Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data
Established classifications exist to confirm Sjögren's Disease (SD) (previously referred as Sjögren's Syndrome) and recruit patients for research. However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge denta...
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| Veröffentlicht in: | PloS one 2023-07, Vol.18 (7), p.e0289335-e0289335 |
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| creator | Felix Gomez, Grace Gomez Hugenberg, Steven T Zunt, Susan Patel, Jay S Wang, Mei Rajapuri, Anushri Singh Lembcke, Lauren R Rajendran, Divya Smith, Jonas C Cheriyan, Biju Boyd, LaKeisha J Eckert, George J Grannis, Shaun J Srinivasan, Mythily Zero, Domenick T Thyvalikakath, Thankam P |
| description | Established classifications exist to confirm Sjögren's Disease (SD) (previously referred as Sjögren's Syndrome) and recruit patients for research. However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge dental disease burden impairing their quality of life. This study established criteria to characterize Indiana University School of Dentistry (IUSD) patients' SD based on symptoms and signs in the electronic health record (EHR) data available through the state-wide Indiana health information exchange (IHIE). Association between SD diagnosis, and comorbidities including other autoimmune conditions, and documentation of SD diagnosis in electronic dental record (EDR) were also determined. The IUSD patients' EDR were linked with their EHR data in the IHIE and queried for SD diagnostic ICD9/10 codes. The resulting cohorts' EHR clinical findings were characterized and classified using diagnostic criteria based on clinical experts' recommendations. Descriptive statistics were performed, and Chi-square tests determined the association between the different SD presentations and comorbidities including other autoimmune conditions. Eighty-three percent of IUSD patients had an EHR of which 377 patients had a SD diagnosis. They were characterized as positive (24%), uncertain (20%) and negative (56%) based on EHR clinical findings. Dry eyes and mouth were reported for 51% and positive Anti-Ro/SSA antibodies and anti-nuclear antibody (ANA) for 17% of this study cohort. One comorbidity was present in 98% and other autoimmune condition/s were present in 53% respectively. Significant differences were observed between the three SD clinical characteristics/classifications and certain medical and autoimmune conditions (p |
| doi_str_mv | 10.1371/journal.pone.0289335 |
| format | Article |
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However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge dental disease burden impairing their quality of life. This study established criteria to characterize Indiana University School of Dentistry (IUSD) patients' SD based on symptoms and signs in the electronic health record (EHR) data available through the state-wide Indiana health information exchange (IHIE). Association between SD diagnosis, and comorbidities including other autoimmune conditions, and documentation of SD diagnosis in electronic dental record (EDR) were also determined. The IUSD patients' EDR were linked with their EHR data in the IHIE and queried for SD diagnostic ICD9/10 codes. The resulting cohorts' EHR clinical findings were characterized and classified using diagnostic criteria based on clinical experts' recommendations. Descriptive statistics were performed, and Chi-square tests determined the association between the different SD presentations and comorbidities including other autoimmune conditions. Eighty-three percent of IUSD patients had an EHR of which 377 patients had a SD diagnosis. They were characterized as positive (24%), uncertain (20%) and negative (56%) based on EHR clinical findings. Dry eyes and mouth were reported for 51% and positive Anti-Ro/SSA antibodies and anti-nuclear antibody (ANA) for 17% of this study cohort. One comorbidity was present in 98% and other autoimmune condition/s were present in 53% respectively. Significant differences were observed between the three SD clinical characteristics/classifications and certain medical and autoimmune conditions (p<0.05). Sixty-nine percent of patients' EDR did not mention SD, highlighting the huge gap in reporting SD during dental care. This study of SD patients diagnosed in community practices characterized three different SD clinical presentations, which can be used to generate SD study cohorts for longitudinal studies using EHR data. The results emphasize the heterogenous SD clinical presentations and the need for further research to diagnose SD early in community practice settings where most people seek care.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0289335</identifier><identifier>PMID: 37523369</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Antibodies ; Antibodies, Antinuclear ; Autoimmune diseases ; Biology and Life Sciences ; Biopsy ; Care and treatment ; Chi-square test ; Classification ; Clinical outcomes ; Codes ; Comorbidity ; Computational linguistics ; Computer and Information Sciences ; Criteria ; Data exchange ; Dental care ; Dental disorders ; Dentistry ; Dentists ; Diagnosis ; Diagnostic systems ; Disease ; Dry Eye Syndromes ; Electronic health records ; Electronic medical records ; Electronic records ; Evidence-based medicine ; Exocrine glands ; Health ; Health Information Exchange ; Humans ; Immune system ; Language processing ; Longitudinal studies ; Medical diagnosis ; Medical records ; Medical research ; Medicine and Health Sciences ; Medicine, Experimental ; Natural language interfaces ; Oral hygiene ; Patients ; Physicians ; Population ; Quality of Life ; Radiation ; Respiratory distress syndrome ; Ro(SSA) antigen ; Serology ; Signs and symptoms ; Sjogren's syndrome ; Sjogren's Syndrome - diagnosis ; Sjogren's Syndrome - epidemiology ; Viral antibodies</subject><ispartof>PloS one, 2023-07, Vol.18 (7), p.e0289335-e0289335</ispartof><rights>Copyright: © 2023 Felix Gomez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Felix Gomez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Felix Gomez et al 2023 Felix Gomez et al</rights><rights>2023 Felix Gomez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c693t-a14c18d3f05a5fb5b65d15d355cca46b92b604b5cd57b2e5e965fd685c817dd43</citedby><cites>FETCH-LOGICAL-c693t-a14c18d3f05a5fb5b65d15d355cca46b92b604b5cd57b2e5e965fd685c817dd43</cites><orcidid>0000-0003-2544-8568 ; 0000-0001-8729-2277 ; 0000-0003-3549-2124 ; 0000-0002-7294-2318 ; 0000-0001-7798-7155</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/PMC10389720/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10389720/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37523369$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Felix Gomez, Grace Gomez</creatorcontrib><creatorcontrib>Hugenberg, Steven T</creatorcontrib><creatorcontrib>Zunt, Susan</creatorcontrib><creatorcontrib>Patel, Jay S</creatorcontrib><creatorcontrib>Wang, Mei</creatorcontrib><creatorcontrib>Rajapuri, Anushri Singh</creatorcontrib><creatorcontrib>Lembcke, Lauren R</creatorcontrib><creatorcontrib>Rajendran, Divya</creatorcontrib><creatorcontrib>Smith, Jonas C</creatorcontrib><creatorcontrib>Cheriyan, Biju</creatorcontrib><creatorcontrib>Boyd, LaKeisha J</creatorcontrib><creatorcontrib>Eckert, George J</creatorcontrib><creatorcontrib>Grannis, Shaun J</creatorcontrib><creatorcontrib>Srinivasan, Mythily</creatorcontrib><creatorcontrib>Zero, Domenick T</creatorcontrib><creatorcontrib>Thyvalikakath, Thankam P</creatorcontrib><title>Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Established classifications exist to confirm Sjögren's Disease (SD) (previously referred as Sjögren's Syndrome) and recruit patients for research. However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge dental disease burden impairing their quality of life. This study established criteria to characterize Indiana University School of Dentistry (IUSD) patients' SD based on symptoms and signs in the electronic health record (EHR) data available through the state-wide Indiana health information exchange (IHIE). Association between SD diagnosis, and comorbidities including other autoimmune conditions, and documentation of SD diagnosis in electronic dental record (EDR) were also determined. The IUSD patients' EDR were linked with their EHR data in the IHIE and queried for SD diagnostic ICD9/10 codes. The resulting cohorts' EHR clinical findings were characterized and classified using diagnostic criteria based on clinical experts' recommendations. Descriptive statistics were performed, and Chi-square tests determined the association between the different SD presentations and comorbidities including other autoimmune conditions. Eighty-three percent of IUSD patients had an EHR of which 377 patients had a SD diagnosis. They were characterized as positive (24%), uncertain (20%) and negative (56%) based on EHR clinical findings. Dry eyes and mouth were reported for 51% and positive Anti-Ro/SSA antibodies and anti-nuclear antibody (ANA) for 17% of this study cohort. One comorbidity was present in 98% and other autoimmune condition/s were present in 53% respectively. Significant differences were observed between the three SD clinical characteristics/classifications and certain medical and autoimmune conditions (p<0.05). Sixty-nine percent of patients' EDR did not mention SD, highlighting the huge gap in reporting SD during dental care. This study of SD patients diagnosed in community practices characterized three different SD clinical presentations, which can be used to generate SD study cohorts for longitudinal studies using EHR data. The results emphasize the heterogenous SD clinical presentations and the need for further research to diagnose SD early in community practice settings where most people seek care.</description><subject>Analysis</subject><subject>Antibodies</subject><subject>Antibodies, Antinuclear</subject><subject>Autoimmune diseases</subject><subject>Biology and Life Sciences</subject><subject>Biopsy</subject><subject>Care and treatment</subject><subject>Chi-square test</subject><subject>Classification</subject><subject>Clinical outcomes</subject><subject>Codes</subject><subject>Comorbidity</subject><subject>Computational linguistics</subject><subject>Computer and Information Sciences</subject><subject>Criteria</subject><subject>Data exchange</subject><subject>Dental care</subject><subject>Dental disorders</subject><subject>Dentistry</subject><subject>Dentists</subject><subject>Diagnosis</subject><subject>Diagnostic systems</subject><subject>Disease</subject><subject>Dry Eye Syndromes</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Electronic records</subject><subject>Evidence-based medicine</subject><subject>Exocrine glands</subject><subject>Health</subject><subject>Health Information Exchange</subject><subject>Humans</subject><subject>Immune system</subject><subject>Language processing</subject><subject>Longitudinal studies</subject><subject>Medical diagnosis</subject><subject>Medical records</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Medicine, Experimental</subject><subject>Natural language interfaces</subject><subject>Oral hygiene</subject><subject>Patients</subject><subject>Physicians</subject><subject>Population</subject><subject>Quality of Life</subject><subject>Radiation</subject><subject>Respiratory distress syndrome</subject><subject>Ro(SSA) antigen</subject><subject>Serology</subject><subject>Signs and 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clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data</title><author>Felix Gomez, Grace Gomez ; Hugenberg, Steven T ; Zunt, Susan ; Patel, Jay S ; Wang, Mei ; Rajapuri, Anushri Singh ; Lembcke, Lauren R ; Rajendran, Divya ; Smith, Jonas C ; Cheriyan, Biju ; Boyd, LaKeisha J ; Eckert, George J ; Grannis, Shaun J ; Srinivasan, Mythily ; Zero, Domenick T ; Thyvalikakath, Thankam P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c693t-a14c18d3f05a5fb5b65d15d355cca46b92b604b5cd57b2e5e965fd685c817dd43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Analysis</topic><topic>Antibodies</topic><topic>Antibodies, Antinuclear</topic><topic>Autoimmune diseases</topic><topic>Biology and Life Sciences</topic><topic>Biopsy</topic><topic>Care and treatment</topic><topic>Chi-square 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Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Felix Gomez, Grace Gomez</au><au>Hugenberg, Steven T</au><au>Zunt, Susan</au><au>Patel, Jay S</au><au>Wang, Mei</au><au>Rajapuri, Anushri Singh</au><au>Lembcke, Lauren R</au><au>Rajendran, Divya</au><au>Smith, Jonas C</au><au>Cheriyan, Biju</au><au>Boyd, LaKeisha J</au><au>Eckert, George J</au><au>Grannis, Shaun J</au><au>Srinivasan, Mythily</au><au>Zero, Domenick T</au><au>Thyvalikakath, Thankam P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2023-07-31</date><risdate>2023</risdate><volume>18</volume><issue>7</issue><spage>e0289335</spage><epage>e0289335</epage><pages>e0289335-e0289335</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Established classifications exist to confirm Sjögren's Disease (SD) (previously referred as Sjögren's Syndrome) and recruit patients for research. However, no established classification exists for diagnosis in clinical settings causing delayed diagnosis. SD patients experience a huge dental disease burden impairing their quality of life. This study established criteria to characterize Indiana University School of Dentistry (IUSD) patients' SD based on symptoms and signs in the electronic health record (EHR) data available through the state-wide Indiana health information exchange (IHIE). Association between SD diagnosis, and comorbidities including other autoimmune conditions, and documentation of SD diagnosis in electronic dental record (EDR) were also determined. The IUSD patients' EDR were linked with their EHR data in the IHIE and queried for SD diagnostic ICD9/10 codes. The resulting cohorts' EHR clinical findings were characterized and classified using diagnostic criteria based on clinical experts' recommendations. Descriptive statistics were performed, and Chi-square tests determined the association between the different SD presentations and comorbidities including other autoimmune conditions. Eighty-three percent of IUSD patients had an EHR of which 377 patients had a SD diagnosis. They were characterized as positive (24%), uncertain (20%) and negative (56%) based on EHR clinical findings. Dry eyes and mouth were reported for 51% and positive Anti-Ro/SSA antibodies and anti-nuclear antibody (ANA) for 17% of this study cohort. One comorbidity was present in 98% and other autoimmune condition/s were present in 53% respectively. Significant differences were observed between the three SD clinical characteristics/classifications and certain medical and autoimmune conditions (p<0.05). Sixty-nine percent of patients' EDR did not mention SD, highlighting the huge gap in reporting SD during dental care. This study of SD patients diagnosed in community practices characterized three different SD clinical presentations, which can be used to generate SD study cohorts for longitudinal studies using EHR data. The results emphasize the heterogenous SD clinical presentations and the need for further research to diagnose SD early in community practice settings where most people seek care.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>37523369</pmid><doi>10.1371/journal.pone.0289335</doi><tpages>e0289335</tpages><orcidid>https://orcid.org/0000-0003-2544-8568</orcidid><orcidid>https://orcid.org/0000-0001-8729-2277</orcidid><orcidid>https://orcid.org/0000-0003-3549-2124</orcidid><orcidid>https://orcid.org/0000-0002-7294-2318</orcidid><orcidid>https://orcid.org/0000-0001-7798-7155</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2023-07, Vol.18 (7), p.e0289335-e0289335 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2844074639 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Analysis Antibodies Antibodies, Antinuclear Autoimmune diseases Biology and Life Sciences Biopsy Care and treatment Chi-square test Classification Clinical outcomes Codes Comorbidity Computational linguistics Computer and Information Sciences Criteria Data exchange Dental care Dental disorders Dentistry Dentists Diagnosis Diagnostic systems Disease Dry Eye Syndromes Electronic health records Electronic medical records Electronic records Evidence-based medicine Exocrine glands Health Health Information Exchange Humans Immune system Language processing Longitudinal studies Medical diagnosis Medical records Medical research Medicine and Health Sciences Medicine, Experimental Natural language interfaces Oral hygiene Patients Physicians Population Quality of Life Radiation Respiratory distress syndrome Ro(SSA) antigen Serology Signs and symptoms Sjogren's syndrome Sjogren's Syndrome - diagnosis Sjogren's Syndrome - epidemiology Viral antibodies |
| title | Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data |
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