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Body Mass Index, Left Ventricular Mass Index and Cardiovascular Events in Chronic Kidney Disease
CLINICAL INVESTIGATION
Body Mass Index, Left Ventricular Mass Index and Cardiovascular Events in Chronic Kidney Disease Szu-Chia Chen, MD, Jiun-Chi Huang, MD, Yi-Chun Tsai, MD, Ling-I Chen, MD, Ho-Ming Su, MD, Jer-Ming Chang, MD, PhD and Hung-Chun Chen, MD, PhD ABSTRACT Background: Obesity and left ventricular hypertrophy are prevalent in chronic kidney disease (CKD), but the association of body mass index (BMI) and left ventricular mass index (LVMI) with cardiovascular outcomes in patients with CKD is unclear. This study was designed to assess whether the combination of BMI and LVMI is independently associated with cardiovascular events in patients with CKD stages 3-5. Methods: From the outpatient department, 523 patients with CKD who received echocardiographic examination were enrolled. The patients under study were classified into 4 groups according to sex-specific median BMIs and LVMIs. Cardiovascular events were defined as cardiovascular death, hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, hospitalization for congestive heart failure, transient ischemia attack and stroke. The relative cardiovascular event risk was analyzed using Cox-regression methods. Results: The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVMIs (men: 140.1 g/m2; women: 131.6 g/m2). A combination of low BMI and high LVMI (versus the combination of high BMI and low LVMI) was significantly associated with cardiovascular events in an unadjusted model (hazard ratio [HR] ¼ 3.178; 95% confidence interval [CI]: 1.645-6.140; P o 0.001) and in a multivariable model after adjustment for demographic, clinical and biochemical characteristics and medications (HR ¼ 3.553; 95% CI: 1.494-8.450; P ¼ 0.004). Conclusions: The findings showed that the combination of low BMI and high LVMI was associated with adverse cardiovascular events in patients with CKD stages 3–5. Key Indexing Terms: Cardiovascular events; Chronic kidney disease; Body mass index; Left ventricular mass index. [Am J Med Sci 2016;351(1):91–96.]
INTRODUCTION
O
besity has reached epidemic proportions in the developed world1 and has increased the risk of cardiovascular disease–related mortality in the general population.2,3 In contrast to the general population, obesity appears to be associated with better survival in patients undergoing hemodialysis.4 However, published data on the relationship between obesity and cardiovascular morbidity and mortality in chronic kidney disease (CKD) are limited and inconsistent. Among studies related to obesity and mortality, one study reported that high body mass index (BMI) was associated with an increased risk of coronary artery disease,5 another study failed to identify BMI as a prognostic factor,6 whereas a third study suggested that a reverse association exists between obesity and mortality in patients with CKD.7,8 Thus, the status of obesity as a risk factor for adverse cardiovascular events in patients with CKD remains controversial. An increased BMI was affected by or linked to various risk factors for left ventricular hypertrophy
(LVH), such as obesity, insulin resistance, metabolic syndrome and hypertension.9–11 Rider et al10 positively associated BMI with LVH detected using echocardiography. LVH was also frequently encountered in patients with CKD because of pressure and volume overload.12,13 Furthermore, recent study involving patients with CKD stages 3-5 demonstrated that an increased left ventricular mass index (LVMI) was independently associated with adverse cardiovascular outcomes.14 CKD is an increasing worldwide public health problem associated with increased morbidity and mortality. Cardiovascular disease is the leading cause of morbidity and mortality in patients with CKD.15,16 No studies have evaluated the association between the combination of BMI and LVMI and cardiovascular outcome in patients with CKD. Therefore, the aim of this study was to assess whether the combination of BMI and LVMI is associated with cardiovascular events in patients with CKD stages 3–5.
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STUDY PATIENTS AND METHODS Study Patients and Design This study was conducted in a regional hospital in Southern Taiwan. The study consecutively recruited 523 patients with CKD stages 3–5, who had underwent predialysis, according to the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines,17 from January 2007-May 2010. The study classified patients with evidence of kidney damage lasting longer than 3 months into CKD stages 3a, 3b, 4 and 5, based on estimated glomerular filtration rates (eGFRs) of 45–59, 30–44, 15–29 and o15 mL/min/ 1.73 m2, respectively. The study patients were followedup regularly at the Outpatient Department of Internal Medicine. They were selected to participate in this study if they agreed to receive echocardiographic examination. A total of 3 patients refused echocardiographic examinations because of personal reasons. A total of 10 patients with significant mitral and aortic valve diseases and 5 other patients with inadequate image visualization were also excluded. Finally, 505 patients were included. The protocol was approved by the Institutional Review Board and enrolled patients gave written, informed consents. Evaluation of Cardiac Structure and Function The echocardiographic examination was performed by an experienced cardiologist using a VIVID 7 (General Electric Medical Systems, Horten, Norway), with the participant respiring quietly in the left decubitus position. The cardiologist was blinded to the other data. Twodimensional and 2-dimensionally–guided M-mode images were recorded in the standardized views. The echocardiographic measurements included the left ventricular internal diameter in diastole (LVIDd), left ventricular posterior wall thickness in diastole (LVPWTd), interventricular septal wall thickness in diastole (IVSTd), E-wave deceleration time, transmitral E-wave velocity and transmitral A-wave velocity. The left ventricular ejection fraction was measured using the modified Simpson's method. Impaired left ventricular systolic function was defined as left ventricular ejection fraction o50%. The left ventricular relative wall thickness was calculated as the ratio of 2 LVPWTd/LVIDd. The left ventricular mass (LVM) was calculated using Devereuxmodified method (ie, LVM ¼ 1.04 [(IVSTd þ LVIDd þ LVPWTd)3 – LVIDd3] – 13.6 g).18 The LVMI was calculated by dividing the LVM by the body surface area. LVH was defined as LVMI 4125 g/m2 in men and 4110 g/m2 in women.19 Collection of Demographic, Medical and Laboratory Data Demographic and medical data including age, sex, smoking history (ever versus never) and comorbid conditions were obtained from medical records or patient interviews. The patients under study were defined as
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having diabetes mellitus (DM) if the fasting blood glucose level was 4126 mg/dL or if hypoglycemic agents were used to control blood glucose levels. Similarly, patients were considered as having hypertension if the systolic blood pressure was Z140 mmHg or diastolic blood pressure Z90 mmHg, or if antihypertensive drugs were prescribed. Coronary artery disease was defined as a history of typical angina with a positive result for stress test, angiographically documented coronary artery disease, history of myocardial infarction or history of coronary artery bypass surgery or angioplasty. The BMI was calculated as the ratio of the weight in kilograms divided by the square of the height in meters. Laboratory data were measured from fasting blood samples by using an autoanalyzer (Roche Diagnostics GmbH, D-68298 Mannheim COBAS Integra 400). Serum creatinine was measured using the compensated Jaffé (kinetic alkaline picrate) method in a Roche/Integra 400 Analyzer (Roche Diagnostics, Mannheim, Germany) with a traceable calibrator to perform isotope-dilution mass spectrometry.20 The eGFR was calculated using the 4-variable equation in the Modification of Diet in Renal Disease study.21 Proteinuria was examined using dipsticks (Hema-Combistix, Bayer Diagnostics). A test result of 1þ or higher was defined as positive. Blood and urine samples were obtained within 1 month of enrollment. In addition, data related to angiotensin converting enzyme inhibitors (ACEIs) and angiotensin II receptor blocker (ARB) use during the study period were obtained from medical records. Definition of Cardiovascular Events Cardiovascular events were defined as cardiovascular death, hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, hospitalization for congestive heart failure, transient ischemia attack and stroke. Cardiovascular events were ascertained and adjudicated by 2 cardiologists with disagreement resolved by adjudication from a third cardiologist from the hospital course and medical records. The patients were followed-up until either the first episode of cardiovascular events or until February 2011. Statistical Analysis Statistical analysis was performed using SPSS 17.0 for Windows (SPSS Inc, Chicago, USA). Data were expressed as percentages or mean ⫾ standard deviation. Multiple comparisons among the study groups were performed using one-way analysis of variance followed by a Boneferroni-adjusted post hoc test. A Cox proportional hazards model was used to model the covariates of the risk factors and the time required for the cardiovascular events to occur. The association of the study groups with cardiovascular events was assessed using a modified stepwise procedure in a 2-step model. The first model consisted of age, THE AMERICAN JOURNAL VOLUME 351
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comorbidities (DM, hypertension, coronary artery disease and atrial fibrillation), systolic blood pressure and pulse pressure. The second model consisted of biomarkers and medications including albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria and ACEI or ARB use or use of both ACEI and ARB. A group of patients with high BMI and low LVMI was treated as the reference group, which was at the lowest risk of cardiovascular events. At P o 0.05, a difference was considered significant.
RESULTS A total of 505 patients with CKD, who were nondialyzed were included. The mean age was 66.3 ⫾ 12.2 years with 320 men and 185 women. The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVMIs (men: 140.1 g/m2; women: 131.6 g/m2). A comparison of the clinical characteristics among these study groups is shown in Table 1. The BMIs for the 4 groups were 28.3 ⫾ 3.1, 22.2 ⫾ 2.1, 28.4 ⫾ 2.7 and 22.4 ⫾ 2.1 kg/m2, respectively. Additionally, the LVMIs for the 4 groups were 105.9 ⫾ 20.9, 102.7 ⫾ 21.5, 177.3 ⫾ 35.0 and 181.9 ⫾ 48.8 g/m2. There were 50 patients and 107 patients receiving erythropoiesis-stimulating agents and iron therapy, respectively. The level of hemoglobin was inversely correlated with LVMI (unstandardized β ¼ 4.081; P o 0.001).
Relationship of Study Groups to Cardiovascular Events The median of the follow-up period was 28.8 (16.1– 36.0) months. A total of 89 cardiovascular events were documented during the follow-up period, including cardiovascular death (n ¼ 11), hospitalization for unstable angina and nonfatal myocardial infarction (n ¼ 17), sustained ventricular arrhythmia (n ¼ 9), hospitalization for congestive heart failure (n ¼ 30) and transient ischemia attack and stroke (n ¼ 22). Table 2 lists the hazard ratio (HR) estimates for cardiovascular events with and without multivariate adjustment. In the first analysis, the combination of low BMI and high LVMI (versus the combination of high BMI and low LVMI) was significantly associated with cardiovascular events in the unadjusted model (HR ¼ 3.178; 95% confidence interval [CI]: 1.645-6.140; P ¼ 0.001) and multivariable model after adjustment for age, DM, hypertension, coronary artery disease, atrial fibrillation, systolic blood pressure and pulse pressure (HR ¼ 3.511; 95% CI: 1.744-7.072; P o 0.001). This relationship remained significant after further adjustment for biomarkers, including albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria and ACEI or ARB use or use of both ACEI and ARB (HR ¼ 3.553; 95% CI: 1.494-8.450; P ¼ 0.004).
The study performed another analysis by using the ratio of LVM to height2.7 instead of LVMI.22 The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVM/height2.7 (men: 63.2 g/m2; women: 64.2 g/m2), and found the similar results, ie, the combination of low BMI and high LVM/height2.7 (versus the combination of high BMI and low LVM/ height2.7) was significantly associated with cardiovascular events in the multivariable model (HR ¼ 2.566; 95% CI: 1.071-6.147; P ¼ 0.034) after adjustment for demographic, clinical and biochemical characteristics and medications. Reproducibility The LVM intraobserver error, calculated by dividing the difference between 2 measurements by the mean of 2 measurements from 10 randomly selected cases, was 13% ⫾ 9% in this study.
DISCUSSION In the present study, the association of BMI and LVMI with cardiovascular events in patients with CKD stages 3-5 was evaluated. The combination of low BMI and high LVMI was associated with an increase in cardiovascular events compared with the combination of high BMI and low LVMI. Obesity is associated with poor survival in the general population, but it appears to improve the survival of patients undergoing hemodialysis.4 Data on the relationship between BMI and mortality in patients with CKD are limited and inconsistent. Muntner et al5 evaluated the association between BMI and coronary heart disease in patients with CKD stages 3 and 4 and reported that a high BMI was associated with an increased risk of coronary heart disease. In addition, Hsu et al23 reported that a high BMI was a risk factor for mortality in a large cohort of patients with CKD. Magdalen determined that the relationship between high BMI and cardiovascular mortality was nonsignificant after multivariate adjustment for 1,759 patients with CKD with a mean eGFR of 39 mL/min/1.73 m2.6 These results differ from those of other recent studies. In a cohort of 920 patients with advanced CKD (median creatinine levels of 3.8 mg/dL for men and 3.2 mg/dL for women), a BMI o 20 kg/m2 was associated with a greater risk of all-cause mortality. A BMI 4 30 kg/m2 demonstrated a protective trend.7 Similarly, Kovesdy et al8 revealed that a low BMI was associated with increased mortality in 521 men with CKD with a mean eGFR of 37.5 mL/min/ 1.73 m2. The inverse association was partially explained by the confounding effects of case-mix and malnutritioninflammation-cachexia syndrome. A key finding of the study was that when comparing the 2 groups with high LVMI, only the group with low BMI was associated with increased cardiovascular events (versus high BMI and low LVMI group). The association of a high BMI with
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TABLE 1. Comparison of clinical characteristics among study groups
Characteristics Age (year) Male gender (%) Smoking (%) Diabetes mellitus (%) Hypertension (%) Coronary artery disease (%) Atrial fibrillation (%) Stage of CKD Stage 3a (%) Stage 3b (%) Stage 4 (%) Stage 5 (%) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Pulse pressure (mm Hg) BMI (kg/m2) Laboratory parameters Albumin (g/dL) Fasting glucose (mg/dL) Triglyceride (mg/dL) Total cholesterol (mg/dL) Hemoglobin (g/dL) eGFR (mL/min/1.73 m2) Proteinuria (%) Medications ACEI or ARB use or use of both Echocardiographic data LVMI (g/m2) (male o 125; female o 110) LVEF (%) (450) Relative wall thickness E-wave deceleration time (ms) E/A
Higher BMI and lower LVMI (n ¼ 118)
Lower BMI and LVMI (n ¼ 135)
Higher BMI and LVMI (n ¼ 134)
Lower BMI and higher LVMI (n ¼ 118)
64.5 ⫾ 13.0 67.8 25.4 62.7 83.1 12.7 3.4
66.1 ⫾ 11.3 59.3 29.6 43.0a 83.5 4.4a 2.2
66.7 ⫾ 12.3 59.0 35.8 64.2b 85.8b 17.2 4.5
67.8 ⫾ 12.1 68.6 34.7 56.8 89.0b 11.0 6.8
8.5 40.7 33.9 16.9 137.3 ⫾ 16.3 79.7 ⫾ 11.1 57.6 ⫾ 15.8 28.3 ⫾ 3.1
11.1 41.5 28.9 18.5 135.6 ⫾ 21.1 77.6 ⫾ 11.3 58.0 ⫾ 16.2 22.2 ⫾ 2.1a
7.5ab 20.1 39.6 32.8 148.3 ⫾ 22.3ab 80.8 ⫾ 15.5 67.5 ⫾ 18.5ab 28.4 ⫾ 2.7b
3.4ab 19.5 28.8 48.3 144.1 ⫾ 21.7b 79.2 ⫾ 12.9 65.0 ⫾ 17.7ab 22.4 ⫾ 2.1ac
4.1 ⫾ 0.4 126.6 ⫾ 61.1 151 (100–211) 191.9 ⫾ 47.7 12.5 ⫾ 2.2 29.0 ⫾ 12.2 57.3
4.1 ⫾ 0.3 111.6 ⫾ 36.6 122 (92–175.25) 192.8 ⫾ 43.6 11.9 ⫾ 2.2 29.0 ⫾ 12.8 56.3
4.0 ⫾ 0.4ab 139.8 ⫾ 70.1b 154 (114.75–240.5) b 199.5 ⫾ 51.0 11.4 ⫾ 2.5a 23.2 ⫾ 12.5ab 74.6ab
3.8 ⫾ 0.5abc 126.4 ⫾ 57.9 124.5 (81.25–194.5) 192.2 ⫾ 46.9 10.7 ⫾ 2.3ab 20.7 ⫾ 12.0ab 75.2ab
81.0
72.9
74.8
63.2a
105.9 ⫾ 20.9 69.8 ⫾ 8.2 0.41 ⫾ 0.11 223.6 ⫾ 63.9 0.89 ⫾ 0.45
102.7 ⫾ 21.5 69.4 ⫾ 10.3 0.40 ⫾ 0.13 229.3 ⫾ 67.9 0.85 ⫾ 0.30
177.3 ⫾ 35.0ab 67.4 ⫾ 11.6 0.47 ⫾ 0.14ab 227.5 ⫾ 63.1 0.87 ⫾ 0.44
181.9 ⫾ 48.8ab 66.1 ⫾ 13.0 0.49 ⫾ 0.19ab 215.5 ⫾ 66.8 0.86 ⫾ 0.35
Abbreviations. A, transmitral A-wave velocity; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; E, transmitral E-wave velocity; LVEF, left ventricular ejection fraction; LVMI, left ventricular mass index. The patients under study were stratified into 4 groups according to sex-specific median values of BMI (male: 25.2 kg/m2; female: 24.9 kg/m2) and LVMI (male: 140.1 g/m2; female: 131.6 g/m2). a P o 0.05 compared with higher BMI and lower LVMI. b P o 0.05 compared with lower BMI and LVMI. c P o 0.05 compared with higher BMI and LVMI.
better cardiovascular outcomes in CKD is considered a “reverse epidemiology,” and it has been suggested that malnutrition, atherosclerosis, and inflammation may be associated.24 Markers of protein-energy wasting including hypoalbuminemia, low serum cholesterol level and low BMI, are associated with increased mortality.25 Hence, our findings suggested that the relationship between BMI and cardiovascular outcomes in patients with CKD was different from that in the general population. In general, our findings are in accordance with those from studies including patients receiving dialysis therapy.4,7,8 However, these results differ from those
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of Muntner et al5 and Hsu et al.23 The inconsistency may be explained by the difference in the severity of kidney disease among the participants. In studies by Muntner et al5 and Hsu et al,23 the cohorts represented patients with CKD stages 3–4 and 1–4, respectively. This study population consisted of patients with CKD stages 3–5 and a mean eGFR of 26.3 mL/min/ 1.73 m2. Their study population was considerably closer to the general population; thus, their results were similar to those obtained from studies involving the general population; ie, a high BMI was a risk factor for mortality.
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TABLE 2. Relation of study groups to cardiovascular events Unadjusted Parameters Higher BMI and lower LVMI Lower BMI and LVMI Higher BMI and LVMI Lower BMI and higher LVMI
Multivariate adjusted (1)
Multivariate adjusted (2)
Hazard ratio (95% CI)
P
Hazard ratio (95% CI)
P
Hazard ratio (95% CI)
P
1 1.060 (0.490–2.293) 2.146 (1.094–4.206) 3.178 (1.645–6.140)
0.882 0.026 0.001
1 1.465 (0.646–3.322) 1.965 (0.973–3.966) 3.511 (1.744–7.072)
0.361 0.060 o0.001
1 2.006 (0.768–5.240) 2.058 (0.900–4.710) 3.553 (1.494–8.450)
0.155 0.087 0.004
Values expressed as hazard ratio (95% CI). Abbreviations are the same as in Table 1. The patients under study were stratified into 4 groups according to sex-specific median values of BMI (male: 25.2 kg/m2; female: 24.9 kg/m2) and LVMI (male: 140.1 g/m2; female: 131.6 g/m2). Multivariate model (1): adjusted for age, diabetes mellitus, hypertension, coronary artery disease, atrial fibrillation, systolic blood pressure, and pulse pressure. Multivariate model (2): model (1) þ albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria, and ACEI and/or ARB use.
LVH has been frequently noted in patients with CKD because of pressure and volume overload.12,13 An increased LVMI has been reported to be a risk factor for poor cardiovascular prognosis in CKD.26–29 Silaruks et al29 investigated the clinical outcome of LVH in 66 patients, who were nondiabetic on continuous ambulatory peritoneal dialysis and observed that severe LVH (left ventricular wall thickness 41.4 cm) was significantly associated with high cardiovascular morbidity and mortality. The Cardiovascular Risk Reduction by Early Anemia Treatment with Epoetin Beta trial demonstrated that LVH was frequently associated with poor cardiovascular outcomes in patients with CKD stages 3 and 4.30 In this study, compared with the group with a high BMI and low LVMI, the group with a low BMI and high LVMI was at a higher risk of conditions leading to cardiovascular morbidity, such as higher prevalence of hypertension, higher systolic blood pressure and pulse pressure, lower albumin, lower hemoglobin, lower eGFR, higher prevalence of proteinuria and advanced CKD stages. Even after adjustment for these confounding factors, the group with low BMI and high LVMI was still associated with an increase in the cardiovascular events. Hence, low BMI and high LVMI might have had a synergetic effect on adverse cardiovascular outcomes. Chronic anemia may lead to a compensatory increase in cardiac output. Such increase in cardiac workload may enhance left ventricular dilation and growth.31,32 Anemia has also been identified as an important risk factor for LVH and poor cardiovascular prognosis.33 In our study, we also found that the hemoglobin level was inversely associated with LVMI. There were several limitations in the present study. First, we used the baseline BMI for analysis. Data of time-dependent changes in BMI were not obtained, and we were not able to investigate the association between weight variation and outcomes. In addition, BMI is limited to differentiate the fat and lean mass. Therefore, body composition analysis using dual-energy x ray absorption is of importance to elucidate this issue in the future studies. Finally, BMI may be misleading in the presence of edema, which occurs commonly in patients with advanced CKD. Waist circumference may be a more sensitive marker for risk stratification in CKD.
CONCLUSIONS The results demonstrate that the coexistence of low BMI and high LVMI was independently associated with increased cardiovascular events in patients with CKD stages 3-5. BMI and LVMI assessment might be useful in identifying a high-risk group of patients with CKD with poor cardiovascular prognosis.
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15. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events and hospitalization. N Engl J Med 2004; 351:1296–305. 16. Tonelli M, Wiebe N, Culleton B, et al. Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol 2006;17:2034–47. 17. Levey AS, Coresh J, Bolton K, et al. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification. Am J Kidney Dis 2002;39:S1–266. 18. Devereux RB, Alonso DR, Lutas EM, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol 1986;57:450–8. 19. Mancia G, De Backer G, Dominiczak A, et al. Guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2007;25: 1105–87. 20. Vickery S, Stevens PE, Dalton RN, et al. Does the ID-MS traceable MDRD equation work and is it suitable for use with compensated Jaffe and enzymatic creatinine assays. Nephrol Dial Transplant 2006;21:2439–45. 21. Chen LI, Guh JY, Wu KD, et al. Modification of diet in renal disease (MDRD) study and CKD epidemiology collaboration (CKD-EPI) equations for Taiwanese adults. PLoS One 2014;9:e99645. 22. de Simone G, Daniels SR, Devereux RB, et al. Left ventricular mass and body size in normotensive children and adults: assessment of allometric relations and impact of overweight. J Am Coll Cardiol 1992;20: 1251–60. 23. Hsu CY, McCulloch CE, Iribarren C, et al. Body mass index and risk for end-stage renal disease. Ann Intern Med 2006;144:21–8. 24. Beddhu S. The body mass index paradox and an obesity, inflammation and atherosclerosis syndrome in chronic kidney disease. Semin Dial 2004; 17:229–32. 25. Kovesdy CP, Kalantar-Zadeh K. Why is protein-energy wasting associated with mortality in chronic kidney disease? Semin Nephrol 2009;29:3–14. 26. Aronow WS, Epstein S, Koenigsberg M, et al. Usefulness of echocardiographic left ventricular hypertrophy, ventricular tachycardia and complex ventricular arrhythmias in predicting ventricular fibrillation or sudden cardiac death in elderly patients. Am J Cardiol 1988;62: 1124–5. 27. Aronow WS, Koenigsberg M, Schwartz KS. Usefulness of echocardiographic left ventricular hypertrophy in predicting new coronary events and atherothrombotic brain infarction in patients over 62 years of age. Am J Cardiol 1988;61:1130–2.
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From the Division of Nephrology (SCC, JCH, YCT, LIC, JMC, HCC), Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Division of Cardiology (HMS), Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Department of Internal Medicine (SCC, JCH, HMS, JMC), Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Faculty of Renal Care (JMC, HCC), College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Faculty of Medicine (SCC, HMS), College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC Submitted May 11, 2015; accepted August 3, 2015. The research presented in this article is supported by the grant from Kaohsiung Municipal Hsiao-Kang Hospital (kmhk-102-001), Kaohsiung Medical University, Kaohsiung, and the statistical work by the Department of Research Education and Training at Kaohsiung Municipal Hsiao-Kang Hospital. The authors have no conflicts of interest to disclose. Correspondence: Ho-Ming Su, MD, Department of Internal Medicine, Kaohsiung Municipal, Hsiao-Kang Hospital, Kaohsiung Medical University, 482, Shan-Ming Road, Hsiao-Kang District, 812 Kaohsiung, Taiwan, ROC. (E-mail: [email protected]).
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Body Mass Index, Left Ventricular Mass Index and Cardiovascular Events in Chronic Kidney Disease Szu-Chia Chen, MD, Jiun-Chi Huang, MD, Yi-Chun Tsai, MD, Ling-I Chen, MD, Ho-Ming Su, MD, Jer-Ming Chang, MD, PhD and Hung-Chun Chen, MD, PhD ABSTRACT Background: Obesity and left ventricular hypertrophy are prevalent in chronic kidney disease (CKD), but the association of body mass index (BMI) and left ventricular mass index (LVMI) with cardiovascular outcomes in patients with CKD is unclear. This study was designed to assess whether the combination of BMI and LVMI is independently associated with cardiovascular events in patients with CKD stages 3-5. Methods: From the outpatient department, 523 patients with CKD who received echocardiographic examination were enrolled. The patients under study were classified into 4 groups according to sex-specific median BMIs and LVMIs. Cardiovascular events were defined as cardiovascular death, hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, hospitalization for congestive heart failure, transient ischemia attack and stroke. The relative cardiovascular event risk was analyzed using Cox-regression methods. Results: The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVMIs (men: 140.1 g/m2; women: 131.6 g/m2). A combination of low BMI and high LVMI (versus the combination of high BMI and low LVMI) was significantly associated with cardiovascular events in an unadjusted model (hazard ratio [HR] ¼ 3.178; 95% confidence interval [CI]: 1.645-6.140; P o 0.001) and in a multivariable model after adjustment for demographic, clinical and biochemical characteristics and medications (HR ¼ 3.553; 95% CI: 1.494-8.450; P ¼ 0.004). Conclusions: The findings showed that the combination of low BMI and high LVMI was associated with adverse cardiovascular events in patients with CKD stages 3–5. Key Indexing Terms: Cardiovascular events; Chronic kidney disease; Body mass index; Left ventricular mass index. [Am J Med Sci 2016;351(1):91–96.]
INTRODUCTION
O
besity has reached epidemic proportions in the developed world1 and has increased the risk of cardiovascular disease–related mortality in the general population.2,3 In contrast to the general population, obesity appears to be associated with better survival in patients undergoing hemodialysis.4 However, published data on the relationship between obesity and cardiovascular morbidity and mortality in chronic kidney disease (CKD) are limited and inconsistent. Among studies related to obesity and mortality, one study reported that high body mass index (BMI) was associated with an increased risk of coronary artery disease,5 another study failed to identify BMI as a prognostic factor,6 whereas a third study suggested that a reverse association exists between obesity and mortality in patients with CKD.7,8 Thus, the status of obesity as a risk factor for adverse cardiovascular events in patients with CKD remains controversial. An increased BMI was affected by or linked to various risk factors for left ventricular hypertrophy
(LVH), such as obesity, insulin resistance, metabolic syndrome and hypertension.9–11 Rider et al10 positively associated BMI with LVH detected using echocardiography. LVH was also frequently encountered in patients with CKD because of pressure and volume overload.12,13 Furthermore, recent study involving patients with CKD stages 3-5 demonstrated that an increased left ventricular mass index (LVMI) was independently associated with adverse cardiovascular outcomes.14 CKD is an increasing worldwide public health problem associated with increased morbidity and mortality. Cardiovascular disease is the leading cause of morbidity and mortality in patients with CKD.15,16 No studies have evaluated the association between the combination of BMI and LVMI and cardiovascular outcome in patients with CKD. Therefore, the aim of this study was to assess whether the combination of BMI and LVMI is associated with cardiovascular events in patients with CKD stages 3–5.
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STUDY PATIENTS AND METHODS Study Patients and Design This study was conducted in a regional hospital in Southern Taiwan. The study consecutively recruited 523 patients with CKD stages 3–5, who had underwent predialysis, according to the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (K/DOQI) guidelines,17 from January 2007-May 2010. The study classified patients with evidence of kidney damage lasting longer than 3 months into CKD stages 3a, 3b, 4 and 5, based on estimated glomerular filtration rates (eGFRs) of 45–59, 30–44, 15–29 and o15 mL/min/ 1.73 m2, respectively. The study patients were followedup regularly at the Outpatient Department of Internal Medicine. They were selected to participate in this study if they agreed to receive echocardiographic examination. A total of 3 patients refused echocardiographic examinations because of personal reasons. A total of 10 patients with significant mitral and aortic valve diseases and 5 other patients with inadequate image visualization were also excluded. Finally, 505 patients were included. The protocol was approved by the Institutional Review Board and enrolled patients gave written, informed consents. Evaluation of Cardiac Structure and Function The echocardiographic examination was performed by an experienced cardiologist using a VIVID 7 (General Electric Medical Systems, Horten, Norway), with the participant respiring quietly in the left decubitus position. The cardiologist was blinded to the other data. Twodimensional and 2-dimensionally–guided M-mode images were recorded in the standardized views. The echocardiographic measurements included the left ventricular internal diameter in diastole (LVIDd), left ventricular posterior wall thickness in diastole (LVPWTd), interventricular septal wall thickness in diastole (IVSTd), E-wave deceleration time, transmitral E-wave velocity and transmitral A-wave velocity. The left ventricular ejection fraction was measured using the modified Simpson's method. Impaired left ventricular systolic function was defined as left ventricular ejection fraction o50%. The left ventricular relative wall thickness was calculated as the ratio of 2 LVPWTd/LVIDd. The left ventricular mass (LVM) was calculated using Devereuxmodified method (ie, LVM ¼ 1.04 [(IVSTd þ LVIDd þ LVPWTd)3 – LVIDd3] – 13.6 g).18 The LVMI was calculated by dividing the LVM by the body surface area. LVH was defined as LVMI 4125 g/m2 in men and 4110 g/m2 in women.19 Collection of Demographic, Medical and Laboratory Data Demographic and medical data including age, sex, smoking history (ever versus never) and comorbid conditions were obtained from medical records or patient interviews. The patients under study were defined as
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having diabetes mellitus (DM) if the fasting blood glucose level was 4126 mg/dL or if hypoglycemic agents were used to control blood glucose levels. Similarly, patients were considered as having hypertension if the systolic blood pressure was Z140 mmHg or diastolic blood pressure Z90 mmHg, or if antihypertensive drugs were prescribed. Coronary artery disease was defined as a history of typical angina with a positive result for stress test, angiographically documented coronary artery disease, history of myocardial infarction or history of coronary artery bypass surgery or angioplasty. The BMI was calculated as the ratio of the weight in kilograms divided by the square of the height in meters. Laboratory data were measured from fasting blood samples by using an autoanalyzer (Roche Diagnostics GmbH, D-68298 Mannheim COBAS Integra 400). Serum creatinine was measured using the compensated Jaffé (kinetic alkaline picrate) method in a Roche/Integra 400 Analyzer (Roche Diagnostics, Mannheim, Germany) with a traceable calibrator to perform isotope-dilution mass spectrometry.20 The eGFR was calculated using the 4-variable equation in the Modification of Diet in Renal Disease study.21 Proteinuria was examined using dipsticks (Hema-Combistix, Bayer Diagnostics). A test result of 1þ or higher was defined as positive. Blood and urine samples were obtained within 1 month of enrollment. In addition, data related to angiotensin converting enzyme inhibitors (ACEIs) and angiotensin II receptor blocker (ARB) use during the study period were obtained from medical records. Definition of Cardiovascular Events Cardiovascular events were defined as cardiovascular death, hospitalization for unstable angina, nonfatal myocardial infarction, sustained ventricular arrhythmia, hospitalization for congestive heart failure, transient ischemia attack and stroke. Cardiovascular events were ascertained and adjudicated by 2 cardiologists with disagreement resolved by adjudication from a third cardiologist from the hospital course and medical records. The patients were followed-up until either the first episode of cardiovascular events or until February 2011. Statistical Analysis Statistical analysis was performed using SPSS 17.0 for Windows (SPSS Inc, Chicago, USA). Data were expressed as percentages or mean ⫾ standard deviation. Multiple comparisons among the study groups were performed using one-way analysis of variance followed by a Boneferroni-adjusted post hoc test. A Cox proportional hazards model was used to model the covariates of the risk factors and the time required for the cardiovascular events to occur. The association of the study groups with cardiovascular events was assessed using a modified stepwise procedure in a 2-step model. The first model consisted of age, THE AMERICAN JOURNAL VOLUME 351
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comorbidities (DM, hypertension, coronary artery disease and atrial fibrillation), systolic blood pressure and pulse pressure. The second model consisted of biomarkers and medications including albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria and ACEI or ARB use or use of both ACEI and ARB. A group of patients with high BMI and low LVMI was treated as the reference group, which was at the lowest risk of cardiovascular events. At P o 0.05, a difference was considered significant.
RESULTS A total of 505 patients with CKD, who were nondialyzed were included. The mean age was 66.3 ⫾ 12.2 years with 320 men and 185 women. The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVMIs (men: 140.1 g/m2; women: 131.6 g/m2). A comparison of the clinical characteristics among these study groups is shown in Table 1. The BMIs for the 4 groups were 28.3 ⫾ 3.1, 22.2 ⫾ 2.1, 28.4 ⫾ 2.7 and 22.4 ⫾ 2.1 kg/m2, respectively. Additionally, the LVMIs for the 4 groups were 105.9 ⫾ 20.9, 102.7 ⫾ 21.5, 177.3 ⫾ 35.0 and 181.9 ⫾ 48.8 g/m2. There were 50 patients and 107 patients receiving erythropoiesis-stimulating agents and iron therapy, respectively. The level of hemoglobin was inversely correlated with LVMI (unstandardized β ¼ 4.081; P o 0.001).
Relationship of Study Groups to Cardiovascular Events The median of the follow-up period was 28.8 (16.1– 36.0) months. A total of 89 cardiovascular events were documented during the follow-up period, including cardiovascular death (n ¼ 11), hospitalization for unstable angina and nonfatal myocardial infarction (n ¼ 17), sustained ventricular arrhythmia (n ¼ 9), hospitalization for congestive heart failure (n ¼ 30) and transient ischemia attack and stroke (n ¼ 22). Table 2 lists the hazard ratio (HR) estimates for cardiovascular events with and without multivariate adjustment. In the first analysis, the combination of low BMI and high LVMI (versus the combination of high BMI and low LVMI) was significantly associated with cardiovascular events in the unadjusted model (HR ¼ 3.178; 95% confidence interval [CI]: 1.645-6.140; P ¼ 0.001) and multivariable model after adjustment for age, DM, hypertension, coronary artery disease, atrial fibrillation, systolic blood pressure and pulse pressure (HR ¼ 3.511; 95% CI: 1.744-7.072; P o 0.001). This relationship remained significant after further adjustment for biomarkers, including albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria and ACEI or ARB use or use of both ACEI and ARB (HR ¼ 3.553; 95% CI: 1.494-8.450; P ¼ 0.004).
The study performed another analysis by using the ratio of LVM to height2.7 instead of LVMI.22 The patients were stratified into 4 groups according to sex-specific median BMIs (men: 25.2 kg/m2; women: 24.9 kg/m2) and LVM/height2.7 (men: 63.2 g/m2; women: 64.2 g/m2), and found the similar results, ie, the combination of low BMI and high LVM/height2.7 (versus the combination of high BMI and low LVM/ height2.7) was significantly associated with cardiovascular events in the multivariable model (HR ¼ 2.566; 95% CI: 1.071-6.147; P ¼ 0.034) after adjustment for demographic, clinical and biochemical characteristics and medications. Reproducibility The LVM intraobserver error, calculated by dividing the difference between 2 measurements by the mean of 2 measurements from 10 randomly selected cases, was 13% ⫾ 9% in this study.
DISCUSSION In the present study, the association of BMI and LVMI with cardiovascular events in patients with CKD stages 3-5 was evaluated. The combination of low BMI and high LVMI was associated with an increase in cardiovascular events compared with the combination of high BMI and low LVMI. Obesity is associated with poor survival in the general population, but it appears to improve the survival of patients undergoing hemodialysis.4 Data on the relationship between BMI and mortality in patients with CKD are limited and inconsistent. Muntner et al5 evaluated the association between BMI and coronary heart disease in patients with CKD stages 3 and 4 and reported that a high BMI was associated with an increased risk of coronary heart disease. In addition, Hsu et al23 reported that a high BMI was a risk factor for mortality in a large cohort of patients with CKD. Magdalen determined that the relationship between high BMI and cardiovascular mortality was nonsignificant after multivariate adjustment for 1,759 patients with CKD with a mean eGFR of 39 mL/min/1.73 m2.6 These results differ from those of other recent studies. In a cohort of 920 patients with advanced CKD (median creatinine levels of 3.8 mg/dL for men and 3.2 mg/dL for women), a BMI o 20 kg/m2 was associated with a greater risk of all-cause mortality. A BMI 4 30 kg/m2 demonstrated a protective trend.7 Similarly, Kovesdy et al8 revealed that a low BMI was associated with increased mortality in 521 men with CKD with a mean eGFR of 37.5 mL/min/ 1.73 m2. The inverse association was partially explained by the confounding effects of case-mix and malnutritioninflammation-cachexia syndrome. A key finding of the study was that when comparing the 2 groups with high LVMI, only the group with low BMI was associated with increased cardiovascular events (versus high BMI and low LVMI group). The association of a high BMI with
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TABLE 1. Comparison of clinical characteristics among study groups
Characteristics Age (year) Male gender (%) Smoking (%) Diabetes mellitus (%) Hypertension (%) Coronary artery disease (%) Atrial fibrillation (%) Stage of CKD Stage 3a (%) Stage 3b (%) Stage 4 (%) Stage 5 (%) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Pulse pressure (mm Hg) BMI (kg/m2) Laboratory parameters Albumin (g/dL) Fasting glucose (mg/dL) Triglyceride (mg/dL) Total cholesterol (mg/dL) Hemoglobin (g/dL) eGFR (mL/min/1.73 m2) Proteinuria (%) Medications ACEI or ARB use or use of both Echocardiographic data LVMI (g/m2) (male o 125; female o 110) LVEF (%) (450) Relative wall thickness E-wave deceleration time (ms) E/A
Higher BMI and lower LVMI (n ¼ 118)
Lower BMI and LVMI (n ¼ 135)
Higher BMI and LVMI (n ¼ 134)
Lower BMI and higher LVMI (n ¼ 118)
64.5 ⫾ 13.0 67.8 25.4 62.7 83.1 12.7 3.4
66.1 ⫾ 11.3 59.3 29.6 43.0a 83.5 4.4a 2.2
66.7 ⫾ 12.3 59.0 35.8 64.2b 85.8b 17.2 4.5
67.8 ⫾ 12.1 68.6 34.7 56.8 89.0b 11.0 6.8
8.5 40.7 33.9 16.9 137.3 ⫾ 16.3 79.7 ⫾ 11.1 57.6 ⫾ 15.8 28.3 ⫾ 3.1
11.1 41.5 28.9 18.5 135.6 ⫾ 21.1 77.6 ⫾ 11.3 58.0 ⫾ 16.2 22.2 ⫾ 2.1a
7.5ab 20.1 39.6 32.8 148.3 ⫾ 22.3ab 80.8 ⫾ 15.5 67.5 ⫾ 18.5ab 28.4 ⫾ 2.7b
3.4ab 19.5 28.8 48.3 144.1 ⫾ 21.7b 79.2 ⫾ 12.9 65.0 ⫾ 17.7ab 22.4 ⫾ 2.1ac
4.1 ⫾ 0.4 126.6 ⫾ 61.1 151 (100–211) 191.9 ⫾ 47.7 12.5 ⫾ 2.2 29.0 ⫾ 12.2 57.3
4.1 ⫾ 0.3 111.6 ⫾ 36.6 122 (92–175.25) 192.8 ⫾ 43.6 11.9 ⫾ 2.2 29.0 ⫾ 12.8 56.3
4.0 ⫾ 0.4ab 139.8 ⫾ 70.1b 154 (114.75–240.5) b 199.5 ⫾ 51.0 11.4 ⫾ 2.5a 23.2 ⫾ 12.5ab 74.6ab
3.8 ⫾ 0.5abc 126.4 ⫾ 57.9 124.5 (81.25–194.5) 192.2 ⫾ 46.9 10.7 ⫾ 2.3ab 20.7 ⫾ 12.0ab 75.2ab
81.0
72.9
74.8
63.2a
105.9 ⫾ 20.9 69.8 ⫾ 8.2 0.41 ⫾ 0.11 223.6 ⫾ 63.9 0.89 ⫾ 0.45
102.7 ⫾ 21.5 69.4 ⫾ 10.3 0.40 ⫾ 0.13 229.3 ⫾ 67.9 0.85 ⫾ 0.30
177.3 ⫾ 35.0ab 67.4 ⫾ 11.6 0.47 ⫾ 0.14ab 227.5 ⫾ 63.1 0.87 ⫾ 0.44
181.9 ⫾ 48.8ab 66.1 ⫾ 13.0 0.49 ⫾ 0.19ab 215.5 ⫾ 66.8 0.86 ⫾ 0.35
Abbreviations. A, transmitral A-wave velocity; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; E, transmitral E-wave velocity; LVEF, left ventricular ejection fraction; LVMI, left ventricular mass index. The patients under study were stratified into 4 groups according to sex-specific median values of BMI (male: 25.2 kg/m2; female: 24.9 kg/m2) and LVMI (male: 140.1 g/m2; female: 131.6 g/m2). a P o 0.05 compared with higher BMI and lower LVMI. b P o 0.05 compared with lower BMI and LVMI. c P o 0.05 compared with higher BMI and LVMI.
better cardiovascular outcomes in CKD is considered a “reverse epidemiology,” and it has been suggested that malnutrition, atherosclerosis, and inflammation may be associated.24 Markers of protein-energy wasting including hypoalbuminemia, low serum cholesterol level and low BMI, are associated with increased mortality.25 Hence, our findings suggested that the relationship between BMI and cardiovascular outcomes in patients with CKD was different from that in the general population. In general, our findings are in accordance with those from studies including patients receiving dialysis therapy.4,7,8 However, these results differ from those
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of Muntner et al5 and Hsu et al.23 The inconsistency may be explained by the difference in the severity of kidney disease among the participants. In studies by Muntner et al5 and Hsu et al,23 the cohorts represented patients with CKD stages 3–4 and 1–4, respectively. This study population consisted of patients with CKD stages 3–5 and a mean eGFR of 26.3 mL/min/ 1.73 m2. Their study population was considerably closer to the general population; thus, their results were similar to those obtained from studies involving the general population; ie, a high BMI was a risk factor for mortality.
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TABLE 2. Relation of study groups to cardiovascular events Unadjusted Parameters Higher BMI and lower LVMI Lower BMI and LVMI Higher BMI and LVMI Lower BMI and higher LVMI
Multivariate adjusted (1)
Multivariate adjusted (2)
Hazard ratio (95% CI)
P
Hazard ratio (95% CI)
P
Hazard ratio (95% CI)
P
1 1.060 (0.490–2.293) 2.146 (1.094–4.206) 3.178 (1.645–6.140)
0.882 0.026 0.001
1 1.465 (0.646–3.322) 1.965 (0.973–3.966) 3.511 (1.744–7.072)
0.361 0.060 o0.001
1 2.006 (0.768–5.240) 2.058 (0.900–4.710) 3.553 (1.494–8.450)
0.155 0.087 0.004
Values expressed as hazard ratio (95% CI). Abbreviations are the same as in Table 1. The patients under study were stratified into 4 groups according to sex-specific median values of BMI (male: 25.2 kg/m2; female: 24.9 kg/m2) and LVMI (male: 140.1 g/m2; female: 131.6 g/m2). Multivariate model (1): adjusted for age, diabetes mellitus, hypertension, coronary artery disease, atrial fibrillation, systolic blood pressure, and pulse pressure. Multivariate model (2): model (1) þ albumin, fasting glucose, log triglyceride, total cholesterol, hemoglobin, eGFR, proteinuria, and ACEI and/or ARB use.
LVH has been frequently noted in patients with CKD because of pressure and volume overload.12,13 An increased LVMI has been reported to be a risk factor for poor cardiovascular prognosis in CKD.26–29 Silaruks et al29 investigated the clinical outcome of LVH in 66 patients, who were nondiabetic on continuous ambulatory peritoneal dialysis and observed that severe LVH (left ventricular wall thickness 41.4 cm) was significantly associated with high cardiovascular morbidity and mortality. The Cardiovascular Risk Reduction by Early Anemia Treatment with Epoetin Beta trial demonstrated that LVH was frequently associated with poor cardiovascular outcomes in patients with CKD stages 3 and 4.30 In this study, compared with the group with a high BMI and low LVMI, the group with a low BMI and high LVMI was at a higher risk of conditions leading to cardiovascular morbidity, such as higher prevalence of hypertension, higher systolic blood pressure and pulse pressure, lower albumin, lower hemoglobin, lower eGFR, higher prevalence of proteinuria and advanced CKD stages. Even after adjustment for these confounding factors, the group with low BMI and high LVMI was still associated with an increase in the cardiovascular events. Hence, low BMI and high LVMI might have had a synergetic effect on adverse cardiovascular outcomes. Chronic anemia may lead to a compensatory increase in cardiac output. Such increase in cardiac workload may enhance left ventricular dilation and growth.31,32 Anemia has also been identified as an important risk factor for LVH and poor cardiovascular prognosis.33 In our study, we also found that the hemoglobin level was inversely associated with LVMI. There were several limitations in the present study. First, we used the baseline BMI for analysis. Data of time-dependent changes in BMI were not obtained, and we were not able to investigate the association between weight variation and outcomes. In addition, BMI is limited to differentiate the fat and lean mass. Therefore, body composition analysis using dual-energy x ray absorption is of importance to elucidate this issue in the future studies. Finally, BMI may be misleading in the presence of edema, which occurs commonly in patients with advanced CKD. Waist circumference may be a more sensitive marker for risk stratification in CKD.
CONCLUSIONS The results demonstrate that the coexistence of low BMI and high LVMI was independently associated with increased cardiovascular events in patients with CKD stages 3-5. BMI and LVMI assessment might be useful in identifying a high-risk group of patients with CKD with poor cardiovascular prognosis.
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15. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events and hospitalization. N Engl J Med 2004; 351:1296–305. 16. Tonelli M, Wiebe N, Culleton B, et al. Chronic kidney disease and mortality risk: a systematic review. J Am Soc Nephrol 2006;17:2034–47. 17. Levey AS, Coresh J, Bolton K, et al. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification. Am J Kidney Dis 2002;39:S1–266. 18. Devereux RB, Alonso DR, Lutas EM, et al. Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol 1986;57:450–8. 19. Mancia G, De Backer G, Dominiczak A, et al. Guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2007;25: 1105–87. 20. Vickery S, Stevens PE, Dalton RN, et al. Does the ID-MS traceable MDRD equation work and is it suitable for use with compensated Jaffe and enzymatic creatinine assays. Nephrol Dial Transplant 2006;21:2439–45. 21. Chen LI, Guh JY, Wu KD, et al. Modification of diet in renal disease (MDRD) study and CKD epidemiology collaboration (CKD-EPI) equations for Taiwanese adults. PLoS One 2014;9:e99645. 22. de Simone G, Daniels SR, Devereux RB, et al. Left ventricular mass and body size in normotensive children and adults: assessment of allometric relations and impact of overweight. J Am Coll Cardiol 1992;20: 1251–60. 23. Hsu CY, McCulloch CE, Iribarren C, et al. Body mass index and risk for end-stage renal disease. Ann Intern Med 2006;144:21–8. 24. Beddhu S. The body mass index paradox and an obesity, inflammation and atherosclerosis syndrome in chronic kidney disease. Semin Dial 2004; 17:229–32. 25. Kovesdy CP, Kalantar-Zadeh K. Why is protein-energy wasting associated with mortality in chronic kidney disease? Semin Nephrol 2009;29:3–14. 26. Aronow WS, Epstein S, Koenigsberg M, et al. Usefulness of echocardiographic left ventricular hypertrophy, ventricular tachycardia and complex ventricular arrhythmias in predicting ventricular fibrillation or sudden cardiac death in elderly patients. Am J Cardiol 1988;62: 1124–5. 27. Aronow WS, Koenigsberg M, Schwartz KS. Usefulness of echocardiographic left ventricular hypertrophy in predicting new coronary events and atherothrombotic brain infarction in patients over 62 years of age. Am J Cardiol 1988;61:1130–2.
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28. Casale PN, Devereux RB, Milner M, et al. Value of echocardiographic measurement of left ventricular mass in predicting cardiovascular morbid events in hypertensive men. Ann Intern Med 1986;105:173–8. 29. Silaruks S, Sirivongs D, Chunlertrith D. Left ventricular hypertrophy and clinical outcome in capd patients. Perit Dial Int 2000;20:461–6. 30. Eckardt KU, Scherhag A, Macdougall IC, et al. Left ventricular geometry predicts cardiovascular outcomes associated with anemia correction in CKD. J Am Soc Nephrol 2009;20:2651–60. 31. Vlagopoulos PT, Tighiouart H, Weiner DE, et al. Anemia as a risk factor for cardiovascular disease and all-cause mortality in diabetes: the impact of chronic kidney disease. J Am Soc Nephrol 2005;16:3403–10. 32. Weiner DE, Tighiouart H, Vlagopoulos PT, et al. Effects of anemia and left ventricular hypertrophy on cardiovascular disease in patients with chronic kidney disease. J Am Soc Nephrol 2005;16:1803–10. 33. Levin A, Thompson CR, Ethier J, et al. Left ventricular mass index increase in early renal disease: impact of decline in hemoglobin. Am J Kidney Dis 1999;34:125–34.
From the Division of Nephrology (SCC, JCH, YCT, LIC, JMC, HCC), Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Division of Cardiology (HMS), Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Department of Internal Medicine (SCC, JCH, HMS, JMC), Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Faculty of Renal Care (JMC, HCC), College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC; Faculty of Medicine (SCC, HMS), College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, ROC Submitted May 11, 2015; accepted August 3, 2015. The research presented in this article is supported by the grant from Kaohsiung Municipal Hsiao-Kang Hospital (kmhk-102-001), Kaohsiung Medical University, Kaohsiung, and the statistical work by the Department of Research Education and Training at Kaohsiung Municipal Hsiao-Kang Hospital. The authors have no conflicts of interest to disclose. Correspondence: Ho-Ming Su, MD, Department of Internal Medicine, Kaohsiung Municipal, Hsiao-Kang Hospital, Kaohsiung Medical University, 482, Shan-Ming Road, Hsiao-Kang District, 812 Kaohsiung, Taiwan, ROC. (E-mail: [email protected]).
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