Relationship between body mass index, coronary disease extension and clinical outcomes in patients with acute coronary syndrome Helder Dores, Luís Bronze Carvalho, Ingrid Rosário, Sílvio Leal, Maria João Correia, José Monge, José Azevedo, Isabel Arroja, Ana Aleixo, Miguel Mendes
Conflicts of interest: none
Introduction (1) Aim Methods Results Conclusions Obesity has reached epidemic proportions in the western countries: - Prevalence is trending upward - Risk factor for coronary disease and acute coronary syndrome (ACS) - Association with cardiovascular (CV) and non-cv mortality (general population)
Introduction (2) Aim Methods Results Conclusions Contradictory evidence in patients with established coronary artery disease (CAD) Obesity paradox? Conditions in which obesity has been associated with favourable prognosis First elective PCI n=9578 All-cause death 5-years
Aim Cardiology Department Introduction Methods Results Conclusions To assess the extension of coronary disease and the prognosis of patients with ACS according to the Body Mass Index (BMI)
Introduction Aim Methods (1) Results Conclusions Retrospective analysis Consecutive patients admitted with ACS in a Coronary Unit (Jan/03-Jan/04) Categorization of the patients according to the BMI * (kg/m 2 ) category (WHO * ): Underweight (<18.5 ) Normal weight (18.5-24.9) Overweight (25.0-29.9) Obesity ( 30.0) * WHO World Health Organization
Aim Methods (2) Introduction Results Conclusions Variables Demographic: Age and gender Clinical: CV risk factors (Hypertension, Diabetes Mellitus, Smoking, Dyslipidemia), past history [Acute Myocardial Infarction (AMI), Percutaneous Coronary Intervention (PCI), Coronary Artery Bypass Grafting (CABG), Stroke/Transient Ischemic Accident (TIA)] and clinical presentation (height, weight, blood pressure, heart rate, Killip class) Electrocardiographic: ST deviation, T wave inversion Echocardiographic: Left Ventricular Ejection Fraction (LVEF) Angiographic: Number of significant coronary artery stenosis (>50% lumen obstruction) Therapeutic: Reperfusion (PCI, Thrombolysis and CABG) and therapy at discharge
Introduction Aim Methods (3) Results Conclusions Comparison of the variables registered between the BMI categories Survival analysis and evaluation of the correlation between BMI and all-cause mortality at 30-days, 12 -months and 5-years of follow-up Statistical analysis (SPSS v18.0) Qualitative variables (numbers and percentages) compared by chi-square test continuous variables by t-student (m±sd) (Kolmogorov-Smirnov normality tested) Logistic regression (OR, 95% CI) comparing patients variables: BMI 24.9 vs 25.0 kg/m 2 Multivariate binary logistic regression - correlation between BMI and multivesel lesions Cox regression analysis to evaluate the association between BMI and all-cause mortality Survival analysis by the Kaplan-Meier method (Log-Rank test to evaluate differences) Statistical significance - p value <0.05
Aim Results (1) Introduction Methods Conclusions Baseline characteristics n = 270 patients Age (m±sd) = 64.8±12.2 years 67.8% (183) male NSTEMI - 38.5% (104) STEMI - 36.3% (98) UA - 25.2% (68) BMI category (%)* BMI (m±sd) = 27.4±4.1 kg/m 2 * No patients underweight
Aim Results (2) Introduction Methods Conclusions Baseline characteristics Variables (%) BMI 24.9 (n=59) p value BMI 25.0 29.9 (n=145) p value BMI 30.0 (n=66) Age (m±sd) 66.9±11.8 0.310 65.0±12.1 0.147 62.2±12.1 Age >75 years 28.8 0.064 17.2 0.547 13.8 Male gender 64.4 0.257 72.4 0.093 60.3 Hypertension 50.8 0.003 72.4 0.309 79.3 Diabetes Mellitus 22.0 0.600 25.5 0.199 34.5 Dyslipidemia 39.0 0.195 49.0 0.564 53.4 Smoking 40.7 0.222 31.7 0.563 27.6 Stroke/TIA 5.1 0.939 4.8 0.918 5.2 Prior AMI 27.1 0.813 25.5 0.838 24.1 Prior PCI 8.5 0.684 10.3 0.446 6.9 Prior CABG 6.8 0.728 5.5 0.415 8.6
Introduction Aim Methods Results (3) Conclusions Baseline characteristics Variables (%) BMI 24.9 (n=59) p value BMI 25.0 29.9 (n=145) p value BMI 30.0 (n=66) STEMI 42.4 0.289 34.5 0.816 36.2 NSTEMI 39.0 0.965 39.3 0.522 34.5 UA 18.6 0.252 26.2 0.653 29.3 SBP (m±sd) 151.8±29.0 0.547 154.7±35.3 0.215 148.3±32.0 Heart rate (m±sd) 78.2±20.5 0.685 79.5±21.7 0.201 84.1±24.3 Killip class > I 19.6 0.660 16.9 0.839 18.2 ECG ST-elevation 40.7 0.481 35.4 0.916 36.2 ST-depression 35.6 0.127 25.0 0.898 24.1 Isolated T wave inversion 10.2 0.023 24.3 0.817 25.9 Normal 11.9 0.797 13.2 0.910 13.6 LVEF (m±sd) 61.0±16.3 0.41 58.8±14.2 0.161 55.3±16.9 ECG Electrocardiogram; SAP Systolic Arterial Pressure; STEMI /NSTEMI ST Elevation/Non Myocardial Infarction; UA Unstable Angina.
Introduction Angiographic characteristics Aim Methods Results (4) Conclusions Variables (%) BMI 24.9 (n=59) p value BMI 25.0 29.9 (n=145) p value BMI 30.0 (n=66) Angiography 78 0.745 80 0.009 94.8 Left main 6.5 0.386 3.4 0.123 9,1 Left anterior descending 65.2 0.015 44.0 0.001 70.9 Left circunflex 34.8 0.946 35.3 0.418 29.1 Right coronary 67.4 0.001 38.8 0.203 49.1 Without significant lesions 10.9 0,042 27.1 0.182 17.5 One-vessel lesion 39.1 0.575 43,2 0.624 42.1 Multivessel lesions 50.0 0.013 29.7 0.082 40.4 Logistic regression (predictors of multivessel lesions) Variables OR 95% CI p value Overweight 0.39 [0.19-0.80] 0.010 Diabetes Mellitus 2.58 [1.20-5.66] 0.016 Adjusted for gender, age > 75 years and cardiovascular risk factors (dyslipidemia, Diabetes Mellitus, Hypertension)
Introduction Aim Methods Results (5) Conclusions In-hospital management Variables (%) BMI 24.9 (n=59) p value BMI 25.0 29.9 (n=145) p value BMI 30.0 (n=66) Thrombolysis * 30.5 0.404 24.8 0.531 20.7 PCI 46.8 0.427 40.8 0.029 57.4 In-hospital death 5.1 0.765 4.1 0.395 1.7 Statins + 90.7 0.949 90.4 0.167 83.3 βb + 72.2 0.936 72.8 0.328 79.6 ACE-I/ARB + 72.2 0.747 69.9 0.173 79.6 Eligible patients; + Therapy at discharge ACE-I angiotensin-converting enzyme inhibitor; ARB angiotensin receptor blocker; β B Beta bloker.
Introduction Aim Methods Results (6) Conclusions Logistic regression: BMI 24.9 vs BMI 25.0 Kg/m 2 Unadjusted model Variables OR * 95% CI p value Hypertension 3.08 [1.54-6.14] 0.001 Isolated T-wave inversion 3.97 [1.32-11.92] 0.014 Multivessel lesions 0.5 [0.25-0.98] 0.044 OR for IMC > 25.0 Kg/m 2
Aim Results (7) Introduction Methods Conclusions Correlation between BMI and all-cause mortality (Cox regression) Unadjusted model (univariate) BMI HR 95% CI p value 30-days 0.9 [0.78-1.09] 0.34 12-months 0.9 [0.79-1.08] 0.30 5-years 0.9 [0.79-1.02] 0.10 Adjusted model (multivariate) * BMI HR 95% CI p value 30-days - - - 12-months 0.9 [0.66-1.25] 0.57 5-years 0.9 [0.76-1.08] 0.24 * Adjustment for age, gender and confounders [cardiovascular risk factors, clinical presentation, LVEF and angiographic findings]
Aim Results (8) Introduction Methods Conclusions Independent predictors of all-cause mortality (Cox regression * ) Variables (%) HR 95% CI p value 30-days - - - - 12-months LVEF 0.91 [0.85-0.99] 0.023 5-years LVEF 0.96 [0.93-1.00] 0.025 * Adjustment for age, gender and confounders [cardiovascular risk factors, clinical presentation, LVEF and angiographic findings]
Introduction Aim Methods Results (9) Conclusions Survival analysis (Kaplan-Meier curves) BMI categories Normal Overweight Obesity BMI 25.0 <25.0 Time (days) 25.0 Kg/m 2 Log-Rank test (p) Time BMI categories BMI 24.9 vs Events (%/n) 30-days 0.353 0.829 4.8/11 12-months 0.852 0.656 5.6/13 5-years 0.480 0.337 11.0/22
Aim Results Conclusions (1) Introduction Methods 1) In the studied population, patients with normal BMI had more extensive CAD Paradoxically, overweight seems to have exerted a protective effect 2) Obese patients were more likely to underwent coronary angiography and PCI 3) These differences were not reflected in the prognosis (short, medium or long-term) 4) BMI was not an independent predictor for all-cause mortality
Aim Results Conclusions (2) Introduction Methods The question of which measure of obesity better predicts survival in patients with coronary artery disease remains controversial It is crucial to improve the understanding of the relationship between excess weight and cardiovascular outcomes
Aim Results Conclusions (3) Introduction Methods Limitations - Retrospective analysis - Small dimension of the sample - Duration of obesity, body-fat distribution and percentage were not quantified - Temporal weight changes during the follow-up were not valued (BMI reflects global adiposity)
Relationship between body mass index, coronary disease extension and clinical outcomes in patients with acute coronary syndrome Helder Dores, Luís Bronze Carvalho, Ingrid Rosário, Sílvio Leal, Maria João Correia, José Monge, José Azevedo, Isabel Arroja, Ana Aleixo, Miguel Mendes Thanks
Introduction Aim Methods Results Conclusions Severity of angiographic coronary stenosis and BMI n=46663 (PCI) Relation between obesity and severity of coronary artery disease in patients undergoing coronary angiography. Rubinshtein R, Halon DA, Jaffe R, Shahla J, Lewis BS. n=928 Advancing age, male gender, diabetes mellitus and hyperlipidemia were independent predictors of high-risk anatomy, whereas obesity remained a significant negative independent predictor. n=9146 (PCI)
Introduction Aim Methods Results Conclusions n=770 (ACS)