ORIGINAL RESEARCH Association of Body Mass Index With Clinical Outcomes in Patients With Atrial Fibrillation: A Report From the FANTASIIA Registry Vicente Bertomeu-Gonzalez, MD, PhD;* Jose Moreno-Arribas, MD, PhD;* Marıa Asunci on Esteve-Pastor, MD, PhD; Inmaculada Roldan-Rabadan, MD, PhD; Javier Mu~ na-Mıguez, PhD; Martın Ruiz-Ortiz, MD, PhD; niz, MD, PhD; Paula Ra~  Angel Cequier, MD, PhD; Vicente Bertomeu-Martınez, MD, PhD; Lina Badim on, MD, PhD; Manuel Anguita, MD, PhD; Gregory Y. H. Lip, MD; Francisco Marın, MD, PhD; on behalf of FANTASIIA Study Investigators† Background-—Obesity and atrial fibrillation (AF) frequently coexist and independently increase mortality. We sought to assess the association between obesity and adverse events in patients receiving oral anticoagulants for AF. Methods and Results-—Consecutive AF outpatients receiving anticoagulant agents (both vitamin K antagonists and direct oral anticoagulants) were recruited into the FANTASIIA (Atrial fibrillation: influence of the level and type of anticoagulation on the incidence of ischemic and hemorrhagic stroke) registry. This observational, multicenter, and prospective registry of AF patients analyzes the quality of anticoagulation, incidence of events, and differences between oral anticoagulant therapies. We analyzed baseline patient characteristics according to body mass index, normal: <25 kg/m2, overweight: 25–30 kg/m2, and obese: ≥30 kg/m2), assessing all- cause mortality, stroke, major bleeding and major adverse cardiovascular events (a composite of ischemic stroke, myocardial infarction, and total mortality) at 3 years’ follow-up. In this secondary prespecified substudy, the association of weight on prognosis was evaluated. We recruited 1956 patients (56% men, mean age 73.89.4 years): 358 (18.3%) had normal body mass index, 871 (44.5%) were overweight, and 727 (37.2%) were obese. Obese patients were younger (P<0.01) and had more comorbidities. Mean time in the therapeutic range was similar across body mass index categories (P=0.42). After a median follow-up of 1070 days, 255 patients died (13%), 45 had a stroke (2.3%), 146 a major bleeding episode (7.5%) and 168 a major adverse cardiovascular event (8.6%). Event rates were similar between groups for total mortality (P=0.29), stroke (P=0.90), major bleeding (P=0.31), and major adverse cardiovascular events (P=0.24). On multivariate Cox analysis, body mass index was not independently associated with all-cause mortality, cardiovascular mortality, stroke, major bleeding, or major adverse cardiovascular events. Downloaded from http://ahajournals.org by on October 10, 2023 Conclusions-—In this prospective cohort of patients anticoagulated for AF, obesity was highly prevalent and was associated with more comorbidities, but not with poor prognosis. ( J Am Heart Assoc. 2020;9:e013789. DOI: 10.1161/JAHA.119.013789.) Key Words: atrial fibrillation • mortality • obesity • prognosis • risk factors O besity and atrial fibrillation (AF) are increasing in epidemic proportions worldwide, and both increase the incidence of cardiovascular events.1,2 AF has long been recognized as a risk factor for stroke, and its association with all-cause mortality is also widely acknowledged.3 While obesity significantly increases the risk of many metabolic From the Department of Cardiology, Hospital Universitario de San Juan de Alicante, Universidad Miguel Hernandez, Alicante, Spain (V.B.-G., J.M.-A., V.B.M.); Department of Cardiology, Hospital Clınico Universitario Virgen de la Arrixaca, Instituto Murciano de Investigacion Biosanitaria (IMIB-Arrixaca), Murcia, Spain (M.A.E.-P., F.M.); Department of Cardiology, Hospital La Paz, Madrid, Spain (I.R.-R.); Instituto Universitario de Ciencias de la Salud, Instituto de Investigacion Biomedica de A Coru~na (INIBIC), Universidade da Coru~na, La Coru~na, Spain (J.M.); ODDS, SL, A Coru~na, Spain (P.R.-M.); Department of Cardiology, Hospital Universitario Reina Sofıa, Cordoba, Spain (M.R.-O., M.A.); Department of Cardiology, Hospital de Bellvitge, Barcelona, Spain (A.C.); Cardiovascular Research Center (CSIC-ICCC), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain (L.B.); Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart & Chest Hospital, Liverpool, United Kingdom (G.Y.H.L.); Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark (G.Y.H.L.); Centro de Investigacion Biomedica en Red-Enfermedades Cardiovasculares: CIBER-CV, Madrid, Spain (V.B.-G., J.M.-A., M.A.E.-P., I.R.-R., J.M., A.C., V.B.M., L.B., F.M.). Accompanying Appendix, Tables S1 through S3 are available at https://www.ahajournals.org/doi/suppl/10.1161/JAHA.119.013789 *Dr Bertomeu-Gonzalez and Dr Moreno-Arribas contributed equally to this work. † A complete list of the FANTASIIA Study Investigators can be found in the Appendix. Correspondence to: Marıa Asuncion Esteve-Pastor, MD, PhD, Department of Cardiology, Hospital Clınico Universitario Virgen de la Arrixaca, IMIB-Arrixaca. Ctra. Madrid-Cartagena s/n 30120, Murcia, Spain. E-mail: masunep@gmail.com Received June 29, 2019; accepted October 4, 2019. ª 2019 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non- commercial and no modifications or adaptations are made. DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 1 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH VKA. The data that support the findings of this study are Clinical Perspective available from the corresponding author upon reasonable request. What Is New? • Obesity is not associated with prognosis in patients anticoagulated for atrial fibrillation. Study Population Between June 2013 and March 2014, outpatients with What Are the Clinical Implications? confirmed diagnosis of paroxysmal, persistent, or permanent • While obesity is one of the main risk factors we target to AF were prospectively enrolled. All patients included had been prevent and treat cardiovascular disease, in the setting of receiving oral anticoagulation for at least 6 months at the atrial fibrillation obese patients show similar incidence of time of recruitment. By design, each investigator included 16 mortality and nonfatal adverse clinical outcomes. patients taking VKA and 4 patients who were taking direct oral anticoagulants. Eighty investigators, working in 50 outpatient clinics, performed the study. Exclusion criteria and cardiovascular diseases,1–3 it is also associated with a were as follows: patients with valvular heart disease lower incidence of events once the cardiovascular disease has (rheumatic valve disease, moderate–severe valve disease, been established, as has been proven with conditions such as and prosthesis or valve repair surgery), age younger than diabetes mellitus, chronic kidney disease, stroke, dementia, 18 years, or with recent hospital admission. The study aimed coronary artery disease, and heart failure.4–8 This phe- to assess the influence of the anticoagulant treatment in nomenon is known as the “obesity paradox.” prognosis; thus, patients admitted or with an admission in the Obesity has been related to the incidence and progression prior 3 months were excluded. All patients provided signed of AF,9,10 but its effect on prognosis in AF patients is informed consent. controversial.11 Two subanalyses from randomized clinical The study complied with the ethical principles of the trials have shown lower rates of adverse events in patients Declaration of Helsinki and Good Clinical Practice Guidelines. with higher body mass index (BMI), the AFFIRM (Atrial It was approved by the Spanish Agency of Medicine and Fibrillation Follow-Up Investigation of Rhythm Management)12 Health Products as a prospective follow-up postauthorization and ARISTOTLE (Apixaban for Reduction in Stroke and Other study (approval number SEC-ACO-2012–01) and by the Ethics Thromboembolic Events in Atrial Fibrillation) trials,13 but this Downloaded from http://ahajournals.org by on October 10, 2023 Committee of the Hospital Universitario San Juan de Alicante. observation has not been confirmed in observational reg- istries with real-world data.14 Some authors have proposed that obese patients may have a more favorable prognosis Study Variables and Data Collection because of better anticoagulation control or to a more Clinical and demographic data for all AF patients were complete pharmacological treatment compared with nonob- collected in a detailed medical history. We defined previous ese patients, but results have not been consistent among heart disease as the composite of coronary artery disease, different studies.12,14 heart failure, and other structural cardiomyopathies (such as We sought to assess the role of obesity and BMI on hypertrophic cardiomyopathy, chronic pericardial disease, or prognosis in real-world patients receiving oral anticoagulants congenital diseases). Coagulation status was determined by for AF. the international normalized ratio values at 6 months before study entry and at 1 year of follow-up. The estimated time spent in the therapeutic range was assessed by the Rosendaal Methods method. Stroke risk was calculated using the CHADS2 and The FANTASIIA (Spanish acronym for “Atrial fibrillation: CHA2DS2-VASc scores,16,17 bleeding risk using the HAS-BLED influence of the level and type of anticoagulation on the score,18 and comorbidity according to the Charlson index. incidence of ischemic and hemorrhagic stroke”) registry Serum creatinine levels were collected at baseline and the design is described in detail elsewhere.15 In brief, this is an estimated glomerular filtration rate was calculated using the observational, prospective, national, and multicenter study of Cockcroft-Gault formula: ([140–age] 9[weight in kg]9[0.85 if clinical and demographic characteristics of Spanish patients female]/[729creatinine]). Obesity was assessed at baseline with AF. Its main objective is to assess the incidence of by means of BMI and stratified as normal weight (<25 kg/ thromboembolic and bleeding events in an unselected m2), overweight (25 to <30 kg/m2), and obese (≥30 kg/m2). population of patients with AF, assessing the type of oral At 3 years, we assessed incidence of stroke, major anticoagulant (ie, vitamin K antagonists (VKA) or direct oral bleeding, all-cause mortality, cardiovascular mortality, and anticoagulants) used, and the quality of anticoagulation with major adverse cardiovascular events (MACE, defined as the DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 2 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Table 1. Baseline Characteristics Stratified by BMI Normal Weight Overweight Obese All Patients (BMI<25 kg/m2) (BMI 25–30 kg/m2) (BMI≥30 kg/m2) P Value N 1956 358 871 727 Demographic data Age (y, meanSD) 73.89.4 75.39.5 74.59.5 72.19.2 <0.01 Women, % 44.0 46.7 40.6 46.6 0.03 Comorbidities and cardiovascular risk factors Arterial hypertension, % 80.4 69.8 79.7 86.5 <0.01 Dyslipidemia, % 52.2 48.6 51.8 54.5 0.18 Diabetes mellitus, % 29.4 24.3 25.5 36.5 <0.01 Smoking habit, % 5.1 5.6 3.9 6.2 0.10 CODP/OSAS, % 17.5 14.5 13.9 23.4 <0.01 Chronic kidney failure, % 19.3 22.6 19.5 17.3 0.11 Liver dysfunction, % 1.2 1.1 1.2 1.4 0.90 Cancer 8.6 9.8 8.2 8.5 0.65 Aortic or peripheral artery disease 6.0 6.7 6.4 5.2 0.51 History of stroke 17.0 20.7 17.6 14.4 0.03 History of systemic embolism 2.2 1.1 1.5 3.6 <0.01 Thyroid dysfunction 11.1 12.0 11.7 10.0 0.49 Alcohol abuse 3.7 3.9 2.3 5.2 <0.01 Charlson index 1.141.16 1.161.20 1.041.14 1.261.15 <0.01 Previous cardiac disease AF, % 100 100 100 100 Downloaded from http://ahajournals.org by on October 10, 2023 Cardiac disease, % 48.0 44.1 45.6 52.7 <0.01 Heart failure, % 28.9 28.2 25.8 32.9 <0.01 Coronary artery diseases, % 18.2 16.2 19.4 17.7 0.39 Acute coronary syndrome, % 13.8 12.6 14.6 13.5 0.62 Coronary revascularization, % 11.5 10.9 12.2 10.9 0.67 Coronary stent, % 9.4 6.9 10.5 9.4 0.17 Dilated cardiomyopathy or LVEF <45% (%) 11.7 13.1 10.6 12.2 0.37 Hypertrophic cardiomyopathy, % 2.6 2.8 2.9 2.2 0.68 Congenital heart disease, % 0.6 1.1 0.2 0.8 0.13 Aortic valve disease, % 3.2 6.2 2.4 2.8 <0.01 Left ventricular hypertrophy, % 15.6 10.3 15.6 18.3 <0.01 Atrial flutter, % 4.4 5.6 3.8 4.5 0.37 Sinus node dysfunction, % 2.6 3.1 2.8 2.1 0.54 Pacemaker 6.5 7.8 6.9 5.4 0.25 Bleeding episodes in the last 6 mo Major bleeding episodes, % 4.1 5.6 4.1 3.3 0.20 Bleeding requiring transfusion 32.5 35.0 38.9 20.8 0.33 (% within bleedings) Bleeding requiring surgery 8.8 10.0 5.6 12.5 0.63 (% within bleedings) Continued DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 3 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Table 1. Continued Normal Weight Overweight Obese All Patients (BMI<25 kg/m2) (BMI 25–30 kg/m2) (BMI≥30 kg/m2) P Value Type of AF Paroxysmal, % 29.1 32.7 31.0 25.2 0.14 Persistent, % 16.8 16.8 15.9 17.7 Longstanding persistent, % 4.7 4.2 4.4 5.2 Permanent, % 49.4 46.4 48.7 51.9 Previous electrical cardioversion, % 18.1 14.3 17.3 20.9 0.02 Previous pharmacological cardioversion, % 21.8 21.8 20.8 22.9 0.57 Previous AF ablation, % 4.3 4.5 4.6 3.9 0.76 Control strategy in the baseline visit 0.79 Rhythm control, % 38.2 39.7 37.6 38.2 Rate control, % 61.8 60.3 62.5 61.8 CHADS2 (meanSD) 2.251.24 2.231.34 2.221.21 2.311.24 0.37 CHA2DS2-VASc (meanSD) 3.711.59 3.731.64 3.671.53 3.741.62 0.79 HAS-BLED (meanSD) 2.011.05 2.031.10 1.981.02 2.021.05 0.72 Physical examination Systolic blood pressure (mm Hg, meanSD) 132.118.5 127.117.4 132.517.7 134.219.5 <0.01 Diastolic blood pressure (mm Hg, meanSD) 75.911.5 72.211.0 75.811.1 77.9711.7 <0.01 Heart rate (bpm, meanSD) 72.715.1 71.816.0 71.814.2 74.115.5 <0.01 Weight (kg, meanSD) 78.514.4 63.48.8 75.08.4 90.213.1 <0.01 Height (cm, meanSD) 164.58.9 164.79.0 165.48.5 163.39.1 <0.01 BMI (kg/m2, meanSD) 28.94.9 23.02.6 27.41.4 33.83.7 <0.01 Downloaded from http://ahajournals.org by on October 10, 2023 Complementary examinations Rhythm at baseline 0.05 Sinus, % 33.0 35.8 35.3 29.0 AF, % 60.6 57.3 57.9 65.5 Pacemaker, % 5.7 5.9 6.2 4.9 Other, % 0.7 1.1 0.6 0.6 LVEF (%, meanSD) 58.611.4 57.812.3 59.111.2 58.311.1 0.09 Left ventricular hypertrophy, % 40.0 33.0 38.1 45.7 <0.01 Hemoglobin (g/dL, meanSD) 13.71.7 13.41.7 13.71.7 13.71.8 <0.01 Serum creatinine (mg/dL, meanSD) 1.10.5 1.10.8 1.00.4 1.00.4 0.05 Glomerular filtration rate 66.222.9 60.920.3 64.520.7 70.825.8 <0.01 (mL/min per 1.73 m2, meanSD) Total cholesterol (mg/dL, meanSD) 177.138.6 179.840.8 177.236.5 175.639.9 0.10 Glucose (mg/dL, meanSD) 108.631.6 103.227.8 106.329.5 114.134.8 <0.01 HBA1C (%, meanSD) 6.21.3 5.91.2 6.21.1 6.31.6 <0.01 AF indicates atrial fibrillation; BMI, body mass index; bpm, beats per minute; COPD, chronic obstructive pulmonary disorder; HBA1C, hemoglobin A1c; LVEF, left ventricular ejection fraction; OSAS, obstructive sleep apnea syndrome. composite of ischemic stroke, myocardial infarction, and computed tomography or magnetic resonance imaging cardiovascular and all-cause mortality). Thromboembolic according to the neurologist’s criteria. Bleeding events were events were defined as stroke or transient ischemic attack assessed according to the 2005 International Society of and peripheral artery embolism. All strokes were evaluated by Thrombosis and Haemostasis criteria.19 All-cause and DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 4 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Table 2. Pharmacological Treatment at Baseline Stratified by BMI Normal Weight Overweight Obese (BMI<25 kg/m2) (BMI 25–30 kg/m2) (BMI≥30 kg/m2) P Value N 358 871 727 Diuretics, % 48.9 54.9 64.5 <0.01 Aldosterone antagonists, % 16.2 11.3 16.1 <0.01 ACE inhibitors, % 26.8 31.7 31.8 0.19 Angiotensin receptor blockers, % 32.4 39.5 46.2 <0.01 Statins, % 46.1 55.6 58.7 <0.01 Antiplatelets, % 9.5 11.6 9.9 0.42 b-Blockers, % 55.9 58.1 65.2 <0.01 Digoxin, % 20.9 16.9 18.3 0.24 Antiarrhythmic drugs, % 25.4 25.7 22.9 0.42 ACE indicates angiotensin-converting enzyme; BMI, body mass index. cardiovascular mortality were also recorded. Death was of clinical variables on adverse clinical outcomes was classified as cardiovascular when caused by acute coronary calculated using a Cox proportional hazards regression; the syndrome, heart failure, lethal arrhythmia or sudden death, multivariate model included variables yielding a P<0.15 on artery aneurysm rupture, or stroke. An external event univariable analysis. The models included BMI, age, sex, assignment committee evaluated all adverse events. hypertension, dyslipidemia, diabetes mellitus, coronary artery disease, heart failure, aortic or peripheral artery disease, chronic kidney disease, Charlson index, history of stroke, and Statistical Analyses CHA2DS2-VASc and HAS-BLED scores. Differences in event- The Kolmogorov-Smirnov method was used to test the free survival were examined with the log-rank test, and Downloaded from http://ahajournals.org by on October 10, 2023 normality of continuous variables, which were reported as Kaplan-Meier curves were drafted accordingly. To test meanSD or median (interquartile range), as appropriate. nonlinear association between the continuous variable BMI Categorical variables were expressed as relative frequencies and the events, analyses of restricted cubic splines were (%). We used the ANOVA test to compare continuous performed by generating restricted cubic splines for 4 knots variables across BMI categories and the post hoc Tukey test and adjusting the Cox multivariate model for each event, to assess intergroup differences. Qualitative variables were including splines as covariates. P<0.05 were considered compared using the v2 test. Cox regression analyses were statistically significant. All statistical analyses were per- used to test the associations between BMI and mortality, formed with Stata version 12 (Stata Corporation, College bleeding, and cardiovascular events. The independent effect Station, TX). Table 3. Events During Follow-Up, Stratified by BMI Normal Weight (BMI<25 kg/m2) Overweight (BMI 25–30 kg/m2) Obese (BMI≥30 kg/m2) N=358 N=871 N=727 Annual Rate Annual Rate Annual Rate n (%/year) n (%/year) n (%/year) P Value All-cause mortality 52 (4.84) 119 (4.55) 84 (3.85) 0.29 Cardiovascular 16 (1.51) 56 (2.18) 35 (1.63) 0.26 mortality Stroke 9 (0.85) 19 (0.74) 17 (0.79) 0.90 Systemic embolism 9 (0.85) 22 (0.84) 17 (0.79) 0.96 Major bleeding 23 (2.18) 75 (2.91) 48 (2.24) 0.22 MACE 24 (2.27) 84 (3.27) 60 (2.79) 0.24 BMI indicates body mass index; MACE, major adverse cardiovascular event (composite of ischemic stroke, myocardial infarction, and cardiovascular and total mortality). DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 5 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Results (5.47%) from cardiovascular causes. Forty-five (2.30%) patients had suffered a stroke, 48 (2.45%) a systemic embolism, 146 The final study sample comprised 1956 patients (56% men, (7.46%) a major bleeding episode, and 168 (8.59%) a MACE. mean age 73.89.4 years). Table 1 shows the baseline Annual event rates were similar across BMI groups for total characteristics of the study population. BMI was in the mortality (normal weight: 4.84% versus overweight: 4.55% normal range in 358 (18.3%) patients, while 871 (44.5%) versus obese: 3.85%; P=0.29), cardiovascular mortality (normal patients were overweight and 727 (37.2%) were obese. Obese weight: 1.51% versus overweight: 2.18% versus obese: 1.63%; patients were significantly younger and showed a higher P=0.26), stroke (normal weight: 0.85% versus overweight: prevalence of comorbidities such as hypertension, diabetes 0.74% versus obese: 0.79% P=0.90), systemic embolism mellitus, previous heart failure, and pulmonary disease (normal weight: 0.85% versus overweight: 0.84% versus obese: compared with normal weight and overweight patients. 0.79%; P=0.96), major bleeding (normal weight: 2.18% versus overweight: 2.91% versus obese: 2.24%; P=0.31), and MACE (normal weight: 2.27% versus overweight: 3.27% versus obese: Pharmacological Treatment 2.79%; P=0.24) (Table 3 and Figure 1). There were significant differences in most cardiovascular On univariable analysis, obesity was not statistically related medications (Table 2), but not in the quality of anticoagulation to all-cause mortality (odds ratio [OR] 1.24, 95% CI 0.94–1.64; control with VKA according to BMI. Mean time in the therapeutic P=0.14, cardiovascular mortality OR 1.23, 95% CI 0.81–1.86; range was similar across BMI categories (normal weight: 61.1% P=0.33), stroke (OR 0.97, 95% CI 0.53–1.79; P=0.93), systemic versus overweight: 62.5% versus obese: 63.1%; P=0.42). No embolism (OR 1.08, 95% CI 0.59–1.97; P=0.80), major bleeding significant differences were found in the percentage of VKA (OR 1.23, 95% CI 0.86–1.75; P=0.27), or MACE (OR 1.07, 95% patients achieving <65% or 70% of their time in the therapeutic CI 0.77–1.49; P=0.68) (Table S2). range (Table S1). Subgroup Analyses Events During Follow-Up The event rates were analyzed in prespecified subgroups. We did After a median of 1070 (interquartile range 750–1110) days of not find significant differences between sexes or age groups. follow-up, 255 (13.04%) patients had died, including 107 Event rates for death or MACE are shown in Table S2. Only 7 Downloaded from http://ahajournals.org by on October 10, 2023 Figure 1. Kaplan–Meier survival estimates. A, Mortality, (B) stroke, (C) major bleeding, and (D) MACE (composite of ischemic stroke, myocardial infarction, and cardiovascular and total mortality). MACE indicates major adverse cardiovascular events. DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 6 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Table 4. Multivariate Cox regression third were obese. Despite the higher prevalence of cardio- vascular risk factors in overweight and obese patients, there HR 95% CI P Value were no significant differences in adverse events between Total mortality normal and obese patients. Moreover, higher BMI was not BMI (reference <30 kg/m2) 0.94 0.71 1.25 0.69 independently associated with a higher risk of mortality or Age, per y 1.09 1.07 1.11 <0.01 adverse outcomes in multivariate analysis. Whether obesity is a protective factor or has no effect is a Heart failure 1.72 1.26 2.36 <0.01 matter of debate. In 2 substudies of the ARISTOTLE trial, Charlson index 1.33 1.15 1.54 <0.01 overweight and obesity were associated with lower risk of all- CHA2DS2-VASc 0.81 0.69 0.95 0.01 cause mortality, cardiovascular mortality, and stroke even HAS-BLED 1.34 1.16 1.55 <0.01 after adjusting for biomarkers of cardiac and renal dysfunction Stroke and inflammatory activity.13,20 A large meta-analysis and BMI (reference <30 kg/m2) 1.17 0.62 2.22 0.63 systematic review evaluated the relationship between BMI Cerebrovascular disease 2.54 1.10 5.88 0.03 and clinical outcomes in AF patients, finding that the risk of stroke, death, and cardiovascular death were lower in Major bleeding overweight and obese patients compared with patients with BMI (reference <30 kg/m2) 0.88 0.61 1.28 0.51 a normal BMI,21 but other studies, such as the EORP-AF Dyslipidemia 0.57 0.41 0.81 0.01 (EURObservational Research Programme-Atrial Fibrillation),22 Chronic kidney failure 1.50 1.01 2.23 0.04 did not find significant differences. HAS-BLED 1.29 1.08 1.55 <0.01 Studies including clinical trial data show reduced events MACE among obese patients (the so-called “obesity paradox”), while BMI (reference <30 kg/m2) 1.00 0.72 1.41 0.98 most observational registries report similar event rates between obese and normal weight patients, suggesting that Age, per y 1.06 1.03 1.09 <0.01 comorbidities have an important role in determining out- Coronary artery disease 1.99 1.26 3.13 <0.01 comes.22 Proietti et al23 performed a systematic review Heart failure 2.01 1.27 3.16 <0.01 studying the relationship between overweight or obesity and HAS-BLED 1.21 1.01 1.44 0.04 cardiovascular prognosis and observed an obesity paradox for Downloaded from http://ahajournals.org by on October 10, 2023 adverse events only in clinical trials cohorts, whereas Model adjustment: The models included BMI, age, sex, hypertension, dyslipidemia, diabetes mellitus, coronary artery disease, heart failure, aortic or peripheral artery observational studies fail to show this relationship, in disease, chronic kidney disease, Charlson index, history of stroke, CHA2DS2-VASc and accordance with our results in the FANTASIIA registry. HAS-BLED scores. BMI indicates body mass index; HR, hazard ratio; MACE, major adverse cardiovascular event (composite of ischemic stroke, myocardial infarction, and Indeed, in our study, the Charlson index was significantly cardiovascular and total mortality). higher among obese patients, and in the multivariate analyses it was an independent predictor of mortality, while patients in our population were underweight (BMI<18.5 kg/m2), obesity did not show significant association. While clinical precluding further analyses in this category (Table S3). trials are considered to provide the highest grade of evidence, observational registries are better suited for Multivariate Analysis studying broader populations without strict inclusion criteria, obtaining information more representative of real-life daily In the multivariate Cox analysis performed to adjust for clinical practice. confounding variables, BMI was not independently associated Obesity has been shown to be an independent risk factor with all-cause mortality, cardiovascular mortality, stroke, for thromboembolic events in the general population with no major bleeding, or MACE (Table 4). The restricted cubic AF,14,24 but the relationship between stroke and BMI in splines analyses showed nonlinear relationship between BMI patients with AF is debated. Indeed, scores to predict stroke and events (Figure 2). do not include BMI, and the 2 variables (stroke and obesity) An additional model including only BMI and age was are not associated in observational studies.17,25 Our results performed in order to further study the effect of age in the corroborate these observations. Although most studies in relationship between BMI and events (Figure 3). patients with AF show neutral or protective effects for higher BMI, overweight and obesity were associated with a worse prognosis in the Danish Diet, Cancer, and Health study of Discussion incident AF, a prospective nationwide study.26 The protection In a real-world cohort of patients receiving oral anticoagulant conferred by obesity seems more evident in patients with therapy for AF, half of the patients were overweight and a established cardiovascular disease, and the selection of DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 7 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Figure 2. Association between BMI and the estimated 3-year survival probability including BMI as a continuous variable using restricted cubic splines with 3 degrees of freedom. The dotted lines represent the 95% CI. (A) Mortality, (B) stroke, (C) major bleeding, and (D) MACE (composite of ischemic stroke, myocardial infarction, and cardiovascular and total mortality). The models were adjusted by age, sex, hypertension, diabetes mellitus, dyslipidemia, coronary artery disease, heart failure, aortic artery disease, chronic kidney disease, Charlson index, previous stroke, CHA2DS2-VASc, and HAS-BLED. BMI indicates body mass index; MACE, major adverse cardiovascular events. Downloaded from http://ahajournals.org by on October 10, 2023 patients with incident AF could result in a lower-risk metabolic reserves that may help to cope with heart disease. population. In fact, in heart failure—the paradigm of advanced Our results support this hypothesis. Figure 2 shows that cardiac disease—the obesity paradox is more pronounced.27 rather than a decrease of risk for obesity, there is an increase The risk of bleeding has scarcely been studied. Our results of risk for BMI values <25. suggest that obesity does not modify bleeding risk in patients Finally, obese patients may have better tolerance for anticoagulated for AF, and other studies have shown only that cardiovascular drugs with proven prognostic benefits. In our underweight could be associated with increased bleeding study, obese patients received a significantly higher propor- risk,25,28 but not overweight or obesity. Again, obesity is not tion of renin-angiotensin system blockers, diuretics, statins, included in any bleeding risk score: neither HAS-BLED nor and b-blockers. This finding is consistent with previous ATRIA, HAEMORR2HAGES, or ORBIT include weight among reports and could explain, at least in part, the good prognosis the variables that predict bleeding episodes.29 associated with obesity. In agreement with other groups, we Age is one of the strongest predictors of mortality. In our found similar international normalized ratio control among study, mean age decreased as BMI increased, and this finding BMI categories,25 but the effect of overweight and obesity on is consistent with other studies.13,20,30 In the subanalysis prognosis did not change after adjustment for these potential including only age and BMI, BMI still did not show a significant confounders. A nonlinear relationship between BMI and relationship with events in the follow-up. events was also tested (Figure 2) and we did not find The higher risk of developing a cardiovascular disease significant changes in the event rates through all the caused by obesity is probably not as strong as the effect of spectrum of BMI of our population, reinforcing the lack of cachexia worsening prognosis in any chronic disease. We association between weight and prognosis in this scenario. speculate that obesity increases the probability of developing cardiovascular diseases, but it also helps patients survive their complications. Underweight patients have an increased Limitations mortality risk21,31 and are more prone to have diseases as a This study has some limitations. BMI was collected only at result of poor nutritional status, whereas obesity confers baseline, so we could not assess the associations between DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 8 Obesity and Atrial Fibrillation Bertomeu-Gonzalez et al ORIGINAL RESEARCH Figure 3. Association between BMI and the estimated 3-year survival probability including BMI as a continuous variable using restricted cubic splines with 3 degrees of freedom. The dotted lines represent the 95% CI. A, Mortality, (B) stroke, (C) major bleeding, and (D) MACE (composite of ischemic stroke, myocardial infarction, and cardiovascular and total mortality). The models were adjusted by age. BMI indicates body mass index; MACE, major adverse cardiovascular events. long-term changes in BMI over time on outcomes. The Instituto de Salud Carlos III (Madrid)-FEDER (RD16/11/ measurement of obesity by means of BMI is a limited approach, 00420, RD12/0042/0068, RD12/0042/0010, RD12/0042/ Downloaded from http://ahajournals.org by on October 10, 2023 because it does not assess the distribution of fat, the amount of 0069, and RD12/0042/0063). The authors are supported by lean body weight, body fat, fat-free mass, or fat composition.32 RD12/0042/0049 (RETICS) from ISCIII and PI13/00513/ While most studies assess obesity with BMI, results are similar FEDER from ISCIII. Fundacion Seneca (19245/PI/14), Instituto in studies evaluating it by waist circumference.13,20 The lack of Murciano de Investigacion Biosanitaria (IMIB16/AP/01/06). more detailed information about the type of bleeding or the cause of cardiovascular death prevented further analyses. The Cockcroft-Gault formula tends to overestimate creatinine Disclosures clearance in obese patients. Although multivariate adjustment None. was performed, the effects of residual confounding cannot be fully excluded. A propensity-score matched analysis would have References reinforced the strength of the findings, but the limited sample orschel CS, Schnabel RB. The imminent epidemic of atrial fibrillation and its 1. B€ size of our study prevented us from performing this analysis. On concomitant diseases—Myocardial infarction and heart failure—a cause for concern. Int J Cardiol. 2019;287:162–173. the other hand, the observational nature of our study provides 2. 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DOI: 10.1161/JAHA.119.013789 Journal of the American Heart Association 10 SUPPLEMENTAL MATERIAL Downloaded from http://ahajournals.org by on October 10, 2023 Appendix FANTASIIA Registry Investigators Carmen Rus Mansila1, Juan Luis Bonilla Palomas1, Antonio Luis Gámez López1, Daniel Salas Bravo1, Miriam Martín Toro1, Antonio Luis Gámez López1, Juan Luis Bonilla Palomas1, Manuel Anguita Sánchez2, Mónica Delgado Ortega2, Juan Carlos Castillo Domínguez2, Martín Ruiz Ortiz2, Elías Romo Peña2, Mónica Delgado Ortega2, Dr. Fátima Esteban3, Dr. Miguel Ángel Casanova3, Dr. Francisco Torres Calvo4, Dr. Rafael Bravo Marqués4, Dr. Pedro Chinchurreta Capote4, Dr. Alejandro Pérez Cabeza4, Dr. Raúl Quirós López4, Dr. Rodrigo Mayo Cabeza4, Dr. Juan José Gómez Doblas5, Dr. José Carlos Pérez Sánchez5, Dr. Manuel Almendro Delia6, Dr. Cristina Jiménez Hidalgo6, Dr. Gonzalo Barón7, Dr. Silvia Gómez Moreno7, Dr. Antonio Fernández7, Dr. Lorena García Riesco7. Dr. María Laura García Pérez8, Dr. José Rozado Castaño8, Dr. Jorge Álvarez9, Dr. Tomas Downloaded from http://ahajournals.org by on October 10, 2023 Ripoll Vera9, Dr. Joan Torres Marqués9, Dr. Juana Núñez Morcillo9, Dr. Marcos Rodríguez Esteban10, Dr. José Alejandro Medina García10, Dr. César Sosa10, Dr. Javier Mesa Fumero10, Dr. Daniel García Fuertes11, Dr. Manuel Crespín Crespín11, Dr. Inmaculada Coca Prieto11, Dr. José Gonzalo Delgado Díaz-Benito11, Dr. Elena Villanueva Fernández11, Dr. Teresa Cano Mozo12, Dr. José Luis Moriñigo Muñoz12, Dr. Ana Martín García12, Dr. Jesús Manuel Hernández Hernández12, Dr. Imanol Otaegui13, Dr. Jordi Pérez Rodón13, Dr. Jaume Francisco Pascual13, Dr. Neus Bellera Gotarda13, Dr. Eulalia Roig Minguell14, Dra. Sonia Mirabet Pérez14, Dr. Vicens Brossa14, Dr. Laura López14, Dr. Nicolás Manito Lorite15, Dr. Ignasi Anguera Camos15, Dr. David Chivite Guillén15, Dr. Jorge Antonio Morales Álvarez16, Dr. Andrés, Fernández Gasalia16, Dr. Neus Piulats Egea16, Dr. Josep Casas Rodríguez16, Dr. Óscar Alcaide17, Dr. Roger Villuendas17, Dr. Áxel Sarrias17, Dr. Mar Domingo17, Dr. Ramón de Castro18, Dr. Nuria Farré18, Dr. Isabel Serrano Rodríguez18, Dr. Ingrid Colomer18, Dr. José Moreno Arribas19, Dr. Vicente Bertomeu Gónzalez19, Dr. Bertomeu Martínez19, Dr. Francisco Ridocci Soriano20, Dr. Rafael Payá Serrano20, Dr. Jose Antonio Madrigal Vilata20, Dr. José Perez Silvestre20, Dr. Juan Cosín Sales21, Dr. Francisco Buendía21, Dr. Esther Esteban21, Dr. Antonio Lillo21, Dr. Dolores Marco Macian21, Dr. Yolanda Porrás Ramos22, Dr. Mª Victoria Mongollón Jiménez22, Dr. Pilar Marón Ramos23, Dr. Alfonso Varela Román23, Dr. Antonio Pose Reino23, Dr. Manuel Suárez Tembra23, Dr. Manuel Lado López23, Dr. Carlos González Juanatey24, Dr. Inmaculada Roldán25, Dr. Carlos Escobar Cervantes25, Dr. Marta Mateos García25, Dr. Mª Angustias Quesada Simón25, Dr. José Camacho Siles25, Dr. Paloma Eviro García25, Dr. Manuel Martínez Sellés26, Dr. Tomás Datino26, Dr. Mª Teresa Vidán26, Dr. Luis Cornide26, Dr. Pablo García Pavía27, Dr. Marta Mª Cobo Marcos27, Dr. David Vivas28, Dr. Javier Higueres Nafría28, Dr. José Manuel Rubio Campal29, Dr. Pepa Sánchez Borque29, Dr. Francisco Marín Ortuño30, Dr. Miguel García Downloaded from http://ahajournals.org by on October 10, 2023 Navarro30, Dr. Raquel Pérez Luján30, Dr. Mariano Leal Hernández30, Dr. Sergio Manzano Fernández30, Dr. Diego Giménez Cervantes31, Dr. Francisco José García Amargo31, Dr. Manuel Gonzálvez Ortega31, Dr. Milagros Gil Ortega31. Dr. Nekane Murga Eizagaechevarría32, Dr. Esther Recalde32. Centers: 1Ciudad de Jaén Hospital, Jaén, Spain. 2Reina Sofía Hospital, Córdoba, Spain. 3 Infanta Margarita Hospital, Cabra, Córdoba, Spain.4Costa del Sol Hospital, Marbella, Spain.5Virgen de la Victoria Hospital, Málaga, Spain.6Virgen Macarena Hospital, Sevilla, Spain. 7Virgen del Rocío Hospital, Seviila, Spain. 8Central de Asturias Hospital, Asturias, Spain. 9Son Llázer Hospital, Baleares, Spain. 10 Candelaria Hospital, Canarias, Spain. 11 12 Santa Bárbara Hospital, Ciudad Real, Spain. Clínico de Salamanca Hospital, 13 14 Salamanca, Spain. Vall d’Hebrón Hospital, Barcelona, Spain. Sant Pau Hospital, Barcelona, Spain.15Universitari de Bellvitge Hospital, Barcelona, Spain. 16 Del Mar Hospital, Barcelona, Spain. 17Germans Trias, Barcelona, Spain. 18Juan XXIII, Tarragona, Spain. 19San Juan de Alicante Hospital, San Juan, Spain. 20General Hospital, Valencia, 21 22 Spain. Arnau de Vilanova Hospital, Valencia, Spain. Cáceres Hospital, Cáceres, 23 24 Spain. Clínico de Santiago de Compostela, Galicia, Spain. Universitario Lucus 25 Augusti Hospital, Galicia, Spain. La Paz Hospital, Madrid, Spain. 26Gregorio Marañon Hospital, Madrid, Spain. 27Puerta de Hierro Hospital, Madrid, Spain.28Clínico San Carlos, 29 30 Madrid, Spain. Fundación Jiménez Díaz Hospital, Madrid, Spain. Virgen de la 31 Arrixaca Hospital, Murcia, Spain. Morales Meseguer Hospital, Murcia, Spain. 32 Basurto Hospital, Vizcaya, Spain Downloaded from http://ahajournals.org by on October 10, 2023 Table S1. Quality of antivitamin k control stratified by BMI. Normal weight Overweight (BMI < 25 (BMI 25-30 Obese (BMI kg/m2) kg/m2) ≥ 30 kg/m2) p value N 266 643 574 TTR Rosendaal (mean ± SD), % 61.1 ± 19.4 62.5 ± 20.7 63.1 ± 19.2 0.42 TTR < 65% (%) 55.7 52.4 51.1 0.52 TTR < 70% (%) 64.1 62 62.2 0.87 BMI: body mass index; SD: standard deviation; TTR: time in the therapeutic range. Downloaded from http://ahajournals.org by on October 10, 2023 Table S2. Univariate Cox regression. Total mortality HR 95% CI p value BMI (reference <30 kg/m2) 0.81 0.62 1.05 0.10 Female sex 0.79 0.61 1.02 0.12 Age, per year 1.09 1.07 1.11 <0.01 Arterial hypertension 1.80 1.25 2.60 <0.01 Diabetes mellitus 1.60 1.24 2.07 <0.01 Dyslipidemia 1.02 0.79 1.30 0.90 Coronary artery disease 1.80 1.37 2.37 <0.01 Heart failure 2.37 1.85 3.03 <0.01 Aortic valve disease 1.49 0.96 2.31 0.07 Chronic kidney failure 2.77 2.13 3.61 <0.01 Downloaded from http://ahajournals.org by on October 10, 2023 Charlson index 1.48 1.36 1.62 <0.01 Cerebrovascular disease 1.25 0.92 1.70 0.16 CHA2DS2-VASc 1.39 1.29 1.50 <0.01 HAS-BLED 1.69 1.52 1.50 <0.01 Stroke HR 95% CI p value BMI (reference <30 kg/m2) 0.99 0.54 1.80 0.97 Female sex 0.76 0.42 1.39 0.37 Age, per year 1.02 0.56 1.89 0.27 Arterial hypertension 1.42 0.63 3.18 0.40 Diabetes mellitus 1.03 0.54 1.97 0.93 Dyslipidemia 1.21 0.67 2.18 0.53 Coronary artery disease 1.97 1.03 3.75 0.04 Heart failure 2.21 1.22 3.99 <0.01 Aortic valve disease 0.76 0.18 3.12 0.69 Chronic kidney failure 2.26 1.23 4.17 <0.01 Charlson index 1.36 1.09 1.70 <0.01 Cerebrovascular disease 2.57 1.38 4.79 <0.01 CHA2DS2-VASc 1.33 1.11 1.60 <0.01 HAS-BLED 1.52 1.17 1.96 <0.01 Major bleeding HR 95% CI p value BMI (reference <30 kg/m2) 0.80 0.57 1.14 0.22 Female sex 0.96 0.69 1.33 0.81 Age, per year 1.03 1.01 1.05 <0.01 Downloaded from http://ahajournals.org by on October 10, 2023 Arterial hypertension 1.11 0.73 1.68 0.62 Diabetes mellitus 1.52 1.08 2.13 0.02 Dyslipidemia 0.67 0.48 0.93 0.02 Coronary artery disease 1.33 0.90 1.97 0.15 Heart failure 1.57 1.12 2.20 <0.01 Aortic valve disease 1.14 0.60 2.17 0.69 Chronic kidney failure 1.98 1.42 2.78 <0.01 Charlson index 1.32 1.17 1.49 <0.01 Cerebrovascular disease 1.47 1.00 2.17 0.05 CHA2DS2-VASc 1.24 1.12 1.38 <0.01 HAS-BLED 1.47 1.27 1.70 <0.01 MACE HR 95% CI p value BMI (reference <30 kg/m2) 0.91 0.66 1.24 0.54 Female sex 0.90 0.66 1.22 0.49 Age, per year 1.06 1.04 1.08 <0.01 Arterial hypertension 1.52 0.99 2.33 0.06 Diabetes mellitus 2.06 1.51 2.80 <0.01 Dyslipidemia 1.49 1.09 2.04 0.01 Coronary artery disease 2.80 2.05 3.84 <0.01 Heart failure 2.73 2.01 3.69 <0.01 Aortic valve disease 2.20 1.38 3.52 <0.01 Chronic kidney failure 2.46 1.79 3.38 <0.01 Charlson index 1.52 1.36 1.69 <0.01 Downloaded from http://ahajournals.org by on October 10, 2023 Cerebrovascular disease 1.39 0.96 2.01 0.08 CHA2DS2-VASc 1.45 1.32 1.59 <0.01 HAS-BLED 1.60 1.40 1.82 <0.01 BMI: body mass index; CI: confidence interval; HR: hazard ratio. Table S3. Event rates for subgroups, stratified by BMI. Normal weight Overweight Obese (BMI < 25 kg/m2) (BMI 25-30 kg/m2) (BMI ≥ 30 kg/m2) N = 358 N = 871 N = 727 Annual Annual Annual rate rate rate p n (%/year) n (%/year) n (%/year) value All-cause mortality Age < 65 4 (2.83) 5 (1.32) 4 (0.91) 0.23 years Downloaded from http://ahajournals.org by on October 10, 2023 65-75 9 (2.75) 31 (3.47) 25 (8.33) 0.80 years > 75 39 (6.44) 83 (6.19) 55 (6.03) 0.93 years Sex Women 19 (3.79) 44 (2.54) 35 (3.44) 0.68 Men 33 (5.76) 75 (4.84) 49 (4.21) 0.32 MACE Age < 65 4 (2.83) 6 (1.59) 6 (1.37) 0.53 years 65-75 5 (1.53) 21 (2.35) 23 (2.77) 0.47 years > 75 15 (2.48) 57 (4.25) 31 (3.40) 0.12 years Sex Women 12 (2.39) 27 (2.54) 31 (3.05) 0.70 Men 12 (2.09) 57 (3.67) 29 (2.49) 0.07 BMI: body mass index; MACE: major adverse cardiovascular events (composite of ischemic stroke, myocardial infarction and cardiovascular and total mortality). Downloaded from http://ahajournals.org by on October 10, 2023