Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records.

Autor: Patel JS; Division of Dental Informatics, Department of Dental Public Health and Dental Informatics, Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA. patel.jay@temple.edu.; Department of Health Services Administration and Policy, College of Public Health, Temple University, Philadelphia, PA, USA. patel.jay@temple.edu.; Bio-Health Informatics, Indiana University School of Informatics and Computing, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA. patel.jay@temple.edu., Shin D; Department of Periodontology, IUSD, Indianapolis, IN, USA., Willis L; Division of Dental Informatics, Department of Dental Public Health and Dental Informatics, Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA., Zai A; Division of Dental Informatics, Department of Dental Public Health and Dental Informatics, Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA., Kumar K; Division of Dental Informatics, Department of Dental Public Health and Dental Informatics, Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA., Thyvalikakath TP; Division of Dental Informatics, Department of Dental Public Health and Dental Informatics, Indiana University School of Dentistry (IUSD), Indianapolis, IN, USA. tpt@iu.edu.; Bio-Health Informatics, Indiana University School of Informatics and Computing, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, IN, USA. tpt@iu.edu.; Center for Biomedical Informatics, Regenstrief Institute, Inc., Indianapolis, IN, USA. tpt@iu.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Oct 10; Vol. 13 (1), pp. 17065. Date of Electronic Publication: 2023 Oct 10.
DOI: 10.1038/s41598-023-44307-z
Abstrakt: 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.
(© 2023. Springer Nature Limited.)
Databáze: MEDLINE
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