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Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass
AIM: To evaluate the accuracy of DiaBetter, DiaRem, Ad-DiaRem and 5y-Ad-DiaRem scores’ at predicting T2D remission 10 or more years after surgery. METHODS: Patients with obesity and T2D (n = 126) submitted to RYGB with 10 or more years of follow-up. It was a unicentric trial. Pre-operative anthropom...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Milan
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289962/ https://www.ncbi.nlm.nih.gov/pubmed/37085634 http://dx.doi.org/10.1007/s00592-023-02092-1 |
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author | Cardoso, Samuel Pereira, Sofia S. Almeida, Rui F. Osório, Catarina Silva, Diogo Nora, Mário Monteiro, Mariana P. Guimarães, Marta |
author_facet | Cardoso, Samuel Pereira, Sofia S. Almeida, Rui F. Osório, Catarina Silva, Diogo Nora, Mário Monteiro, Mariana P. Guimarães, Marta |
author_sort | Cardoso, Samuel |
collection | PubMed |
description | AIM: To evaluate the accuracy of DiaBetter, DiaRem, Ad-DiaRem and 5y-Ad-DiaRem scores’ at predicting T2D remission 10 or more years after surgery. METHODS: Patients with obesity and T2D (n = 126) submitted to RYGB with 10 or more years of follow-up. It was a unicentric trial. Pre-operative anthropometric and clinical data was retrieved to calculate DiaRem, DiaBetter, Ad-DiaRem and 5y-Ad-DiaRem scores, while a hospital visit was conducted to assess current diabetes status. The area under the receiver operating characteristic (AUROC) curve was calculated as estimate of the scores’ accuracy to predict long-term T2D remission. RESULTS: Among the entire cohort (n = 126), 70 subjects (55.6%) achieved and maintained T2D remission 10 or more years after RYGB. The 5y-Ad-DiaRem score was the one that depicted the highest discriminative power (AUROC = 0.838) to predict long-term T2D remission when compared to DiaBetter (AUROC = 0.735), DiaRem (AUROC = 0.721) and Ad-DiaRem (AUROC = 0.720). CONCLUSION: The score with highest accuracy to predict long-term T2D remission after RYGB surgery was the 5y-Ad-DiaRem. Yet, the available scores accuracy to predict T2D remission in the long term is still suboptimal, highlighting the unmet need for a better scoring system. |
format | Online Article Text |
id | pubmed-10289962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Milan |
record_format | MEDLINE/PubMed |
spelling | pubmed-102899622023-06-25 Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass Cardoso, Samuel Pereira, Sofia S. Almeida, Rui F. Osório, Catarina Silva, Diogo Nora, Mário Monteiro, Mariana P. Guimarães, Marta Acta Diabetol Original Article AIM: To evaluate the accuracy of DiaBetter, DiaRem, Ad-DiaRem and 5y-Ad-DiaRem scores’ at predicting T2D remission 10 or more years after surgery. METHODS: Patients with obesity and T2D (n = 126) submitted to RYGB with 10 or more years of follow-up. It was a unicentric trial. Pre-operative anthropometric and clinical data was retrieved to calculate DiaRem, DiaBetter, Ad-DiaRem and 5y-Ad-DiaRem scores, while a hospital visit was conducted to assess current diabetes status. The area under the receiver operating characteristic (AUROC) curve was calculated as estimate of the scores’ accuracy to predict long-term T2D remission. RESULTS: Among the entire cohort (n = 126), 70 subjects (55.6%) achieved and maintained T2D remission 10 or more years after RYGB. The 5y-Ad-DiaRem score was the one that depicted the highest discriminative power (AUROC = 0.838) to predict long-term T2D remission when compared to DiaBetter (AUROC = 0.735), DiaRem (AUROC = 0.721) and Ad-DiaRem (AUROC = 0.720). CONCLUSION: The score with highest accuracy to predict long-term T2D remission after RYGB surgery was the 5y-Ad-DiaRem. Yet, the available scores accuracy to predict T2D remission in the long term is still suboptimal, highlighting the unmet need for a better scoring system. Springer Milan 2023-04-21 2023 /pmc/articles/PMC10289962/ /pubmed/37085634 http://dx.doi.org/10.1007/s00592-023-02092-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Cardoso, Samuel Pereira, Sofia S. Almeida, Rui F. Osório, Catarina Silva, Diogo Nora, Mário Monteiro, Mariana P. Guimarães, Marta Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title | Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title_full | Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title_fullStr | Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title_full_unstemmed | Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title_short | Accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
title_sort | accuracy of prediction models for long-term type 2 diabetes remission after gastric bypass |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289962/ https://www.ncbi.nlm.nih.gov/pubmed/37085634 http://dx.doi.org/10.1007/s00592-023-02092-1 |
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