Relationship between body mass index, coronary disease extension and clinical outcomes in patients with acute coronary syndrome
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1 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
2 Conflicts of interest: none
3 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)
4 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
5 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)
6 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 ( ) Overweight ( ) Obesity ( 30.0) * WHO World Health Organization
7 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
8 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
9 Aim Results (1) Introduction Methods Conclusions Baseline characteristics n = 270 patients Age (m±sd) = 64.8±12.2 years 67.8% (183) male NSTEMI % (104) STEMI % (98) UA % (68) BMI category (%)* BMI (m±sd) = 27.4±4.1 kg/m 2 * No patients underweight
10 Aim Results (2) Introduction Methods Conclusions Baseline characteristics Variables (%) BMI 24.9 (n=59) p value BMI (n=145) p value BMI 30.0 (n=66) Age (m±sd) 66.9± ± ±12.1 Age >75 years Male gender Hypertension Diabetes Mellitus Dyslipidemia Smoking Stroke/TIA Prior AMI Prior PCI Prior CABG
11 Introduction Aim Methods Results (3) Conclusions Baseline characteristics Variables (%) BMI 24.9 (n=59) p value BMI (n=145) p value BMI 30.0 (n=66) STEMI NSTEMI UA SBP (m±sd) 151.8± ± ±32.0 Heart rate (m±sd) 78.2± ± ±24.3 Killip class > I ECG ST-elevation ST-depression Isolated T wave inversion Normal LVEF (m±sd) 61.0± ± ±16.9 ECG Electrocardiogram; SAP Systolic Arterial Pressure; STEMI /NSTEMI ST Elevation/Non Myocardial Infarction; UA Unstable Angina.
12 Introduction Angiographic characteristics Aim Methods Results (4) Conclusions Variables (%) BMI 24.9 (n=59) p value BMI (n=145) p value BMI 30.0 (n=66) Angiography Left main ,1 Left anterior descending Left circunflex Right coronary Without significant lesions , One-vessel lesion , Multivessel lesions Logistic regression (predictors of multivessel lesions) Variables OR 95% CI p value Overweight 0.39 [ ] Diabetes Mellitus 2.58 [ ] Adjusted for gender, age > 75 years and cardiovascular risk factors (dyslipidemia, Diabetes Mellitus, Hypertension)
13 Introduction Aim Methods Results (5) Conclusions In-hospital management Variables (%) BMI 24.9 (n=59) p value BMI (n=145) p value BMI 30.0 (n=66) Thrombolysis * PCI In-hospital death Statins βb ACE-I/ARB Eligible patients; + Therapy at discharge ACE-I angiotensin-converting enzyme inhibitor; ARB angiotensin receptor blocker; β B Beta bloker.
14 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 [ ] Isolated T-wave inversion 3.97 [ ] Multivessel lesions 0.5 [ ] OR for IMC > 25.0 Kg/m 2
15 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 [ ] months 0.9 [ ] years 0.9 [ ] 0.10 Adjusted model (multivariate) * BMI HR 95% CI p value 30-days months 0.9 [ ] years 0.9 [ ] 0.24 * Adjustment for age, gender and confounders [cardiovascular risk factors, clinical presentation, LVEF and angiographic findings]
16 Aim Results (8) Introduction Methods Conclusions Independent predictors of all-cause mortality (Cox regression * ) Variables (%) HR 95% CI p value 30-days months LVEF 0.91 [ ] years LVEF 0.96 [ ] * Adjustment for age, gender and confounders [cardiovascular risk factors, clinical presentation, LVEF and angiographic findings]
17 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 /11 12-months /13 5-years /22
18 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
19 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
20 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)
21 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
22 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)
23 Introduction Aim Methods Results Conclusions n=770 (ACS)
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