AI Article Synopsis

  • Periodontal examinations are complex, and there's a need for a simplified index to evaluate periodontal health for public health purposes.
  • Existing periodontal indices use different selected teeth, but there's no clear justification for the choices made in those selections.
  • This study applied a graded response model to determine the best examination sites from data of 254 patients, identifying twelve specific teeth that can accurately represent overall periodontal conditions.

Article Abstract

Periodontal examination data have a complex structure. For epidemiological studies, mass screenings, and public health use, a simple index that represents the periodontal condition is necessary. Periodontal indices for partial examination of selected teeth have been developed. However, the selected teeth vary between indices, and a justification for the selection of examination teeth has not been presented. We applied a graded response model based on the item response theory to select optimal examination teeth and sites that represent periodontal conditions. Data were obtained from 254 patients who participated in a multicenter follow-up study. Baseline data were obtained from initial follow-up. Optimal examination sites were selected using item information calculated by graded response modeling. Twelve sites-maxillary 2nd premolar (palatal-medial), 1st premolar (palatal-distal), canine (palatal-medial), lateral incisor (palatal-central), central incisor (palatal-distal) and mandibular 1st premolar (lingual, medial)-were selected. Mean values for clinical attachment level, probing pocket depth, and bleeding on probing by full mouth examinations were used for objective variables. Measuring the clinical parameters of these sites can predict the results of full mouth examination. For calculating the periodontal index by partial oral examination, a justification for the selection of examination sites is essential. This study presents an evidence-based partial examination methodology and its modeling.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7700480PMC
http://dx.doi.org/10.3390/jcm9113754DOI Listing

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