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Clinical Trial Summary

The association between weight, and cardiovascular disease and mortality is well established, however, the causal effect of weight-loss in midlife on these outcomes is less clear. Bariatric surgery results in substantial weight-loss and is an ideal candidate to study the causal effects of weight-loss. We propose a project that will use causal inference and machine learning methods to answer two important questions: 1. Is bariatric surgery effective for reducing cardiovascular disease and mortality, and if so, for who? 2. Which type of bariatric surgery (gastric bypass or sleeve gastrectomy) is most effective, and for who? We will use data from various Swedish registers to identify individuals with obesity who are eligible for bariatric surgery. We will then compare cardiovascular and mortality outcomes among those undergoing different types of bariatric surgery with those receiving non-surgical obesity management using causal inference methods. We will use causal forests and expert knowledge to estimate indiviual treatment effects, and identify the groups of patients who benefit the most from these surgeries.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms


NCT number NCT06420479
Study type Observational [Patient Registry]
Source Karolinska Institutet
Contact Conor MacDonald, PhD
Phone 0000
Email conor.macdonald@ki.se
Status Recruiting
Phase
Start date January 1, 2024
Completion date December 31, 2027

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