Impact of Extreme Obesity on STEMI and What it Means for the “Obesity Paradox”
2012 Parmley Prize winner
First Author: Sandeep R. Das, MD, MPH
University of Texas Southwestern Medical School
It’s a large group of ST-segment elevation myocardial infarction (STEMI) patients who are at lower a priori risk and receive similar care as other patients, but nevertheless have worse outcomes. Who makes up this growing group? Patients with extreme or “morbid” obesity.
Das and colleagues used the National Cardiovascular Data Registry (NCDR®) to evaluate the care and outcomes of more than 50,000 patients.1 A total of 5.1% of STEMI patients met criteria for Class III obesity (body mass index [BMI] >40 kg/m2); these patients tended to be younger and had higher rates of diabetes, hypertension and dyslipidemia, but lower prevalence of smoking and less extensive coronary artery disease. Process-of-care measures were similar across BMI categories.
Nevertheless, despite factors that should reduce risk, individuals with Class III obesity had significantly higher rates of risk-adjusted in-hospital mortality compared to the lowest-risk STEMI group: individuals with Class I obesity.
Obesity Paradox: Biggest Insight Yet
Besides demonstrating the impact of extreme obesity on in-hospital outcomes, an accompanying commentary by Lavie et al. noted that an equally important finding is their explanation of the obesity paradox.2 The NCDR data provide the best evidence yet of a U-shaped mortality curve, with the highest mortality in the "normal"-BMI group, followed by patients with Class III obesity. After adjusting for potential confounding factors, only the Class III obese patients appeared to have significantly higher in-hospital mortality (but not major bleeding complications).
The investigators indicate that the higher mortality in the "normal"-weight patients disappears after adjustment, suggesting confounders (such as older age, more extensive cardiac disease, or serious medical conditions) in these patients.
Although many prior studies have disputed this finding, in this very large cohort of patients with STEMI, it appears that confounding factors do indeed seem to partly explain the obesity paradox, at least regarding in-hospital mortality.
Obesity: The New Norm?
From 1960 to 2004, national estimates of obesity prevalence as a whole increased from 13.3% to 32.9%, a relative increase of almost 150%. Over the same time interval, however, the population prevalence of class III obesity increased from 0.9% to 5.1%, a relative increase of 460%.
In other words, the authors note, being normal weight in a contemporary population with cardiovascular disease (CVD) is now so uncommon that it may reflect the presence of unmeasured serious comorbid conditions. As such, “protective” effects that have been attributed to overweight and moderate obesity in patients with CVD may not actually exist and may simply reflect unmeasured confounding in the ever-shrinking population of normal-weight individuals.
Clearly, overweight and obesity are associated with high prevalence of almost all major CV diseases, including HF, atrial fibrillation, hypertension, and CHD. Despite the confounding factors, the "weight" of evidence still supports an obesity paradox in most CV disorders. Studies of purposeful weight loss using major CV end points are needed in the prevention and treatment of various CV disorders, especially CHD and HF.
Reference
- Das SR, Alexander KP, Chen AY, et al. Impact of body weight and extreme obesity on the presentation, treatment, and in-hospital outcomes of 50,149 patients with ST-segment elevation myocardial infarction: results from the NCDR (National Cardiovascular Data Registry) J Am Coll Cardiol 2011;58:2642-2650. http://content.onlinejacc.org/cgi/content/full/58/25/2642
- Lavie CJ, Milani RV, Ventura HO. Impact of obesity on outcomes in myocardial infarction combating the "obesity paradox". J Am Coll Cardiol 2011;58:2651-3. http://content.onlinejacc.org/cgi/content/full/58/25/2651
Keywords: Myocardial Infarction, Coronary Artery Disease, Hospital Mortality, Overweight, Weight Loss, Smoking, Prevalence, Registries, Dyslipidemias, Body Mass Index, Obesity, Morbid, Diabetes Mellitus, Hypertension
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