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A comprehensive risk factor analysis using association rules in people with diabetic kidney disease

Association rule is a transparent machine learning method expected to share information about risks for chronic kidney disease (CKD) among diabetic patients, but its findings in clinical data are limited. We used the association rule to evaluate the risk for kidney disease in General and Worker diab...

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Autores principales: Toyama, Tadashi, Shimizu, Miho, Yamaguchi, Taihei, Kurita, Hidekazu, Morita, Tetsurou, Oshima, Megumi, Kitajima, Shinji, Hara, Akinori, Sakai, Norihiko, Hashiba, Atsushi, Takayama, Takuzo, Tajima, Atsushi, Furuichi, Kengo, Wada, Takashi, Iwata, Yasunori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359444/
https://www.ncbi.nlm.nih.gov/pubmed/37474635
http://dx.doi.org/10.1038/s41598-023-38811-5
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author Toyama, Tadashi
Shimizu, Miho
Yamaguchi, Taihei
Kurita, Hidekazu
Morita, Tetsurou
Oshima, Megumi
Kitajima, Shinji
Hara, Akinori
Sakai, Norihiko
Hashiba, Atsushi
Takayama, Takuzo
Tajima, Atsushi
Furuichi, Kengo
Wada, Takashi
Iwata, Yasunori
author_facet Toyama, Tadashi
Shimizu, Miho
Yamaguchi, Taihei
Kurita, Hidekazu
Morita, Tetsurou
Oshima, Megumi
Kitajima, Shinji
Hara, Akinori
Sakai, Norihiko
Hashiba, Atsushi
Takayama, Takuzo
Tajima, Atsushi
Furuichi, Kengo
Wada, Takashi
Iwata, Yasunori
author_sort Toyama, Tadashi
collection PubMed
description Association rule is a transparent machine learning method expected to share information about risks for chronic kidney disease (CKD) among diabetic patients, but its findings in clinical data are limited. We used the association rule to evaluate the risk for kidney disease in General and Worker diabetic cohorts. The absence of risk factors was examined for association with stable kidney function and worsening kidney function. A confidence value was used as an index of association, and a lift of > 1 was considered significant. Analyses were applied for individuals stratified by KDIGO’s (Kidney Disease: Improving Global Outcomes) CKD risk categories. A General cohort of 4935 with a mean age of 66.7 years and a Worker cohort of 2153 with a mean age of 47.8 years were included in the analysis. Good glycemic control was significantly related to stable kidney function in low-risk categories among the General cohort, and in very-high risk categories among the Worker cohort; confidences were 0.82 and 0.77, respectively. Similar results were found with poor glycemic control and worsening kidney function; confidences of HbA1c were 0.41 and 0.27, respectively. Similarly, anemia, obesity, and hypertension showed significant relationships in the low-risk General and very-high risk Worker cohorts. Stratified risk assessment using association rules revealed the importance of the presence or absence of risk factors.
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spelling pubmed-103594442023-07-22 A comprehensive risk factor analysis using association rules in people with diabetic kidney disease Toyama, Tadashi Shimizu, Miho Yamaguchi, Taihei Kurita, Hidekazu Morita, Tetsurou Oshima, Megumi Kitajima, Shinji Hara, Akinori Sakai, Norihiko Hashiba, Atsushi Takayama, Takuzo Tajima, Atsushi Furuichi, Kengo Wada, Takashi Iwata, Yasunori Sci Rep Article Association rule is a transparent machine learning method expected to share information about risks for chronic kidney disease (CKD) among diabetic patients, but its findings in clinical data are limited. We used the association rule to evaluate the risk for kidney disease in General and Worker diabetic cohorts. The absence of risk factors was examined for association with stable kidney function and worsening kidney function. A confidence value was used as an index of association, and a lift of > 1 was considered significant. Analyses were applied for individuals stratified by KDIGO’s (Kidney Disease: Improving Global Outcomes) CKD risk categories. A General cohort of 4935 with a mean age of 66.7 years and a Worker cohort of 2153 with a mean age of 47.8 years were included in the analysis. Good glycemic control was significantly related to stable kidney function in low-risk categories among the General cohort, and in very-high risk categories among the Worker cohort; confidences were 0.82 and 0.77, respectively. Similar results were found with poor glycemic control and worsening kidney function; confidences of HbA1c were 0.41 and 0.27, respectively. Similarly, anemia, obesity, and hypertension showed significant relationships in the low-risk General and very-high risk Worker cohorts. Stratified risk assessment using association rules revealed the importance of the presence or absence of risk factors. Nature Publishing Group UK 2023-07-20 /pmc/articles/PMC10359444/ /pubmed/37474635 http://dx.doi.org/10.1038/s41598-023-38811-5 Text en © The Author(s) 2023 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
Toyama, Tadashi
Shimizu, Miho
Yamaguchi, Taihei
Kurita, Hidekazu
Morita, Tetsurou
Oshima, Megumi
Kitajima, Shinji
Hara, Akinori
Sakai, Norihiko
Hashiba, Atsushi
Takayama, Takuzo
Tajima, Atsushi
Furuichi, Kengo
Wada, Takashi
Iwata, Yasunori
A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title_full A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title_fullStr A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title_full_unstemmed A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title_short A comprehensive risk factor analysis using association rules in people with diabetic kidney disease
title_sort comprehensive risk factor analysis using association rules in people with diabetic kidney disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359444/
https://www.ncbi.nlm.nih.gov/pubmed/37474635
http://dx.doi.org/10.1038/s41598-023-38811-5
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