Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data

dc.contributor.authorFelix Gomez, Grace Gomez
dc.contributor.authorHugenberg, Steven T.
dc.contributor.authorZunt, Susan
dc.contributor.authorPatel, Jay S.
dc.contributor.authorWang, Mei
dc.contributor.authorRajapuri, Anushri Singh
dc.contributor.authorLembcke, Lauren R.
dc.contributor.authorRajendran, Divya
dc.contributor.authorSmith, Jonas C.
dc.contributor.authorCheriyan, Biju
dc.contributor.authorBoyd, LaKeisha J.
dc.contributor.authorEckert, George J.
dc.contributor.authorGrannis, Shaun J.
dc.contributor.authorSrinivasan, Mythily
dc.contributor.authorZero, Domenick T.
dc.contributor.authorThyvalikakath, Thankam P.
dc.contributor.departmentCariology, Operative Dentistry and Dental Public Health, School of Dentistry
dc.date.accessioned2024-02-27T16:37:27Z
dc.date.available2024-02-27T16:37:27Z
dc.date.issued2023-07-31
dc.description.abstractEstablished 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.
dc.eprint.versionFinal published version
dc.identifier.citationFelix Gomez GG, Hugenberg ST, Zunt S, et al. Characterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data. PLoS One. 2023;18(7):e0289335. Published 2023 Jul 31. doi:10.1371/journal.pone.0289335
dc.identifier.urihttps://hdl.handle.net/1805/38934
dc.language.isoen_US
dc.publisherPublic Library of Science
dc.relation.isversionof10.1371/journal.pone.0289335
dc.relation.journalPLoS One
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectAntinuclear antibodies
dc.subjectDry eye syndromes
dc.subjectSjogren's syndrome
dc.titleCharacterizing clinical findings of Sjögren's Disease patients in community practices using matched electronic dental-health record data
dc.typeArticle
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