and cardiovascular disease and contributes to greater mortality and cardiovascular death in CAPD patients may expand its clinical usefulness. Regular monitoring of REE may be useful

(Adding Serum Albumin) in identifying patients who are at increased risk for mortality and morbidity for earlier active intervention. Second, given that loss of residual renal function, cardiovascular disease, 0.050 1.02 (1.00–1.03), 0.006 2.62 (1.22–5.63), 0.267 1.49 (0.67–3.30), 0.002 2.47 (1.28–4.74), 0.426 1.31 (0.73–2.35), 0.001 1.05 (1.02–1.08), inflammation, and malnutrition all are important associates of ϭ ϭ ϭ ϭ ϭ ϭ a greater resting metabolic state, it raises an important question P P P P P P as to whether early identification of PD patients with higher REE for additional energy supplementation may prevent mal- Multivariable Cox Regression Analysis Model 1 nutrition and possibly reduce morbidity and mortality in this (Adding CRP) population. Further study is needed to elucidate the exact mechanistic links between loss of residual renal function, car- diovascular disease, inflammation, and malnutrition and greater REE in PD patients. 0.004 2.88 (1.36–6.07), 0.232 1.56 (0.71–3.45), 0.002 2.70 (1.44–4.05), 0.533 1.27 (0.71–2.26), 0.001 1.05 (1.02–1.08), ϭ ϭ ϭ ϭ Ͻ Acknowledgments P P P P P This study was supported by the Bristol Myers Squibb Unrestricted ———— ———— Nutrition Grant Program and the Hong Kong Health Service Research Fund. Basic Model References 1. Riley M, Elborn JS, McKane WR, Bell N, Stanford CF, Nicholls DP: Resting energy expenditure in chronic cardiac failure. Clin Sci 80: 633–639, 1991 0.001 — — 0.96 (0.90–1.03), 0.003 — 1.02 (1.00–1.03), 0.001 3.01 (1.43–6.35), 0.093 1.62 (0.73–3.58), 0.001 2.70 (1.44–5.06), 0.001 1.20 (0.67–2.14), 0.429 0.443 0.038 — — — 0.80 (0.64–1.01), 0.001 1.06 (1.03–1.09), 2. Congleton J: The pulmonary cachexia syndrome: Aspects of ϭ ϭ Ͻ ϭ Ͻ ϭ ϭ ϭ ϭ Ͻ energy balance. Proc Nutr Soc 58: 321–328, 1999 P P P P P P P P P P 3. Bosaeus I, Daneryd P, Lundholm K: Dietary intake, resting energy expenditure, weight loss and survival in cancer patients. J Nutr 132[Suppl]: 3465S–3466S, 2002 4. Falconer JS, Fearon KC, Plester CE, Ross JA, Carter DC: Cy-

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