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Health system wide “big data” analysis of rheumatologic conditions and scleritis
BACKGROUND: The development of scleritis in the setting of autoimmune conditions has been well documented. Prior series have assessed the relationship between systemic autoimmune disorders and scleritis only in patients referred for rheumatologic or ocular inflammation. This can lead to a referral b...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788757/ https://www.ncbi.nlm.nih.gov/pubmed/33407267 http://dx.doi.org/10.1186/s12886-020-01769-3 |
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author | Berkenstock, Meghan K. Carey, Andrew R. |
author_facet | Berkenstock, Meghan K. Carey, Andrew R. |
author_sort | Berkenstock, Meghan K. |
collection | PubMed |
description | BACKGROUND: The development of scleritis in the setting of autoimmune conditions has been well documented. Prior series have assessed the relationship between systemic autoimmune disorders and scleritis only in patients referred for rheumatologic or ocular inflammation. This can lead to a referral bias. We reviewed all charts within the electronic medical record (EMR) of a health system for patients with systemic autoimmune and scleritis diagnoses to determine the prevalence of both and which disorders had the highest relative risk of developing scleritis. METHODS: The EMR was searched for scleritis and systemic inflammatory diagnoses in the past medical history and diagnosis tabs, and for associated disease specific laboratory values. The intersection of scleritis and systemic inflammatory conditions was assessed through searching both SNOMED Clinical Terminology and ICD-10 codes for diagnoses. The prevalence of each autoimmune disorder, scleritis prevalence, the percentage of patients with an autoimmune condition having scleritis, the percentage of patients with scleritis having an autoimmune condition; the relative risk (RR) of scleritis patients having a specific autoimmune disorder were calculated. RESULTS: A total of 5.9 million charts were searched with autoimmune conditions identified in 148,993 patients. The most common autoimmune conditions overall were HLA-B27-associated diseases (n = 26,680; prevalence 0.45%); rheumatoid arthritis (RA)(N = 19,923; prevalence 0.34%). Conversely, 2702 patients were identified with scleritis (prevalence 0.05%), of which 31.4% had an associated autoimmune condition. Patients with RA represented the highest percentage of patients with an autoimmune condition having scleritis. Granulomatosis with polyangiitis (GPA) represented the highest the percentage of patients with scleritis having an autoimmune condition. Sjogrens was the third most common condition associated with scleritis- making up 4.5% of cases. An association with juvenile idiopathic arthritis (JIA) was seen in 0.3% of patients. CONCLUSIONS: While this is the largest retrospective review examining the association between autoimmune disease and scleritis, the findings are similar to prior studies with nearly a third of scleritis patients having an underlying autoimmune diagnosis. Limitations of the study included accurate chart coding; having laboratory results within the searchable EMR. Future research is needed to delineate associations of systemic disease with the anatomic location of scleritis using EMR. |
format | Online Article Text |
id | pubmed-7788757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77887572021-01-07 Health system wide “big data” analysis of rheumatologic conditions and scleritis Berkenstock, Meghan K. Carey, Andrew R. BMC Ophthalmol Research Article BACKGROUND: The development of scleritis in the setting of autoimmune conditions has been well documented. Prior series have assessed the relationship between systemic autoimmune disorders and scleritis only in patients referred for rheumatologic or ocular inflammation. This can lead to a referral bias. We reviewed all charts within the electronic medical record (EMR) of a health system for patients with systemic autoimmune and scleritis diagnoses to determine the prevalence of both and which disorders had the highest relative risk of developing scleritis. METHODS: The EMR was searched for scleritis and systemic inflammatory diagnoses in the past medical history and diagnosis tabs, and for associated disease specific laboratory values. The intersection of scleritis and systemic inflammatory conditions was assessed through searching both SNOMED Clinical Terminology and ICD-10 codes for diagnoses. The prevalence of each autoimmune disorder, scleritis prevalence, the percentage of patients with an autoimmune condition having scleritis, the percentage of patients with scleritis having an autoimmune condition; the relative risk (RR) of scleritis patients having a specific autoimmune disorder were calculated. RESULTS: A total of 5.9 million charts were searched with autoimmune conditions identified in 148,993 patients. The most common autoimmune conditions overall were HLA-B27-associated diseases (n = 26,680; prevalence 0.45%); rheumatoid arthritis (RA)(N = 19,923; prevalence 0.34%). Conversely, 2702 patients were identified with scleritis (prevalence 0.05%), of which 31.4% had an associated autoimmune condition. Patients with RA represented the highest percentage of patients with an autoimmune condition having scleritis. Granulomatosis with polyangiitis (GPA) represented the highest the percentage of patients with scleritis having an autoimmune condition. Sjogrens was the third most common condition associated with scleritis- making up 4.5% of cases. An association with juvenile idiopathic arthritis (JIA) was seen in 0.3% of patients. CONCLUSIONS: While this is the largest retrospective review examining the association between autoimmune disease and scleritis, the findings are similar to prior studies with nearly a third of scleritis patients having an underlying autoimmune diagnosis. Limitations of the study included accurate chart coding; having laboratory results within the searchable EMR. Future research is needed to delineate associations of systemic disease with the anatomic location of scleritis using EMR. BioMed Central 2021-01-06 /pmc/articles/PMC7788757/ /pubmed/33407267 http://dx.doi.org/10.1186/s12886-020-01769-3 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Berkenstock, Meghan K. Carey, Andrew R. Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title | Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title_full | Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title_fullStr | Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title_full_unstemmed | Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title_short | Health system wide “big data” analysis of rheumatologic conditions and scleritis |
title_sort | health system wide “big data” analysis of rheumatologic conditions and scleritis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788757/ https://www.ncbi.nlm.nih.gov/pubmed/33407267 http://dx.doi.org/10.1186/s12886-020-01769-3 |
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