Metabolic risk factors are increasingly being recognized

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1 Orthotopic Heart Transplantation in Patients With Metabolic Risk Factors Arman Kilic, MD, John V. Conte, MD, Ashish S. Shah, MD, and David D. Yuh, MD Division of Cardiac Surgery, Department of Surgery, The Johns Hopkins Medical Institutions Baltimore, Maryland; and Section of Cardiac Surgery, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut Background. The aim of this study was to evaluate the impact of metabolic risk factors on mortality rates after orthotopic heart transplantation (OHT). Methods. Adult patients undergoing OHT between 1998 and 2008 were identified in the United Network for Organ Sharing registry. The impact of metabolic risk factors (hypertension, diabetes mellitus, and obesity) on mortality post-oht was evaluated in a Cox proportional hazards regression analysis adjusted for other variables associated with survival in univariate analysis (exploratory p value < 0.2). Kaplan-Meier survival estimates were compared with the log-rank test. Results. A total of 15,960 eligible patients underwent OHT during the study period. There were 6,368 (39.9%) patients with none of these risk factors, 6,138 (38.5%) with 1 risk factor, 2,811 (17.6%) with 2 risk factors, and 643 (4.0%) who had all 3 risk factors. After adjusting for other significant variables influencing survival, each individual risk factor independently increased the likelihood of mortality post-oht (hypertension: HR 1.10 [1.03 to 1.17]; diabetes: HR 1.22[1.13 to 1.31]; obesity: HR 1.17 [1.10 to 1.26], each p < 0.01). There was an exponential trend of increasing mortality with the addition of each risk factor (r , p < 0.001) such that patients with all 3 risk factors had a 63% increased mortality compared with those with no risk factors (HR 1.63 [1.42 to 1.88], p < 0.001). There was also a significant trend in declining 5-year survival rates with an increasing number of risk factors: 0 (74.7%), 1 (71.3%), 2 (68.2%), and 3 (63.1%) (p < 0.001). Conclusions. This large-cohort study demonstrates that an increasing number of metabolic risk factors in OHT recipients is associated with exponential increases in postoperative mortality rates. (Ann Thorac Surg 2012;93:718 25) 2012 by The Society of Thoracic Surgeons Metabolic risk factors are increasingly being recognized as occurring in clusters. For instance, obese patients are known to have a higher prevalence of other metabolic disorders such as diabetes mellitus, hypercholesterolemia, and hypertension as compared with nonobese individuals [1]. In fact, a metabolic syndrome has been defined as a constellation of metabolic findings that collectively increases the risk of cardiovascular disease, morbidity, and mortality [2 4]. Given that the prevalence of these conditions is increasing, it is imperative that the effect of these metabolic disorders on surgical outcomes is examined [5, 6]. The impact of an increasing number of metabolic disorders on outcomes of orthotopic heart transplantation (OHT) remains incompletely understood. The aim of this study was to evaluate the effect of obesity, diabetes mellitus, and hypertension, both individually and in combination, on mortality after OHT. Patients and Methods Data Source The United Network for Organ Sharing (UNOS) database was utilized for this study. This registry provides Accepted for publication Nov 18, Address correspondence to Dr Yuh, Section of Cardiac Surgery, Yale University School of Medicine, 330 Cedar St, Boardman 204, New Haven, CT 06510; david.yuh@yale.edu. de-identified data from all thoracic organ transplantations performed in the United States. Follow-up data were available through Our Institutional Review Board approved the study protocol. Study Design All patients undergoing OHT between 1998 and 2008 were identified in the UNOS registry. The study was limited to adult ( 18 years) recipients. Patients undergoing retransplantation or multivisceral transplantation were excluded, as were patients in whom the presence or absence of these metabolic risk factors was not recorded. The primary endpoint was all-cause mortality after OHT. Data and Statistical Analyses Baseline characteristics were initially compared between patients with all 3 risk factors and patients with no risk factors. All recipient, transplant, and donor covariates were then evaluated in univariate Cox proportional hazards regression analysis to determine their impact on the primary endpoint of all-cause mortality after OHT. These variables were assessed at the time of transplant, not at the time of listing. These covariates included UNOS status, age, serum creatinine, serum bilirubin, body mass index, sex, race, mechanical ventilation, hypertension, bridging with ventricular assist devices, intraaortic balloon pump, intensive care unit stay prior to OHT, recipient serum cytomegalovirus status, biatrial versus bicaval 2012 by The Society of Thoracic Surgeons /$36.00 Published by Elsevier Inc doi: /j.athoracsur

2 Ann Thorac Surg KILIC ET AL 2012;93: METABOLIC RISK FACTORS IN OHT 719 Fig 1. Prevalence of risk factors, alone and in combination, in the study cohort. (D diabetes mellitus; H hypertension; O obesity; OHT orthotopic heart transplantation.) ADULT CARDIAC anastomotic technique, year of transplant, days on waitlist, ischemic time, donor age, donor body mass index, donor sex, donor race, donor serum cytomegalovirus status, donor cigarette use, donor diabetes, donor hypertension, donor inotropes, human leukocyte antigen matching, cytomegalovirus status matching, race matching, gender matching, donor to recipient body mass index ratio, and blood type matching. Those factors found to be associated with mortality (exploratory p value 0.2) were entered into a multivariable Cox regression model. Variables with more than 20% missing data were excluded from this multivariate model. The impact of metabolic risk factors on mortality was then evaluated in the multivariate model, adjusting for significant variables identified in the univariate analysis. All hazard ratios were presented with 95% confidence intervals. In addition, the Kaplan-Meier method was used to model survival, and survival curves were compared using the log-rank test. The 2 test was performed for categoric data and the Student t test for continuous data. All analyses were performed using STATA software, version 11 (StataCorp LP, College Station, TX). Results Study Population A total of 15,960 patients underwent OHT during the study period and met entry criteria for the study. Hypertension was the most common metabolic risk factor present (n 6,341; 39.7%) (Fig 1). In addition, there were 3,968 (24.9%) obese patients and 3,380 (21.2%) diabetics in this study population. Overall, there were 6,368 (39.9%) patients with none of the 3 metabolic risk factors. A total of 6,138 (38.5%) had 1 risk factor, 2,811 (17.6%) had 2 risk factors, and 643 (4.0%) had all 3 risk factors. All-cause mortality had occurred in 288 (44.8%) of the patients with all 3 risk factors at a mean follow-up of years. Baseline Characteristics As expected, there were several key differences in baseline recipient characteristics between patients with all 3 of these risk factors and those with zero metabolic risk factors (Table 1). Those with 3 risk factors were older (54.7 vs 49.7 years, p 0.001), and a higher proportion were males (82.9% vs 72.2%, p 0.001). Serum creatinine was also higher in these patients (1.48 vs 1.29, p 0.001). The indication for OHT was also different between populations, with those with all risk factors having a higher incidence of ischemic disease (63.6% vs 37.4%, p 0.001). A higher proportion of these patients were also bridged with ventricular assist devices (19.6% vs 15.8%, p 0.01). Finally, there were more African-American (16.2% vs 13.0%, p 0.02) and fewer Asian recipients (1.1% vs 2.7%, p 0.02) in the group with all risk factors. In examining donor characteristics, those with all risk factors had longer ischemic times (3.25 vs 3.10 hours, p 0.001), although this difference was likely clinically insignificant. Those with all risk factors also received organs from older donors (33.1 vs 31.0 years, p 0.001), and also tended to receive organs from male donors (79.5% vs 66.6%, p 0.001) with higher body mass index (BMI; 28.3 vs 25.3, p 0.001). A higher proportion of these patients were transplanted in the latter part of the study period (42.9% vs 32.5%, p 0.001), and they had longer wait times (282.2 vs days, p 0.001) as compared with patients with no risk factors. There was also a higher incidence of diabetes in donors of patients with all risk factors (3.0% vs 1.8%, p 0.04). Predictors of Mortality After OHT Given these significant yet expected baseline differences, a comprehensive univariate Cox regression analysis was conducted on all plausible recipient, donor, and transplant covariates to test their respective impact on mortality. The only variable that had more than 20% missing data was donor inotrope use, a factor that was not significantly associated with mortality post-oht (p

3 720 KILIC ET AL Ann Thorac Surg METABOLIC RISK FACTORS IN OHT 2012;93: Table 1. Comparison of Baseline Characteristics Between Patients With All 3 Metabolic Risk Factors and Patients With No Risk Factors Characteristic No Risk Factors (n 6,368) All 3 Risk Factors (n 643) Recipient Age (years) Female gender 1,772/6,368 (27.8%) 110/643 (17.1%) Race Caucasian 4,882/6,338 (77.0%) 483/642 (75.2%) 0.30 African American 823/6,338 (13.0%) 104/642 (16.2%) 0.02 Hispanic 432/6,338 (6.8%) 45/642 (7.0%) 0.85 Asian 169/6,338 (2.7%) 7/642 (1.1%) 0.02 Other 201/6,338 (3.2%) 10/642 (1.6%) 0.02 Serum creatinine (mg/dl) Etiology of heart failure Idiopathic dilated cardiomyopathy 3,015/6,368 (47.4%) 208/643 (32.4%) Ischemic heart disease 2,383/6,368 (37.4%) 409/643 (63.6%) Congenital heart disease 271/6,368 (4.3%) 2/643 (0.3%) Other etiology 699/6,368 (11.0%) 24/643 (3.7%) Mechanical ventilation 196/6,368 (3.1%) 16/643 (2.5%) 0.41 Intraaortic balloon pump 353/6,368 (5.5%) 36/643 (5.6%) 0.95 Bridging with VAD 1,006/6,368 (15.8%) 126/643 (19.6%) 0.01 Donor Age (years) Female gender 2,130/6,368 (33.5%) 132/643 (20.5%) Race Caucasian 4,538/6,368 (71.3%) 479/643 (74.5%) 0.08 African American 731/6,368 (11.5%) 78/643 (12.1%) 0.62 Hispanic 923/6,368 (14.5%) 72/643 (11.2%) 0.02 Asian 93/6,368 (1.5%) 6/642 (0.9%) 0.28 Other 83/6,368 (1.3%) 8/643 (1.2%) 0.90 BMI (kg/m 2 ) Diabetes mellitus 113/6,330 (1.8%) 19/640 (3.0%) 0.04 Hypertension 1,015/6,316 (16.1%) 92/641 (14.4%) 0.26 Recipient-donor matching Gender-matched 4,326/6,368 (67.9%) 499/643 (77.6%) Race-matched 4,004/6,368 (62.9%) 411/643 (63.9%) 0.60 HLA-matched (3 or more antigens) 432/5,237 (8.3%) 43/539 (8.0%) 0.83 ABO-matched a 5,386/6,367 (84.6%) 572/643 (89.0%) CMV-matched 3,271/6,331 (51.7%) 316/640 (49.4%) 0.27 Transplant Days on waitlist Ischemic time (hours) Later transplant year (2004 or later) 2,067/6,368 (32.5%) 276/643 (42.9%) a Blood group system (A, AB, B, O). BMI body mass index; CMV cytomegalovirus; HLA human leukocyte antigen; VAD ventricular assist device. 0.54). A total of 23 covariates were found to be associated (p 0.2) with mortality in univariate analysis, including the number of metabolic risk factors (hazard ratio [HR] 1.17 [1.13 to 1.20], p 0.001) (Table 2). These variables were entered into a multivariate analysis to evaluate the independent effect of these risk factors on mortality. In multivariable analysis adjusting for all significant covariates, the number of risk factors as a continuous variable was found to independently impact mortality, such that each additional risk factor was associated with a 16% higher risk of mortality after OHT (HR 1.16 [1.12 to 1.20], p 0.001). This effect was also seen when the number of risk factors was examined as a categoric variable. Moreover, the largest gap in increased mortality was seen in patients with 2 risk factors versus those with all 3 risk factors. Indeed, patients with 1 risk factor had 15% increased mortality versus those with 0 risk factors, those with 2 risk factors had 16% higher mortality than those with 1 risk factor, and those with all 3 risk factors had a 32% higher risk as compared with those with 2 risk factors. This exponential trend in increasing

4 Ann Thorac Surg KILIC ET AL 2012;93: METABOLIC RISK FACTORS IN OHT Table 2. Univariate and Multivariable Cox Regression Analysis: Impact of Number of Metabolic Risk Factors on Mortality After OHT Covariate Univariate Analysis Multivariable Analysis a 721 ADULT CARDIAC Increasing number of risk factors 1.17 ( ) ( ) (continuous) Number of risk factors (categoric) Zero Reference Reference ( ) ( ) ( ) ( ) ( ) ( ) a Adjusted for other significant variables associated (p 0.2) with mortality in exploratory univariate analysis, including United Network for Organ Sharing status, age, transplant type (biatrial versus bicaval), etiology of heart failure, serum creatinine, serum bilirubin, year of transplant, race, gender, mechanical ventilation prior to OHT, bridging with ventricular assist device, intraaortic balloon pump prior to OHT, ICU stay prior to OHT, ischemic time, recipient CMV status, donor age, donor gender, donor CMV status, donor cigarette use, donor diabetes, gender matched, and ABO matched. CI confidence interval; CMV cytomegalovirus; HR hazard ratio; ICU intensive care unit; OHT orthotopic heart transplantation. mortality with increasing risk factors was highly significant (r , p 0.001) (Fig 2). Individual Metabolic Risk Factors To test whether this impact of metabolic risk factors on mortality was largely driven by one of its components, the individual effects of diabetes mellitus, hypertension, and obesity were evaluated. In univariate Cox regression analysis, each of these components was associated with mortality (Table 3). Similarly, in a separate multivariable analysis incorporating the same 22 additional significant covariates, these individual components were each found to be a significant predictor of mortality independent of one another. In fact, diabetes independently increased the odds of mortality by 22%, hypertension by 10%, and obesity by 17% in multivariate analysis (each p 0.01). In summing the individual hazard ratios for these components, the expected increase in mortality would be 49%. However, when patients with all risk factors were compared with those with no risk factors, the increased mortality risk was 63% (HR 1.63 [1.42 to 1.88], p 0.001), which was a 14% absolute increase from this expected effect. In addition, Kaplan- Meier 5-year survival rates showed a significant trend, as an increasing number of risk factors was associated with progressively worse survival (Fig 3). The 5-year survival for patients with 0 risk factors was 74.7% compared with 63.1% for those with all 3 risk factors (p 0.001). Causes of Death The most common cause of death within 30 days in those with all 3 risk factors was primary graft failure (n 14; 28.6%). For mortalities within 1 year of OHT, the most common cause of death in those with all 3 metabolic disorders was bacterial septicemia (n 20; 17.2%) followed by primary graft failure (n 14; 12.1%). These causes of death were not statistically different from the rates occurring in those with no risk factors (each p 0.05). Comment This study evaluated the impact of an increasing number of metabolic risk factors, namely obesity, hypertension, Fig 2. Exponential increase in the risk of mortality after orthotopic heart transplantation with an increasing number of risk factors.

5 722 KILIC ET AL Ann Thorac Surg METABOLIC RISK FACTORS IN OHT 2012;93: Table 3. Univariate and Multivariable Cox Regression Analysis: Impact of Individual Risk Factors on Mortality After OHT Covariate Univariate Analysis Multivariate Analysis a Risk factors Hypertension 1.16 ( ) ( ) Obesity 1.16 ( ) ( ) Diabetes mellitus 1.22 ( ) ( ) a Adjusted for the same significant variables as in Table 2. CI confidence interval; HR hazard ratio; OHT orthotopic heart transplantation. and diabetes mellitus, on survival after OHT for endstage heart failure. There were several important findings in this analysis of over 15,000 patients. One finding was that most patients undergoing OHT have 0 or 1 of these risk factors, whereas only 22% had 2 or more. In fact, only 4% were found to have all 3 of these risk factors. Another important finding was that, as expected, the patients with all 3 risk factors were at baseline much different from those with no risk factors. As such, we decided to conduct our multivariate analysis adjusting for all other variables that were associated with survival as these populations significantly differed. After adjusting, we found that each of these individual risk factors increased the risk of mortality post-oht. The addition of each risk factor was found to significantly impact mortality both as a continuous variable as well as a categoric variable. Perhaps most notably, there was a highly significant exponential trend in increasing mortality with an increasing number of risk factors. Prevalence of Metabolic Disorders in the OHT Population The observed rates of diabetes, hypertension, and obesity in our study were slightly lower than what would be predicted in this patient population based on epidemiologic data [3]. Also, only 4% of patients had all 3 risk factors. While this may be due to an inability to capture all of these patients using this particular dataset, it may also be a reflection of hesitancy to offer OHT to these patients. For instance, in a review of over 27,000 OHT recipients, obese patients were found to have longer wait times and have lower odds of undergoing OHT as compared with non-obese patients [7]. This finding was echoed in our study as well where patients with all 3 risk factors had longer wait times for OHT than patients with no risk factors. This may indicate particular biases in transplanting certain populations. Impact of Individual Metabolic Risk Factors on Mortality The data regarding the effects of obesity on OHT outcomes are mixed. Several prior investigations have found worse graft and patient survival in obese patients [8 10]. A recent UNOS analysis found that a BMI of 30 to 34.9 did not represent an increased risk of mortality after OHT although patients with a BMI of 35 or higher did have worse survival [11]. Our study indicates a higher mortality risk in obese individuals with BMI 30 kg/m 2 or greater, although the magnitude of this risk was lower than that observed with diabetes. With regard to pre-oht diabetes, single-institution studies have also shown conflicting results [12 14]. A large multiinstitutional study utilizing the UNOS registry found that complicated diabetics specifically had worse survival as compared with nondiabetics and uncomplicated diabetics [15]. Although we did not stratify our diabetic cohort by severity, diabetes as a whole did impact mortality significantly in our analysis, as it was independently associated Fig 3. Kaplan-Meier 5-year survival stratified by number of risk factors.

6 Ann Thorac Surg KILIC ET AL 2012;93: METABOLIC RISK FACTORS IN OHT with a 22% increased risk. This was the largest adverse effect of the 3 metabolic risk factors. The impact of pre-oht hypertension on outcomes of OHT is much less studied than the other 2 risk factors. In our study pre-oht hypertension conferred a 10% increased risk of mortality independent of the effects of diabetes or obesity. Although pre-oht hypertension is not well studied, hypertension after OHT is a welldescribed complication that arises frequently and is commonly due to immunosuppressive agents [16]. Post-OHT hypertension is associated with cardiac allograft vasculopathy, the development of which represents an increased mortality risk to the recipient [17]. Impact of Metabolic Risk Factors in Combination An important question is whether the increased post-oht mortality when these metabolic risk factors are present in combination simply represents the sum of the increased mortality seen with each individual risk factor. In our study we noted that the hazard ratio for mortality in patients with all 3 risk factors was significantly higher than the sum of the ratios for its components. Additionally, although diabetes had the largest independent adverse effect (22% increased mortality risk), this was only 5% higher than the risk conferred by obesity and 12% higher than the risk from hypertension. In other words, no 1 risk factor had a predominant influence on the observed increased risk seen in patients with all 3 risk factors. Moreover, the largest jump in mortality was seen in going from 2 to 3 risk factors. The exponential trend seen in increasing mortality with an increasing number of risk factors was also highly significant. These data collectively suggest that while the presence of each of these risk factors is associated with an independent increase in mortality, their adverse impact is exponentially greater when all are present in combination. This observed phenomenon of an exponential, and not linear, rise in mortality with an increasing number of risk factors is known as multiplicative risk. Potential reasons for this observation in our study were that several unmeasured risk factors tend to cluster as more of the measured risk factors are present. These unmeasured mortality risk factors include a prothrombotic and proinflammatory state [18]. Implications in OHT There may be several potential clinical implications of this data. Foremost, the importance of lifestyle changes and medical therapy for these independent risk factors is underscored by this data. In addition, endothelial dysfunction is known to arise when multiple metabolic risk factors are present in combination. This may warrant closer surveillance protocols in recipients with several of these metabolic disorders as coronary endothelial dysfunction has been shown to predict allograft vasculopathy and cardiovascular mortality after OHT [19]. Limitations A limitation of this study is that the results are not generalizable to every OHT recipient. Moreover, the UNOS database is limited to OHT recipients within the United States and the impact of multiple metabolic risk factors in the international population where these disorders likely follow different patterns is unknown. In addition, the impact of these risk factors should they develop post-oht is unknown as this analysis was limited to pretransplant risk factors. Other limitations include those associated with the UNOS database, including errors in data entry and reporting biases. Conclusions This study analyzed over 15,000 patients to determine the impact of an increasing number of metabolic risk factors on mortality after OHT. Although the presence of each risk factor studied was associated with a significant increase in mortality, the largest adverse effect was seen when all 3 risk factors were present in combination. This exponential effect was greater in magnitude than would be expected in summing the individual effects of the components. Therefore, although different institutions define different levels of patient risk that they are willing to consider for OHT, these data should provide added caution as to transplanting those with all 3 risk factors, namely hypertension, diabetes mellitus, and obesity, particularly if other significant risk factors are present. Nonetheless, these data merit further prospective investigations to better delineate the impact of metabolic risk factors, especially when present in combination, on the OHT population, and to perhaps gain insight into the pathophysiological mechanisms as to how this clustering of metabolic disorders impacts cardiac allograft function and patient survival in this setting. This study was supported by Departmental Funds from the Department of Surgery, Johns Hopkins Hospital. There are no relevant disclosures. References Mokdad AH, Ford ES, Bowman BA, et al. Prevalence of obesity, diabetes, and obesity-related health risk factors, JAMA 2003;289: Isomaa B, Almgren P, Tuomi T, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001;24: Malik S, Wong ND, Franklin SS, et al. Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation 2004;110: Alberti KG, Eckel RH, Grundy SM, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Circulation 2009;120: Hiller TA, Fagot-Campagna A, Eschwège E, et al. Weight change and changes in the metabolic syndrome as the French population moves towards overweight: the D.E.S.I.R. cohort. Int J Epidemiol 2006;35: Ervin RB. Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: Untied States, Natl Health Stat Report 2009;13:1 7. ADULT CARDIAC

7 724 KILIC ET AL Ann Thorac Surg METABOLIC RISK FACTORS IN OHT 2012;93: Weiss ES, Allen JG, Russell SD, Shah AS, Conte JV. Impact of body mass index on organ allocation and mortality in orthotopic heart transplantation. J Heart Lung Transplant 2009;28: Grady KL, White-Williams C, Naftel D, et al. Are preoperative obesity and cachexia risk factors for post heart transplant morbidity and mortality: a multi-institutional study of preoperative weight-height indices. J Heart Lung Transplant 1999;18: Lietz K, John R, Burke EA, et al. Pretransplant cachexia and morbid obesity are predictors of increased mortality after heart transplantation. Transplantation 2001;72: Guisado Rasco A, Sobrino Márquez JM, Nevado Portero J, et al. Impact of overweight on survival and primary graft failure after heart transplantation. Transplant Proc 2010;42: Russo MJ, Hong KN, Davies RR, et al. The effect of body mass index on survival following heart transplantation: do outcomes support consensus guidelines? Ann Surg 2010;251: Marelli D, Laks H, Patel B, et al; University of California at Los Angeles Heart Transplant Group. Heart transplantation in patients with diabetes mellitus in the current era. J Heart Lung Transplant 2003;22: Morgan JA, John R, Weinberg AD, Colletti NJ, Mancini DM, Edwards NM. Heart transplantation in diabetic recipients: a decade review of 161 patients at Columbia Presbyterian. J Thorac Cardiovasc Surg 2004;127: Klingenberg R, Gleissner C, Koch A, et al. Impact of preoperative diabetes mellitus upon early and late survival after heart transplantation: a possible era effect. J Heart Lung Transplant 2005;24: Russo MJ, Chen JM, Hong KN, et al; Columbia University Heart Transplant Outcomes Research Group. Survival after heart transplantation is not diminished among recipients with uncomplicated diabetes mellitus: an analysis of the United Network of Organ Sharing database. Circulation 2006;114: Sánchez Lázaro IJ, Almenar Bonet L, Martínez-Dolz L, et al. Hypertension after heart transplantation: predictive factors and number and classes of drugs for its management. Transplant Proc 2008;40: Valantine H. Cardiac allograft vasculopathy after heart transplantation: risk factors and management. J Heart Lung Transplant 2004;23(5 Suppl):S Grundy SM. Metabolic syndrome: connecting and reconciling cardiovascular and diabetes worlds. J Am Coll Cardiol 2006;47: Hollenberg SM, Klein LW, Parrillo JE, et al. Coronary endothelial dysfunction after heart transplantation predicts allograft vasculopathy and cardiac death. Circulation 2001;104: INVITED COMMENTARY Obesity affects 50% to 60% of a nation s population and can be associated with insulin resistance and the metabolic syndrome (MetS) [1]. The prevalence of MetS in the global population is 20% to 30% and people with MetS are twice as likely to die of cardiovascular disease [2]. As more patients with advanced heart failure are presented for evaluation for heart transplantation, such risk factors are often overlooked or marginalized in an effort to provide care. Kilic and colleagues [3] queried the United Network for Organ Sharing (UNOS) database to evaluate the impact of risk factors for MetS and their effect on mortality after orthotopic heart transplantation (OHT). Their work demonstrated that an increasing number of metabolic risk factors contributed to increased mortality and decreased survival in OHT patients. Are the metabolic risk factors reviewed from the UNOS database in this review substantial enough to define them as the MetS? The definition for MetS for use in clinical practice include central obesity measured by waist circumference (WC), plus any two of the following: raised triglyceride 150 mg/dl; reduced high density lipoprotein cholesterol 40 mg/dl; systolic blood pressure 130; raised fasting blood sugar; or type 2 diabetes mellitus [4]. The World Health Organization, The Europe Group for the study of Insulin Resistance, The National Cholesterol Education Program, the American Association of Clinical Endocrinology, the International Diabetic Federation, and the American Heart Association/National Heart, Lung, and Blood Institute have attempted to incorporate all the different parameters used to define MetS. The core manifestations of the MetS which prevail throughout all definitions remain central obesity and insulin resistance, key data missing from the UNOS database [5,6]. The UNOS database does not contain WC, triglyceride, high density lipoprotein, or blood sugar data; the authors substituted body mass index (BMI) 30 kg/m 2 for obesity, history of hypertension, and diabetes for risk factors to evaluate for MetS. Although there is a well defined gradient relationship between the level of BMI and probability of the MetS, most obese individuals do not have MetS and conversely most patients with MetS are not obese or overweight. Central obesity, measured simply by WC, is more indicative of the MetS then BMI across all BMI groups for both men and women [6]. Overall, adiposity defined by BMI is not a surrogate marker for insulin resistance. Despite the sample size and their significant finding that multiple metabolic risk factors in OHT are associated with mortality, this study does not use the standard accepted definitions of MetS. The core manifestations of MetS, central obesity and insulin resistance, were not reported in this review due to the lack of data available in the database. To optimize long-term survival for these patients, clinicians should carefully evaluate candidates for acceptance for transplantation, envision steroid-sparing immunosuppression protocols, and acknowledge and create an algorithm for post-oht physical rehabilitation to minimize the development of MetS. A prospective treatment plan will mitigate and hopefully improve long-term survival and quality of life in patients with metabolic risk factors. Nicholas C. Cavarocchi, MD Department of Surgery Thomas Jefferson University 1025 Walnut St, Ste 605E Philadelphia, PA nicholas.cavarocchi@jefferson.edu 2012 by The Society of Thoracic Surgeons /$36.00 Published by Elsevier Inc doi: /j.athoracsur