Obesity paradox in coronary artery bypass grafting: Myth or reality?

Abstract

Obesity did not increase operative mortality, but it was associated with reduced late survival in patients undergoing primary isolated CABG. Our results raise concerns in supporting any protective effect of obesity in cardiovascular disease, specifically in patients undergoing surgical myocardial revascularization.

Effect of Body Mass Index on Postoperative Complications in Beating Coronary Artery Surgery

“…The term ‘obesity paradox’ explains a protective role of high BMI in patients with coronary artery disease, because of better early and long-term outcomes compared to patients with a low BMI (14–15). However, our findings revealed a statistically significant inclination for increased in-hospital mortality with decreasing BMI values (15). Our study revealed that BMI had no impact on postoperative AF.…”

Morbid obesity and perioperative complications

“…In light of these limitations, it is difficult to conclusively determine the association between BMI and perioperative mortality. Compared with normal weight patients, at this time the literature suggests a survival benefit in the lower BMI obesity range and worse long-term mortality at the higher BMI ranges (>40 kg/m 2 ) [41,42,44].…”

“…Though some surgical literature suggest that any increase in BMI over normal is associated with decreased survival [5,41], other surgical literature suggest an obesity paradox, where limited increases in BMI (in the 25-40 kg/m 2 range) may provide a survival benefit compared with normal weight patients [6 && ,42-44]. Analysis of ACS-NSQIP data on cardiovascular, orthopedic, and oncologic surgeries indicate that patients with BMI at least 25 kg/m 2 did not have an increased odds of 30-day mortality, and in fact those with BMI 25-40 kg/m 2 experienced significantly lower odds of 30-day mortality following abdominal aortic aneurysm repair, total hip arthroplasty, gastrectomy, and colectomy [6 && ].…”

“…Variables with a negative impact on survival, such as positive smoking status, increased age, recent weight loss, and increasing disease severity, are often correlated with a decreased BMI [5,[41][42][43]45], yet are not always accounted for in the analysis of large datasets [43]. Strategies to avoid these confounders are to account for them in multivariate analysis where possible, perform more detailed BMI stratification [45], and limit the analysis of survival data to long-term survival to avoid reverse causation (where decreased BMI itself is not the cause of poor outcomes, but rather is just a marker of the disease severity that results in decreased survival) [42][43][44].…”

“…Abdominal adiposity is associated with greater health risks but is imperfectly accounted for by using BMI [43,45]. Therefore, some authors suggest using waist circumference in research as a more meaningful marker of obesity health risk, or alternative measures of abdominal adiposity such as waist-to-hip ratio, waist-to-height ratio, or computed tomographic measurement of intra-abdominal fat [41,44,45].…”