Real-world evidence of bariatric surgery and cardiovascular benefits using electronic health records data: A lesson in bias

Aim: To reproduce and correct studies on bariatric surgery and the reduction in major adverse cardiovascular events (MACE) among patients with obesity and type 2 diabetes (T2D). Methods: We used electronic healthcare records (EHR) from in and outpatient facilities around the United States to identify a cohort of patients with T2D, aged 18 to 80 years and with a body mass index (BMI) of 30 kg/m(2) or higher undergoing bariatric surgery. We compared against hip/knee arthroplasty to establish an active comparison group that reduced bias from differential information and confounding. The main outcome was six-point MACE. Pre-exposure characteristics were adjusted in propensity score (PS) models with 1:2 matching plus high-dimensional PS matching. Results: After a range of exclusions, the final cohort included 344 bariatric surgery patients (65% female; mean age 58 years) and 551 PS-matched patients undergoing arthroplasty (65% female; 59 years). Median follow-up was 2.5 years in both groups. Bariatric surgery patients showed a sustained 20% weight reduction and an HbA1c reduction by 1% point. We found no benefits of bariatric surgery for six-point MACE (HR = 0.99; 95% CI 0.76-1.30). We observed known increases in risks for vitamin B-12 deficiency anaemia (HR = 3.06; 1.10-8.49) and cholelithiasis (HR = 1.72; 0.94-3.13). Conclusions; This real-world evidence study found reductions in HbA1c and BMI following bariatric surgery similar to trials, and no meaningful cardiovascular benefit compatible with the underpowered trials but in contrast to earlier EHR studies. We showed how information bias typical in EHR analyses and confounding may cause substantial bias.

Automated summary

This real-world evidence study examined the effects of bariatric surgery on patients with T2D, showing weight and HbA1c reductions but no significant cardiovascular benefits, with potential increased risks of anemia and cholelithiasis. The study highlighted the potential biases caused by information bias and confounding in EHR analyses.