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Alternative methods for screening periodontal disease in adults
E E Machtei1, L A Christersson, J J Zambon
1Department of Oral Biology, School of Dental Medicine, Faculty of Health Sciences, State University of New York, Buffalo.
Journal of Clinical Periodontology
|February 1, 1993
Summary
Accurate periodontal disease diagnosis is challenging. Radiographic bone loss and probing pocket depth best correlate with attachment loss, while bacterial assays like P. gingivalis show potential in logistic models for screening.
Area of Science:
- Dentistry
- Periodontology
- Oral Health
Background:
- Clinical attachment loss measurements are standard for diagnosing adult periodontitis but are difficult and labor-intensive.
- Existing indices often inaccurately estimate periodontal disease prevalence and severity.
- Alternative diagnostic parameters are needed to improve accuracy and efficiency in periodontal assessment.
Purpose of the Study:
- To evaluate the correlation of alternative clinical, radiographic, and microbiological parameters with established periodontitis.
- To assess the diagnostic utility of these parameters for screening periodontal disease in adults.
Main Methods:
- A study involving 508 adults with comprehensive periodontal examinations.
- Evaluated probing pocket depth, clinical attachment level, plaque, gingival, and calculus scores.
- Included radiographic analysis for alveolar bone loss and subgingival pathogen assays.
Main Results:
- Radiographic alveolar bone loss (phi=0.72) and probing pocket depth (phi=0.75) showed the highest correlation with clinical attachment loss.
- Plaque, gingival, and calculus scores demonstrated poor correlation with established periodontitis.
- Porphyromonas gingivalis significantly contributed to predicting periodontitis probability in logistic regression models (OR=6.25).
Conclusions:
- Radiographic and probing depth measurements are reliable indicators for assessing periodontal disease severity.
- Microbiological assays, particularly for P. gingivalis, can enhance predictive models for periodontitis.
- A combination of parameters offers improved screening potential for periodontal disease.