If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Obesity has long been identified as a risk factor for coronary artery disease. However, the data evaluating outcomes in patients with acute myocardial infarction (AMI) related to body mass index (BMI) are limited and inconsistent. Patients (n = 284) who were diagnosed with AMI at the Medical College of Georgia from January 1, 2003 to June 25, 2004, were included in this retrospective analysis. BMI, risk for factors for coronary artery disease, AMI characteristics, and outcome variables were obtained from chart records. Logistic and multiple regression techniques were used to model and test hypotheses regarding the effect on outcomes after AMI, adjusting for cardiac risk factors, demographics, and other contextual variables. Compared with normal weight patients, underweight patients had more (65% vs 40%) and morbidly obese patients had fewer (21% vs 40%) ST-elevation AMIs (p = 0.014). Among all patients with AMIs, morbidly obese patients tended to be younger than normal weight subjects. No adverse relations among BMI and mortality, length of stay, readmission rates, or revascularzation in AMI were identified in this analysis. Both diabetes and previous aspirin use were found to increase the odds of in-hosptial mortality during AMI independent of BMI. In conclusion, despite the association between obesity and development of coronary artery disease, obesity does not adversely impact in-hospital outcomes in AMI. However, obesity is associated with AMI at a younger age.
Obesity has been clearly established as an independent risk factor for the development of coronary artery disease and acute coronary syndrome.
demonstrated that, despite a higher prevalence of other cardiovascular risk factors among patients with excess weight, these patients did not develop worse outcomes after an acute myocardial infarction (AMI). This study was conducted to establish the relation between BMI and outcomes in patients with AMI.
All patients diagnosed with AMI at the Medical College of Georgia (Augusta, Georgia) according to code 410 from the International Classification of Diseases, Ninth Revision from January 1, 2003 to June 25, 2004 were included in this study. Three hundred twenty-seven patients were included. A complete chart review was performed for each patient, including a review of discharge summaries, laboratory data, catheterization reports, and echocardiographic reports. The study was approved by the institutional review boad at the Medical College of Georgia.
Patients were categorized into 5 BMI subgroups: underweight (<20 (kg/m2), normal weight (20 to 24.9 kg/m2), overweight (25 to 25.9 kg.m2), obese (30 to 34.9 kg/m2), or morbidly obese (≥35 kg/m2). Assessed risk factors for coronary artery disease included age, hyperlipidemia, hypertension, diabetes mellitus, smoking, cocaine use, aspirin use, and previous percutaneous coronary intervention or previous coronary artery bypass graft surgery. Characteristics of clinical presentation included ST-elevation AMI versus non–ST-elevation AMI, number of diseased vessels, presence of anterior AMI, ventricular arrhythmias, congestive heart failure, shock, required intubation, Killip’s class III or IV, and ejection fraction. Outcome variables were length of stay, groin complications after percutaneous intervention, mortality, readmissions, and the need for percutaneous coronary intervention or coronary artery bypass graft surgery.
The chi-square test was used to test for differences in proportions of BMI categories for categorical variables. Analysis of variance was used to test for differences in means of BMI categories for quantitative variables. Logistic and multiple regression techniques were used to model and test for hypotheses concerning mortality, length of stay, age, and disease severity to determine the effect of BMI after adjustment for other risk factors, demographics, and other contextual variables.
From 327 chart records, the final study population consisted of 284 subjects (31.7% women, 64.2% white), with a mean BMI of 28.8 kg/m2. Forty-three patients were excluded due to incomplete BMI data or a miscode in the database. Distributions of demographic parameters across groups are listed in Table 1. Obese patients were significantly more likely than their nonobese counterparts to have hyperlipidemia (p = 0.02) and hypertension (p = 0.034); otherwise the groups were similar at baseline. Similarly, characteristics of clinical presentation (Table 2) were similar across BMI categories with 1 exception, i.e., underweight patients (BMI <20 kg/m2) had a higher rate of ST-elevation AMI (65%) than normal weight patients (40%, p = 0.014). Conversely, morbidly obese patients (BMI >35 kg/m2) had a lower rate of ST-elevation AMI (21%) than normal weight patients (40%, p = 0.014). Table 3 presents the results of intervention strategies, which were no different between obese and normal weight subjects. There was no statistically significant correlation between BMI and AMI-related outcomes including mortality, length of stay, readmissions, and revascularization (Table 4).
Table 1Characteristics of 284 study participants according to body mass index (BMI) category
Table 5 presents results of stepwise multiple logistic regression analysis of in-hospital mortality. Factors not found to be statistically significant in the regression analysis included hypertension, cocaine use, family history, previous coronary artery disease, BMI, patients with >2 coronary risk factors, previous coronary artery bypass graft surgery, and hyperlipidemia. Diabetes mellitus and previous aspirin use were the only variables selected in the regression analysis as predictors of in-hospital mortality. Diabetes mellitus and aspirin use increased the odds of in-hospital mortality during AMI by approximately 280% (p = 0.018) and 250% (p = 0.032), respectively.
Table 5Final statistics of stepwise multiple logistic regression analysis of in-hospital mortality
95% CI for Exp (B)
CI = confidence interval; df = degrees of freedom.
Results of the adjusted multiple linear regression used to model BMI with age are shown in Figure 1. After correction for diabetes mellitus and aspirin use, BMI was found to be negatively associated with age (p = 0.003), i.e., the higher the BMI, the younger the age at presentation with AMI.
In this retrospective study, no statistically significant associations between BMI and outcomes in AMI including morbidity, mortality, length of stay, readmission rate, and type of revascularization were identified. Previously published studies that assessed the relation between BMI and outcomes for AMI have predominately been substudies of larger clinical trials. Most published studies have not specifically addressed in-hospital morbidity and mortality. They have largely examined only long-term outcomes after AMI, thus making it difficult to determine how lifestyle modifications after AMI affected the data. This study is unique because it is was designed specifically to address the question regarding the relation between obesity and in-hospital outcomes in AMI.
Results of previous studies with regard to long-term outcomes in obese patients after AMI are limited and inconsistent. There has been evidence that obese patient fare worse and evidence that they fare better than nonobese patients after AMI. Rana et al
reported in 2004 that BMI appeared to have a positive relation with death after AMI within 1 to 6 years of a confirmed AMI. Their data were limited not only by the possibility of confounding changes in lifestyle after the AMI but also by only 24% of patients being obese and very obese, which limited the statistical power. Kaplan et al
reported a U-shaped relation between BMI and death among survivors of a first AMI. However, their analysis lacked information on a significant association between BMI and death after AMI among patients who were <65 years of age. In addition, Rea et al
found no statistically significant difference in the 10-year survival of patients with coronary artery disease after cardiac catheterization after adjusting for baseline differences. Similar to our findings, they demonstrated that obese patients with acute coronary syndrome were younger at the time of presentation. Lopez-Jimenez et al
found that, despite a higher prevalence of other cardiovascular risk factors among overweight and obese patients, these patients actually had lower mortality after AMI and a similar rate of cardiac events compared with their normal weight counterparts.
This study also showed that patients with a BMI <20 kg/m2 have a higher rate of ST-elevation AMI and were less likely to receive medical therapy (aspirin, anticoagulation, and β-blocker therapy). Patients with AMI and a BMI <20 kg/m2 were found to have a higher prevalence of concomitant illnesses such as tumor, leukemia, and lymphoma.
Therefore, the higher incidence of ST-elevation AMI could be due to systemic illness that predisposed to a hypercoagulable state, thus increasing the chance of plaque rupture. In addition, complications related to these systemic illnesses may have precluded the use of further medical therapy during AMI.
Only the presence of diabetes mellitus and previous aspirin use were selected as predicting in-hospital mortality in this study. This is consistent with previous findings and the inclusion of previous aspirin use as a component of the Thrombolysis In Myocardial Infarction risk score for non–ST-elevation AMI.
Multiple linear regression was used to model BMI with age after adjusting for aspirin use and diabetes. BMI was negatively associated with age (p = 0.003). This finding is in accordance with several other studies that have demonstrated that obese patients tend to present with AMI at a younger age.