Discovering potential pathways between type 2 diabetes mellitus and diabetic retinopathy: A big data analysis of the South Korean National Sample Cohort
Diabetes mellitus, a prevalent metabolic disorder, is associated with a multitude of complications that necessitate vigilant management post-diagnosis. A notable complication, diabetic retinopathy, could lead to intense ocular injury, including vision impairment and blindness, due to the impact of t...
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| Veröffentlicht in: | Medicine (Baltimore) 2023-08, Vol.102 (31), p.e34576-e34576 |
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| creator | Kim, Yoojoong Hyun, Changwan Lee, Minhyeok |
| description | Diabetes mellitus, a prevalent metabolic disorder, is associated with a multitude of complications that necessitate vigilant management post-diagnosis. A notable complication, diabetic retinopathy, could lead to intense ocular injury, including vision impairment and blindness, due to the impact of the disease. Studying the transition from diabetes to diabetic retinopathy is paramount for grasping and halting the progression of complications. In this study, we examine the statistical correlation between type 2 diabetes mellitus and retinal disorders classified elsewhere, ultimately proposing a comprehensive disease network. The National Sample Cohort of South Korea, containing approximately 1 million samples and primary diagnoses based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision classification, was utilized for this retrospective analysis. The diagnoses of both conditions displayed a statistically significant correlation with a chi-square test value of P |
| doi_str_mv | 10.1097/MD.0000000000034576 |
| format | Article |
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A notable complication, diabetic retinopathy, could lead to intense ocular injury, including vision impairment and blindness, due to the impact of the disease. Studying the transition from diabetes to diabetic retinopathy is paramount for grasping and halting the progression of complications. In this study, we examine the statistical correlation between type 2 diabetes mellitus and retinal disorders classified elsewhere, ultimately proposing a comprehensive disease network. The National Sample Cohort of South Korea, containing approximately 1 million samples and primary diagnoses based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision classification, was utilized for this retrospective analysis. The diagnoses of both conditions displayed a statistically significant correlation with a chi-square test value of P < .001, and the t test for the initial diagnosis date also yielded a P < .001 value. The devised network, comprising 27 diseases and 142 connections, was established through statistical evaluations. This network offers insight into potential pathways leading to diabetic retinopathy and intermediary diseases, encouraging medical researchers to further examine various risk factors associated with these connections.</description><identifier>ISSN: 0025-7974</identifier><identifier>EISSN: 1536-5964</identifier><identifier>DOI: 10.1097/MD.0000000000034576</identifier><identifier>PMID: 37543803</identifier><language>eng</language><publisher>United States: Lippincott Williams & Wilkins</publisher><subject>Blindness ; Diabetes Mellitus, Type 2 - complications ; Diabetes Mellitus, Type 2 - epidemiology ; Diabetic Retinopathy - complications ; Humans ; Observational Study ; Retrospective Studies ; Risk Factors</subject><ispartof>Medicine (Baltimore), 2023-08, Vol.102 (31), p.e34576-e34576</ispartof><rights>Copyright © 2023 the Author(s). 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Published by Wolters Kluwer Health, Inc. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c356t-2c620cb51460ffe9fc59d6cbadb0ae2352b83af72b275edfae636621028865cd3</cites><orcidid>0000-0002-6615-9116 ; 0000-0003-2562-172 ; 0000-0003-2562-172X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402935/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402935/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37543803$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Yoojoong</creatorcontrib><creatorcontrib>Hyun, Changwan</creatorcontrib><creatorcontrib>Lee, Minhyeok</creatorcontrib><title>Discovering potential pathways between type 2 diabetes mellitus and diabetic retinopathy: A big data analysis of the South Korean National Sample Cohort</title><title>Medicine (Baltimore)</title><addtitle>Medicine (Baltimore)</addtitle><description>Diabetes mellitus, a prevalent metabolic disorder, is associated with a multitude of complications that necessitate vigilant management post-diagnosis. A notable complication, diabetic retinopathy, could lead to intense ocular injury, including vision impairment and blindness, due to the impact of the disease. Studying the transition from diabetes to diabetic retinopathy is paramount for grasping and halting the progression of complications. In this study, we examine the statistical correlation between type 2 diabetes mellitus and retinal disorders classified elsewhere, ultimately proposing a comprehensive disease network. The National Sample Cohort of South Korea, containing approximately 1 million samples and primary diagnoses based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision classification, was utilized for this retrospective analysis. The diagnoses of both conditions displayed a statistically significant correlation with a chi-square test value of P < .001, and the t test for the initial diagnosis date also yielded a P < .001 value. The devised network, comprising 27 diseases and 142 connections, was established through statistical evaluations. This network offers insight into potential pathways leading to diabetic retinopathy and intermediary diseases, encouraging medical researchers to further examine various risk factors associated with these connections.</description><subject>Blindness</subject><subject>Diabetes Mellitus, Type 2 - complications</subject><subject>Diabetes Mellitus, Type 2 - epidemiology</subject><subject>Diabetic Retinopathy - complications</subject><subject>Humans</subject><subject>Observational Study</subject><subject>Retrospective Studies</subject><subject>Risk Factors</subject><issn>0025-7974</issn><issn>1536-5964</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdUU1v1TAQtBAVfRR-ARLykUuKY8dOwgVV7_GltnAonK2Ns3kxSuJgO63yT_i5ddVHC-xhV9qdGVszhLzK2WnO6vLt5e6UPZYoZKmekE0uhcpkrYqnZMMYl1lZl8UxeR7CT8ZyUfLiGTkWpSxExcSG_N7ZYNw1ejvt6ewiTtHCQGeI_Q2sgTYYbxAnGtcZKaethbTBQEccBhuXQGFqD1trqE99cnfk9R09o43d0xYiJBAMa7CBuo7GHumVW2JPz51HmOhXiNYlAL2CcR6Qbl3vfHxBjjoYAr48zBPy4-OH79vP2cW3T1-2ZxeZEVLFjBvFmWlkXijWdVh3RtatMg20DQPkQvKmEtCVvOGlxLYDVEIpnjNeVUqaVpyQ9_e689KM2JpkgIdBz96O4FftwOp_L5Pt9d5d65wVjNdCJoU3BwXvfi0Yoh6Tp8kfmNAtQfOqUDUXQokEFfdQ410IHruHd3Km70LVlzv9f6iJ9frvLz5w_qQobgEL5KEF</recordid><startdate>20230804</startdate><enddate>20230804</enddate><creator>Kim, Yoojoong</creator><creator>Hyun, Changwan</creator><creator>Lee, Minhyeok</creator><general>Lippincott Williams & Wilkins</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-6615-9116</orcidid><orcidid>https://orcid.org/0000-0003-2562-172</orcidid><orcidid>https://orcid.org/0000-0003-2562-172X</orcidid></search><sort><creationdate>20230804</creationdate><title>Discovering potential pathways between type 2 diabetes mellitus and diabetic retinopathy: A big data analysis of the South Korean National Sample Cohort</title><author>Kim, Yoojoong ; Hyun, Changwan ; Lee, Minhyeok</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-2c620cb51460ffe9fc59d6cbadb0ae2352b83af72b275edfae636621028865cd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Blindness</topic><topic>Diabetes Mellitus, Type 2 - complications</topic><topic>Diabetes Mellitus, Type 2 - epidemiology</topic><topic>Diabetic Retinopathy - complications</topic><topic>Humans</topic><topic>Observational Study</topic><topic>Retrospective Studies</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Yoojoong</creatorcontrib><creatorcontrib>Hyun, Changwan</creatorcontrib><creatorcontrib>Lee, Minhyeok</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Medicine (Baltimore)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Yoojoong</au><au>Hyun, Changwan</au><au>Lee, Minhyeok</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discovering potential pathways between type 2 diabetes mellitus and diabetic retinopathy: A big data analysis of the South Korean National Sample Cohort</atitle><jtitle>Medicine (Baltimore)</jtitle><addtitle>Medicine (Baltimore)</addtitle><date>2023-08-04</date><risdate>2023</risdate><volume>102</volume><issue>31</issue><spage>e34576</spage><epage>e34576</epage><pages>e34576-e34576</pages><issn>0025-7974</issn><eissn>1536-5964</eissn><abstract>Diabetes mellitus, a prevalent metabolic disorder, is associated with a multitude of complications that necessitate vigilant management post-diagnosis. A notable complication, diabetic retinopathy, could lead to intense ocular injury, including vision impairment and blindness, due to the impact of the disease. Studying the transition from diabetes to diabetic retinopathy is paramount for grasping and halting the progression of complications. In this study, we examine the statistical correlation between type 2 diabetes mellitus and retinal disorders classified elsewhere, ultimately proposing a comprehensive disease network. The National Sample Cohort of South Korea, containing approximately 1 million samples and primary diagnoses based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision classification, was utilized for this retrospective analysis. The diagnoses of both conditions displayed a statistically significant correlation with a chi-square test value of P < .001, and the t test for the initial diagnosis date also yielded a P < .001 value. 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| source | Wolters Kluwer Open Health; MEDLINE; DOAJ Directory of Open Access Journals; IngentaConnect Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Alma/SFX Local Collection |
| subjects | Blindness Diabetes Mellitus, Type 2 - complications Diabetes Mellitus, Type 2 - epidemiology Diabetic Retinopathy - complications Humans Observational Study Retrospective Studies Risk Factors |
| title | Discovering potential pathways between type 2 diabetes mellitus and diabetic retinopathy: A big data analysis of the South Korean National Sample Cohort |
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