Metabolic surgery for the treatment of type 2 diabetes in patients with BMI lower than 35 kg/m2 : Why caution is still needed.
Bruno HalpernMarcio Correa ManciniPublished in: Obesity reviews : an official journal of the International Association for the Study of Obesity (2019)
Bariatric surgery has shifted from being a risky procedure to an evidence-based one, with proven benefits on all-cause mortality, cardiovascular disease, cancer, and diabetes control. The procedure has an overall positive result on type 2 diabetes mellitus (T2DM), with a substantial number of patients achieving disease remission. This has resulted in several studies assessing possible weight-independent effects of bariatric surgery on glycemic improvement, in addition to recommendation of the procedure to patients with class 1 obesity and T2DM, for whom the procedure was classically not indicated, and adoption of a new term, "metabolic surgery," to highlight the overall metabolic benefit of the procedure beyond weight loss. Recently, the Diabetes Surgery Summit (DSS) has included metabolic surgery in its T2DM treatment algorithm. Although the discussion brought by this consensus is highly relevant, the recommendation of metabolic surgery for patients with uncontrolled T2DM and a body mass index of 30 to 35 kg/m2 still lacks enough evidence. This article provides an overall view of the metabolic benefits of bariatric/metabolic surgery in patients with class 1 obesity, compares the procedure against clinical treatment, and presents our rationale for defending caution on recommending the procedure to less obese individuals.
Keyphrases
- minimally invasive
- weight loss
- type diabetes
- bariatric surgery
- glycemic control
- cardiovascular disease
- coronary artery bypass
- body mass index
- roux en y gastric bypass
- insulin resistance
- weight gain
- surgical site infection
- metabolic syndrome
- obese patients
- clinical trial
- gastric bypass
- physical activity
- combination therapy
- newly diagnosed
- high fat diet induced
- deep learning
- machine learning
- rheumatoid arthritis
- cardiovascular events
- acute coronary syndrome
- coronary artery disease
- atrial fibrillation
- electronic health record
- clinical practice
- ulcerative colitis
- skeletal muscle
- papillary thyroid