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Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis

This study aimed to assess the impact of diabetic retinopathy (DR) severity on the incidence of major adverse cardiac events (MACE) and end-stage renal disease (ESRD) in T1D patients. Patients diagnosed with T1D between 1999 and 2013 were identified from patient-level data of Taiwan’s National Healt...

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Autores principales: Wang, Wei-Ming, Ou, Huang-Tz, Wen, Miin-Jye, Su, Pei-Fang, Yang, Chen-Yi, Kuo, Te-Hui, Wang, Ming-Cheng, Lin, Wei-Hung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907198/
https://www.ncbi.nlm.nih.gov/pubmed/35264740
http://dx.doi.org/10.1038/s41598-022-08166-4
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author Wang, Wei-Ming
Ou, Huang-Tz
Wen, Miin-Jye
Su, Pei-Fang
Yang, Chen-Yi
Kuo, Te-Hui
Wang, Ming-Cheng
Lin, Wei-Hung
author_facet Wang, Wei-Ming
Ou, Huang-Tz
Wen, Miin-Jye
Su, Pei-Fang
Yang, Chen-Yi
Kuo, Te-Hui
Wang, Ming-Cheng
Lin, Wei-Hung
author_sort Wang, Wei-Ming
collection PubMed
description This study aimed to assess the impact of diabetic retinopathy (DR) severity on the incidence of major adverse cardiac events (MACE) and end-stage renal disease (ESRD) in T1D patients. Patients diagnosed with T1D between 1999 and 2013 were identified from patient-level data of Taiwan’s National Health Insurance Research database. A total of 1135 patients were included and classified into mild DR (n = 454), severe DR (n = 227), or non-DR (n = 454) by using propensity score matching. Multi-state model analyses, an extension of competing risk models with adjustment for transition-specific covariates for prediction of subsequent MACE and ESRD, were performed. MACE and ESRD risks were significantly higher in the severe DR patients; a 2.97-fold (1.73, 5.07) and 12.29-fold (6.50, 23.23) increase in the MACE risk among the severe DR patients compared to the mild DR and DR-free patients, respectively; and, a 5.91-fold (3.50, 9.99) and 82.31-fold (29.07, 233.04) greater ESRD risk of severe DR patients than that of the mild DR and DR-free groups, respectively (p < 0.001). Severity of DR was significantly associated with the late diabetes-related vascular events (i.e., MACE, ESRD) among T1D patients.
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spelling pubmed-89071982022-03-10 Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis Wang, Wei-Ming Ou, Huang-Tz Wen, Miin-Jye Su, Pei-Fang Yang, Chen-Yi Kuo, Te-Hui Wang, Ming-Cheng Lin, Wei-Hung Sci Rep Article This study aimed to assess the impact of diabetic retinopathy (DR) severity on the incidence of major adverse cardiac events (MACE) and end-stage renal disease (ESRD) in T1D patients. Patients diagnosed with T1D between 1999 and 2013 were identified from patient-level data of Taiwan’s National Health Insurance Research database. A total of 1135 patients were included and classified into mild DR (n = 454), severe DR (n = 227), or non-DR (n = 454) by using propensity score matching. Multi-state model analyses, an extension of competing risk models with adjustment for transition-specific covariates for prediction of subsequent MACE and ESRD, were performed. MACE and ESRD risks were significantly higher in the severe DR patients; a 2.97-fold (1.73, 5.07) and 12.29-fold (6.50, 23.23) increase in the MACE risk among the severe DR patients compared to the mild DR and DR-free patients, respectively; and, a 5.91-fold (3.50, 9.99) and 82.31-fold (29.07, 233.04) greater ESRD risk of severe DR patients than that of the mild DR and DR-free groups, respectively (p < 0.001). Severity of DR was significantly associated with the late diabetes-related vascular events (i.e., MACE, ESRD) among T1D patients. Nature Publishing Group UK 2022-03-09 /pmc/articles/PMC8907198/ /pubmed/35264740 http://dx.doi.org/10.1038/s41598-022-08166-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Article
Wang, Wei-Ming
Ou, Huang-Tz
Wen, Miin-Jye
Su, Pei-Fang
Yang, Chen-Yi
Kuo, Te-Hui
Wang, Ming-Cheng
Lin, Wei-Hung
Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title_full Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title_fullStr Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title_full_unstemmed Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title_short Association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
title_sort association of retinopathy severity with cardiovascular and renal outcomes in patients with type 1 diabetes: a multi-state modeling analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907198/
https://www.ncbi.nlm.nih.gov/pubmed/35264740
http://dx.doi.org/10.1038/s41598-022-08166-4
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