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Pre-intervention clinical determinants and measured β-cell function as predictors of type 2 diabetes remission after Roux-en-Y gastric bypass surgery

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posted on 2021-08-16, 00:33 authored by Chanel Ligon, Ankit Shah, Malini Prasad, Blandine Laferrère
Background: Bariatric surgery results in improved glycemic control in individuals with type 2 diabetes. Single and clusters of clinical determinants have been identified as pre-surgery predictors of post-surgery diabetes remission. Our goal was to assess if the addition of measured pre-operative ß-cell function would improve established clinical models of prediction of diabetes remission.

Methods: Pre-surgery clinical characteristics, metabolic markers, and ß-cell function after oral and intravenous (IV) glucose challenges were assessed in 73 individuals with severe obesity and type 2 diabetes and again one year after gastric bypass surgery. Single and multivariate analyses were conducted with pre-operative variables to determine best predictive models of remission.

Results: Pre-surgery ß-cell glucose sensitivity, a surrogate of ß-cell function, was negatively correlated with known diabetes duration, HbA1c, insulin use, and the diabetes remission scores DiaRem and Ad-DiaRem (all p <0.001). Measured ß-cell function after oral glucose was 1.6-fold greater than after IV glucose challenge, and more strongly correlated with pre-operative clinical and metabolic characteristics. The addition of pre-operative ß-cell function to clinical models containing well-defined diabetes remission scores did not improve the model’s ability to predict diabetes remission post-RYGB.

Conclusions: The addition of measured β-cell function does not add predictive value to defined clinical models of diabetes remission one year after surgical weight loss.

Funding

The data presented were collected in part with grants from the American Diabetes Association (7-05-CR-18 and 1-09-CR-34), the National Institutes of Health (R01-DK-067561, R01-DK-098056, P30-DK-063608 and P30-DK-26687), by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant Number UL1TR001873, and past grant UL1TR000040 and UL1TR024156. AS was supported by KL2TR003018. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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