4.6 Article

Exploring periodontitis misclassification mechanisms under partial-mouth protocols

Journal

JOURNAL OF CLINICAL PERIODONTOLOGY
Volume 49, Issue 5, Pages 448-457

Publisher

WILEY
DOI: 10.1111/jcpe.13611

Keywords

bias; misclassification; periodontal disease; periodontitis; sensitivity and specificity

Funding

  1. National Center for Health Statistics from the Centers for Disease Control and Prevention

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This study investigated the reasons for misclassification of periodontitis under partial-mouth protocols (PMPs) and proposed a tooth selection method based on population rankings of clinical severity to enhance protocol validity.
Aim To investigate the sources of periodontitis misclassification under partial-mouth protocols (PMPs) and to explore possible approaches to enhancing protocol validity. Materials and Methods Using data from 10,680 adults with 244,999 teeth from the National Health and Nutrition Examination Survey, we compared tooth-, site-, and quadrant-specific periodontal parameters and case identification under full-mouth protocols and PMPs. Separately, we utilized population measures of tooth-specific periodontal severity to generate PMPs with tooth selection based on the population ranking of clinical severity and assessed the sensitivity of case identification. Results Symmetry of clinical severity was generally confirmed, with the exception of lingual inter-proximal sites, which yielded greater sensitivity in identifying periodontitis compared to buccal sites due to more severe pocketing and attachment loss on average. Misclassification of severe periodontitis occurred more frequently under commonly implemented PMPs compared to ranking-based selection of teeth, which yielded sensitivity estimates of 70.1%-79.4% with the selection of 8 teeth and reached 90% with the selection of only 14 teeth. Conclusions Clinical symmetry and sources of periodontitis misclassification were confirmed. The proposed selection of teeth based on population rankings of clinical severity yielded optimal sensitivity estimates for the detection of severe periodontitis and may present a favourable alternative to current options.

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