Browsing by Subject "classification criteria"

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    Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records
    (Springer, 2023-10-10) Patel, Jay S.; Shin, Daniel; Willis, Lisa; Zai, Ahad; Kumar, Krishna; Thyvalikakath, Thankam P.; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.
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    Developing classification criteria for skin-predominant dermatomyositis: the Delphi process
    (Wiley, 2020-02) Concha, J. S. S.; Pena, S.; Gaffney, R. G.; Patel, B.; Tarazi, M.; Kushner, C. J.; Merola, J. F.; Fiorentino, D.; Dutz, J. P.; Goodfield, M.; Nyberg, F.; Volc-Platzer, B.; Fujimoto, M.; Ang, C. C.; Werth, V. P.; The Skin Myositis Delphi Group; Dermatology, School of Medicine
    Background The European League Against Rheumatism/American College of Rheumatology classification criteria for inflammatory myopathies are able to classify patients with skin-predominant dermatomyositis (DM). However, approximately 25% of patients with skin-predominant DM do not meet two of the three hallmark skin signs and fail to meet the criteria. Objectives To develop a set of skin-focused classification criteria that will distinguish cutaneous DM from mimickers and allow a more inclusive definition of skin-predominant disease. Methods An extensive literature review was done to generate items for the Delphi process. Items were grouped into categories of distribution, morphology, symptoms, antibodies, histology and contextual factors. Using REDCap™, participants rated these items in terms of appropriateness and distinguishing ability from mimickers. The relevance score ranged from 1 to 100, and the median score determined a rank-ordered list. A prespecified median score cut-off was decided by the steering committee and the participants. There was a pre-Delphi and two rounds of actual Delphi. Results There were 50 participating dermatologists and rheumatologists from North America, South America, Europe and Asia. After a cut-off score of 70 during the first round, 37 of the initial 54 items were retained and carried over to the next round. The cut-off was raised to 80 during round two and a list of 25 items was generated. Conclusions This project is a key step in the development of prospectively validated classification criteria that will create a more inclusive population of patients with DM for clinical research.