International Journal of Cardiology 176 (2014) 1356–1358
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
Obesity paradox in patients with atrial fibrillation and heart failure Juan Wang, Yan-min Yang ⁎, Jun Zhu ⁎, Han Zhang, Xing-hui Shao Emergency and Intensive Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100037,China
a r t i c l e
i n f o
Article history: Received 27 July 2014 Accepted 28 July 2014 Available online 6 August 2014 Keywords: Atrial fibrillation Heart failure Body mass index Obesity
Obesity is an independent risk factor for cardiovascular morbidity and mortality, also a risk factor for the development of atrial fibrillation (AF), and associated with increased risk of incident heart failure (HF) [1]. But in patients with certain established cardiovascular diseases, including myocardial infarction (MI) [2], and HF [3], overweight and obesity were associated with a lower risk of mortality—the “obesity paradox”. However, in patients with AF concomitant HF, the role of body mass index (BMI) in the risk of mortality is not defined, the prognosis significance of obesity in the setting of established HF and AF is not clear. Given these interconnection between obesity and AF, and obesity and HF, we sought to determine the relation between BMI and mortality in patients with established AF and HF. We enrolled 2016 patients with diagnosed AF who presented to an emergence department at 20 hospitals in China from November 2008 to October 2011. A subgroup of 806 AF and HF patients enrolled in this study. The patients were divided into 4 different BMI (BMIs were calculated by dividing weight in kilograms by the square of height in meters, and height and weight data were recorded at the baseline visit) categories according to Chinese obesity working group: underweight (b 18.5 kg/m2, n = 101 [12.5%]), normal-weight (18.5 to b24 kg/m2, n = 373 [46.3%]), overweight (24 to b28 kg/m2, n = 230 [28.5%]), obese (≥ 28 kg/m2, n = 102 [12.7%]) [4]. Follow-up was completed in November 2012. The endpoints for current analysis were all-cause death and cardiovascular mortality during the 12-month follow-up. Univariate and multivariate Cox regression analyses were
⁎ Corresponding authors. Tel.: +86 10 88396294; fax: +86 10 88364591. E-mail addresses: [email protected] (Y. Yang), [email protected] (J. Zhu).
http://dx.doi.org/10.1016/j.ijcard.2014.07.264 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
performed to determine which variables were predictive of all-cause mortality and cardiovascular mortality using SPSS 19.0 (IBM Corporation, New York, NY, USA). All tests were two sided and P b 0.05 was considered statistically significant. A total of 806 patients were included in the analysis, of those, 464 (57.6%) were female. The average age was 68.4 ± 12.9 years and mean BMI was 23.3 ± 4.1 kg/m2. Overweight and obese patients were less female, more current smokers, and had more co-morbidity (coronary artery disease (CAD), MI, hypertension, sleep apnea, and diabetes mellitus (DM)) as compared with normal weight patients (Table 1). Patients in the overweight and obese categories were more likely to be on calcium channel blocker, angiotensin receptor blocker, lipid lowering agents, and antiplatelet therapy compared with normal weight and underweight patients (Table 1). A total of 153 deaths and 113 cardiovascular deaths occurred over the 12-month follow-up. All-cause mortality risk is lower in patients with overweight (HR: 0.41, 95% CI: 0.26–0.64, P b 0.001) and obesity (HR: 0.46, 95% CI: 0.25–0.83, P = 0.011) compared with patients with normal weight (reference group) (Fig. 1). Cardiovascular mortality risk (unadjusted) are lower in overweight (HR: 0.43, 95% CI: 0.26– 0.73, P = 0.002) and obese (HR: 0.49, 95% CI: 0.24–0.97, P = 0.042) patients compared with normal weight. The final multivariate Cox proportional models of predictors for all-cause mortality, and cardiovascular mortality based on stepwise selection. After adjustment for multiple relevant co-variables (age, sex, AF type, current smoking, comorbidities, medications), as a continuous variable, BMI was not a risk factor for all-cause mortality (HR: 0.91, 95% CI: 0.87–0.95; P b 0.001), and for cardiovascular mortality (HR: 0.91, 95% CI: 0.86–0.96; P b 0.001); as a category variable, obesity (HR: 0.50, 95% CI: 0.26– 0.94, P = 0.032) and overweight (HR: 0.40, 95% CI: 0.25–0.63, P b 0.001) were significantly associated with a lower risk of all-cause mortality, and overweight also with a lower cardiovascular death (HR: 0.45, 95% CI 0.26–0.76, P = 0.003) compared to normal weight patients. The most important result from this study is that overweight and obese patients with AF and HF had better survival when compared with normal weight patients. Our study reports for the first time that an “obesity paradox” was observed in patients with AF and HF. There are several possible explanations for the decreased risk of mortality observed among obese and overweight patients. It has been suggested that obese patients who present earlier have more recognizable and aggressively treated co-morbidities, like hypertension, CAD, and DM. Corresponding to the higher incidence of these diseases, in our study, higher BMI was associated with increased use of standard medical therapies such as CCB, ARB, antiplatelet therapy and lipid
J. Wang et al. / International Journal of Cardiology 176 (2014) 1356–1358
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Table 1 Baseline characteristics of 806 atrial fibrillation and heart failure patients by body mass index category. Underweight b 18.5 (n = 101)
Normal weight 18.5 to 24 (n = 373)
Overweight 24 to 28 (n = 230)
Obese ≥ 30 (n = 102)
69.9 ± 15.1 72 (60.1) 16 (15.8)
68.0 ± 13.0 224 (71.3) 81 (21.7)
67.6 ± 12.3 110 (47.8) 70 (30.4)
70.1 ± 11.0 58 (56.9) 34 (33.3)
14 (13.9) 14 (13.9) 73 (72.3)
76 (20.4) 54 (14.5) 243 (65.1)
53 (23.0) 37 (16.1) 140 (60.9)
14 (13.7) 27 (26.5) 61 (59.8)
Co-morbidities MI Hypertension Valvular heart disease LVH Previous stroke Dementia COPD Sleep apnea Diabetes mellitus Hyperthyroidism Previous major bleeding
5 (5.0) 35 (34.7) 42 (41.6) 23 (22.8) 18 (17.8) 3 (3.0) 21 (20.8) 0 (0.0) 5 (5.0) 4 (4.0) 5 (5.0)
29 (7.8) 175 (46.9) 159 (42.6) 96 (25.7) 59 (15.8) 13 (3.5) 52 (13.9) 7 (1.9) 50 (13.4) 9 (2.4) 9 (2.4)
37 (16.1) 124 (53.9) 65 (28.3) 71 (30.9) 43 (18.7) 8 (3.5) 38 (16.5) 13 (5.7) 42 (18.3) 2 (0.9) 8 (3.5)
14 (13.7) 82 (80.4) 12 (11.8) 32 (31.4) 21 (20.6) 3 (2.9) 12 (11.8) 12 (11.8) 28 (27.5) 3 (2.9) 5 (4.9)
0.002 b0.001 b0.001 0.286 0.650 0.988 0.247 b0.001 b0.001 0.305 0.461
Medications Diuretic CCB Beta-blocker ARB ACEI Digoxin Lipid lowering agents Antiplatelet therapy Oral anticoagulant therapy Antiarrhythmics
74 (73.3) 16 (15.8) 44 (43.6) 8 (7.9) 33 (32.7) 71 (70.3) 8 (7.9) 56 (55.4) 30 (29.7) 14 (13.9)
285 (76.4) 85 (22.8) 182 (48.8) 52 (13.9) 135 (36.2) 245 (65.7) 84 (22.5) 252 (67.6) 118 (31.6) 47 (12.6)
172 (74.8) 55 (23.9) 123 (53.5) 49 (21.3) 98 (42.6) 141 (61.3) 71 (30.9) 161 (70.0) 76 (33.0) 35 (15.2)
70 (68.6) 35 (34.3) 56 (54.9) 41 (40.2) 40 (39.2) 43 (42.2) 39 (38.2) 78 (76.5) 20 (19.6) 17 (16.7)
0.447 0.019 0.265 b0.001 0.276 b0.001 b0.001 0.011 0.083 0.684
Age, years Female Current smoking Type of AF Persistent Paroxysmal Permanent
P-value 0.005 0.001 0.003 0.026
AF, atrial fibrillation; MI, myocardial infarction; LVH, left ventricular hypertrophy; COPD, chronic obstructive pulmonary disease; CCB, calcium channel blockers; ARB, angiotensin receptor blocker; ACEI, angiotensin-converting enzyme inhibitor.
lowering agents. As these agents have been shown to reduce mortality in patients with AF [5], and with HF [6], medical treatment differences might account for some of the difference in prognosis. Perhaps the relation between increasing BMI and improved outcomes is not physiologic but rather completely explained by confounding. However, the decreased risk of mortality in overweight patients persisted after adjustment for both of these potential confounders. Other possible explanations for obesity paradox are that the obesity may protect against malnutrition and energy wastage. HF is a catabolic state with a high resting metabolic rate, the development of wasting, characterized by loss of muscle, bone, and fat, is a marker of more severe disease [7]. Studies have demonstrated that patients with advanced HF are malnourished, with an energy and protein intake that is inadequate to meet their energy requirements [8]. Moreover, the metabolic cost, combined with other changes, may lead to cachexia which carries a poor prognosis. It is unclear as to the cause of cardiac cachexia, but activated inflammatory and neuro-hormonal mediators, together with excessive sympathetic activation, are implicated [7]. Meeting the increased metabolic demand of chronic heart failure is likely to be more readily sustained with an increased body reserved of bulk. It has been suggested that overweight and obese individuals with HF may have a higher metabolic reserve and may tolerate the metabolic stresses better than lean individuals with HF [9]. Patients with HF who are underweight or at a healthy weight may not have enough metabolic reserve to overcome the further increased catabolic stress resulting from a HF. These patients may be particularly vulnerable to the adverse pathophysiologic consequences of a limited metabolic reserve. Overweight and obese patients may have more metabolic reserve than lean patients, allowing a greater tolerance for metabolic stress [10]. In conclusion, the present study shows that obese or overweight have better survival when compared with normal weight or underweight in Chinese AF and HF patients. More studies of the association between BMI and survival in these subgroups with AF are required.
Whether or not the effect of obesity on survival in these groups is causal will require longitudinal and preferably intervention studies of weight change in obese AF individuals. The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. References [1] Ghoorah K, Campbell P, Kent A, et al. Obesity and cardiovascular outcomes: a review. Eur Heart J Acute Cardiovasc Care 2014 Published online before print. http://dx.doi. org/10.1177/2048872614523349. [2] Cepeda-Valery B, Slipczuk L, Figueredo VM, et al. Association between obesity and infarct size: insight into the obesity paradox. Int J Cardiol 2013;167:604–6. [3] Oreopoulos A, Padwal R, Kalantar-Zadeh K, et al. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J 2008;156:13–22. [4] Zhou BF. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci 2002;15:83–96. [5] Nieuwlaat R, Prins MH, Le Heuzey JY, et al. Prognosis, disease progression, and treatment of atrial fibrillation patients during 1 year: follow-up of the Euro Heart Survey on atrial fibrillation. Eur Heart J 2008;29:1181–9. [6] Futter JE, Cleland JG, Clark AL. Body mass indices and outcome in patients with chronic heart failure. Eur J Heart Fail 2011;13:207–13. [7] Berry C, Clark AL. Catabolism in chronic heart failure. Eur Heart J 2000;21:521–32. [8] Anker SD, Negassa A, Coats AJ, et al. Prognostic importance of weight loss in chronic heart failure and the effect of treatment with angiotensin-converting-enzyme inhibitors: an observational study. Lancet 2003;361:1077–83. [9] Imbeault P, Tremblay A, Simoneau JA, et al. Weight loss-induced rise in plasma pollutant is associated with reduced skeletal muscle oxidative capacity. Am J Physiol Endocrinol Metab 2002;282:E574–9. [10] Lavie CJ, Alpert MA, Arena R, et al. Impact of obesity and the obesity paradox on prevalence and prognosis in heart failure. JACC Heart Fail 2013;1:93–102.
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J. Wang et al. / International Journal of Cardiology 176 (2014) 1356–1358
Fig. 1. The Kaplan–Meyer event rates and survival curves for A all-cause mortality, B cardiovascular mortality, in patients with AF and HF according to the different BMI categories. Hazard ratios with 95% CI are presented.
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Letter to the Editor
Obesity paradox in patients with atrial fibrillation and heart failure Juan Wang, Yan-min Yang ⁎, Jun Zhu ⁎, Han Zhang, Xing-hui Shao Emergency and Intensive Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100037,China
a r t i c l e
i n f o
Article history: Received 27 July 2014 Accepted 28 July 2014 Available online 6 August 2014 Keywords: Atrial fibrillation Heart failure Body mass index Obesity
Obesity is an independent risk factor for cardiovascular morbidity and mortality, also a risk factor for the development of atrial fibrillation (AF), and associated with increased risk of incident heart failure (HF) [1]. But in patients with certain established cardiovascular diseases, including myocardial infarction (MI) [2], and HF [3], overweight and obesity were associated with a lower risk of mortality—the “obesity paradox”. However, in patients with AF concomitant HF, the role of body mass index (BMI) in the risk of mortality is not defined, the prognosis significance of obesity in the setting of established HF and AF is not clear. Given these interconnection between obesity and AF, and obesity and HF, we sought to determine the relation between BMI and mortality in patients with established AF and HF. We enrolled 2016 patients with diagnosed AF who presented to an emergence department at 20 hospitals in China from November 2008 to October 2011. A subgroup of 806 AF and HF patients enrolled in this study. The patients were divided into 4 different BMI (BMIs were calculated by dividing weight in kilograms by the square of height in meters, and height and weight data were recorded at the baseline visit) categories according to Chinese obesity working group: underweight (b 18.5 kg/m2, n = 101 [12.5%]), normal-weight (18.5 to b24 kg/m2, n = 373 [46.3%]), overweight (24 to b28 kg/m2, n = 230 [28.5%]), obese (≥ 28 kg/m2, n = 102 [12.7%]) [4]. Follow-up was completed in November 2012. The endpoints for current analysis were all-cause death and cardiovascular mortality during the 12-month follow-up. Univariate and multivariate Cox regression analyses were
⁎ Corresponding authors. Tel.: +86 10 88396294; fax: +86 10 88364591. E-mail addresses: [email protected] (Y. Yang), [email protected] (J. Zhu).
http://dx.doi.org/10.1016/j.ijcard.2014.07.264 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.
performed to determine which variables were predictive of all-cause mortality and cardiovascular mortality using SPSS 19.0 (IBM Corporation, New York, NY, USA). All tests were two sided and P b 0.05 was considered statistically significant. A total of 806 patients were included in the analysis, of those, 464 (57.6%) were female. The average age was 68.4 ± 12.9 years and mean BMI was 23.3 ± 4.1 kg/m2. Overweight and obese patients were less female, more current smokers, and had more co-morbidity (coronary artery disease (CAD), MI, hypertension, sleep apnea, and diabetes mellitus (DM)) as compared with normal weight patients (Table 1). Patients in the overweight and obese categories were more likely to be on calcium channel blocker, angiotensin receptor blocker, lipid lowering agents, and antiplatelet therapy compared with normal weight and underweight patients (Table 1). A total of 153 deaths and 113 cardiovascular deaths occurred over the 12-month follow-up. All-cause mortality risk is lower in patients with overweight (HR: 0.41, 95% CI: 0.26–0.64, P b 0.001) and obesity (HR: 0.46, 95% CI: 0.25–0.83, P = 0.011) compared with patients with normal weight (reference group) (Fig. 1). Cardiovascular mortality risk (unadjusted) are lower in overweight (HR: 0.43, 95% CI: 0.26– 0.73, P = 0.002) and obese (HR: 0.49, 95% CI: 0.24–0.97, P = 0.042) patients compared with normal weight. The final multivariate Cox proportional models of predictors for all-cause mortality, and cardiovascular mortality based on stepwise selection. After adjustment for multiple relevant co-variables (age, sex, AF type, current smoking, comorbidities, medications), as a continuous variable, BMI was not a risk factor for all-cause mortality (HR: 0.91, 95% CI: 0.87–0.95; P b 0.001), and for cardiovascular mortality (HR: 0.91, 95% CI: 0.86–0.96; P b 0.001); as a category variable, obesity (HR: 0.50, 95% CI: 0.26– 0.94, P = 0.032) and overweight (HR: 0.40, 95% CI: 0.25–0.63, P b 0.001) were significantly associated with a lower risk of all-cause mortality, and overweight also with a lower cardiovascular death (HR: 0.45, 95% CI 0.26–0.76, P = 0.003) compared to normal weight patients. The most important result from this study is that overweight and obese patients with AF and HF had better survival when compared with normal weight patients. Our study reports for the first time that an “obesity paradox” was observed in patients with AF and HF. There are several possible explanations for the decreased risk of mortality observed among obese and overweight patients. It has been suggested that obese patients who present earlier have more recognizable and aggressively treated co-morbidities, like hypertension, CAD, and DM. Corresponding to the higher incidence of these diseases, in our study, higher BMI was associated with increased use of standard medical therapies such as CCB, ARB, antiplatelet therapy and lipid
J. Wang et al. / International Journal of Cardiology 176 (2014) 1356–1358
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Table 1 Baseline characteristics of 806 atrial fibrillation and heart failure patients by body mass index category. Underweight b 18.5 (n = 101)
Normal weight 18.5 to 24 (n = 373)
Overweight 24 to 28 (n = 230)
Obese ≥ 30 (n = 102)
69.9 ± 15.1 72 (60.1) 16 (15.8)
68.0 ± 13.0 224 (71.3) 81 (21.7)
67.6 ± 12.3 110 (47.8) 70 (30.4)
70.1 ± 11.0 58 (56.9) 34 (33.3)
14 (13.9) 14 (13.9) 73 (72.3)
76 (20.4) 54 (14.5) 243 (65.1)
53 (23.0) 37 (16.1) 140 (60.9)
14 (13.7) 27 (26.5) 61 (59.8)
Co-morbidities MI Hypertension Valvular heart disease LVH Previous stroke Dementia COPD Sleep apnea Diabetes mellitus Hyperthyroidism Previous major bleeding
5 (5.0) 35 (34.7) 42 (41.6) 23 (22.8) 18 (17.8) 3 (3.0) 21 (20.8) 0 (0.0) 5 (5.0) 4 (4.0) 5 (5.0)
29 (7.8) 175 (46.9) 159 (42.6) 96 (25.7) 59 (15.8) 13 (3.5) 52 (13.9) 7 (1.9) 50 (13.4) 9 (2.4) 9 (2.4)
37 (16.1) 124 (53.9) 65 (28.3) 71 (30.9) 43 (18.7) 8 (3.5) 38 (16.5) 13 (5.7) 42 (18.3) 2 (0.9) 8 (3.5)
14 (13.7) 82 (80.4) 12 (11.8) 32 (31.4) 21 (20.6) 3 (2.9) 12 (11.8) 12 (11.8) 28 (27.5) 3 (2.9) 5 (4.9)
0.002 b0.001 b0.001 0.286 0.650 0.988 0.247 b0.001 b0.001 0.305 0.461
Medications Diuretic CCB Beta-blocker ARB ACEI Digoxin Lipid lowering agents Antiplatelet therapy Oral anticoagulant therapy Antiarrhythmics
74 (73.3) 16 (15.8) 44 (43.6) 8 (7.9) 33 (32.7) 71 (70.3) 8 (7.9) 56 (55.4) 30 (29.7) 14 (13.9)
285 (76.4) 85 (22.8) 182 (48.8) 52 (13.9) 135 (36.2) 245 (65.7) 84 (22.5) 252 (67.6) 118 (31.6) 47 (12.6)
172 (74.8) 55 (23.9) 123 (53.5) 49 (21.3) 98 (42.6) 141 (61.3) 71 (30.9) 161 (70.0) 76 (33.0) 35 (15.2)
70 (68.6) 35 (34.3) 56 (54.9) 41 (40.2) 40 (39.2) 43 (42.2) 39 (38.2) 78 (76.5) 20 (19.6) 17 (16.7)
0.447 0.019 0.265 b0.001 0.276 b0.001 b0.001 0.011 0.083 0.684
Age, years Female Current smoking Type of AF Persistent Paroxysmal Permanent
P-value 0.005 0.001 0.003 0.026
AF, atrial fibrillation; MI, myocardial infarction; LVH, left ventricular hypertrophy; COPD, chronic obstructive pulmonary disease; CCB, calcium channel blockers; ARB, angiotensin receptor blocker; ACEI, angiotensin-converting enzyme inhibitor.
lowering agents. As these agents have been shown to reduce mortality in patients with AF [5], and with HF [6], medical treatment differences might account for some of the difference in prognosis. Perhaps the relation between increasing BMI and improved outcomes is not physiologic but rather completely explained by confounding. However, the decreased risk of mortality in overweight patients persisted after adjustment for both of these potential confounders. Other possible explanations for obesity paradox are that the obesity may protect against malnutrition and energy wastage. HF is a catabolic state with a high resting metabolic rate, the development of wasting, characterized by loss of muscle, bone, and fat, is a marker of more severe disease [7]. Studies have demonstrated that patients with advanced HF are malnourished, with an energy and protein intake that is inadequate to meet their energy requirements [8]. Moreover, the metabolic cost, combined with other changes, may lead to cachexia which carries a poor prognosis. It is unclear as to the cause of cardiac cachexia, but activated inflammatory and neuro-hormonal mediators, together with excessive sympathetic activation, are implicated [7]. Meeting the increased metabolic demand of chronic heart failure is likely to be more readily sustained with an increased body reserved of bulk. It has been suggested that overweight and obese individuals with HF may have a higher metabolic reserve and may tolerate the metabolic stresses better than lean individuals with HF [9]. Patients with HF who are underweight or at a healthy weight may not have enough metabolic reserve to overcome the further increased catabolic stress resulting from a HF. These patients may be particularly vulnerable to the adverse pathophysiologic consequences of a limited metabolic reserve. Overweight and obese patients may have more metabolic reserve than lean patients, allowing a greater tolerance for metabolic stress [10]. In conclusion, the present study shows that obese or overweight have better survival when compared with normal weight or underweight in Chinese AF and HF patients. More studies of the association between BMI and survival in these subgroups with AF are required.
Whether or not the effect of obesity on survival in these groups is causal will require longitudinal and preferably intervention studies of weight change in obese AF individuals. The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology. Conflict of interest The authors report no relationships that could be construed as a conflict of interest. References [1] Ghoorah K, Campbell P, Kent A, et al. Obesity and cardiovascular outcomes: a review. Eur Heart J Acute Cardiovasc Care 2014 Published online before print. http://dx.doi. org/10.1177/2048872614523349. [2] Cepeda-Valery B, Slipczuk L, Figueredo VM, et al. Association between obesity and infarct size: insight into the obesity paradox. Int J Cardiol 2013;167:604–6. [3] Oreopoulos A, Padwal R, Kalantar-Zadeh K, et al. Body mass index and mortality in heart failure: a meta-analysis. Am Heart J 2008;156:13–22. [4] Zhou BF. Predictive values of body mass index and waist circumference for risk factors of certain related diseases in Chinese adults—study on optimal cut-off points of body mass index and waist circumference in Chinese adults. Biomed Environ Sci 2002;15:83–96. [5] Nieuwlaat R, Prins MH, Le Heuzey JY, et al. Prognosis, disease progression, and treatment of atrial fibrillation patients during 1 year: follow-up of the Euro Heart Survey on atrial fibrillation. Eur Heart J 2008;29:1181–9. [6] Futter JE, Cleland JG, Clark AL. Body mass indices and outcome in patients with chronic heart failure. Eur J Heart Fail 2011;13:207–13. [7] Berry C, Clark AL. Catabolism in chronic heart failure. Eur Heart J 2000;21:521–32. [8] Anker SD, Negassa A, Coats AJ, et al. Prognostic importance of weight loss in chronic heart failure and the effect of treatment with angiotensin-converting-enzyme inhibitors: an observational study. Lancet 2003;361:1077–83. [9] Imbeault P, Tremblay A, Simoneau JA, et al. Weight loss-induced rise in plasma pollutant is associated with reduced skeletal muscle oxidative capacity. Am J Physiol Endocrinol Metab 2002;282:E574–9. [10] Lavie CJ, Alpert MA, Arena R, et al. Impact of obesity and the obesity paradox on prevalence and prognosis in heart failure. JACC Heart Fail 2013;1:93–102.
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Fig. 1. The Kaplan–Meyer event rates and survival curves for A all-cause mortality, B cardiovascular mortality, in patients with AF and HF according to the different BMI categories. Hazard ratios with 95% CI are presented.
