Journal of Periodontology · 2010 · 27 citations · 31 references
DentistryPeriodonticsPeriodontologyPeriodontal MedicinePeriodontal TherapyRisk Assessment In DentistryPeriodontal DiseasePeriodontal Disease Risk AssessmentPeriodontal ExaminationPeriodontal PrognosisPeriodontal Risk AssessmentPeriodontal Status EvaluationClinical Data ValidationComprehensive Periodontal ExaminationDisease Progression PredictionPeriodontal Disease PrognosisPeriodontal Disease Progression PredictionPeriodontal Progression Risk PredictionPeriodontal Risk PredictionRisk Prediction Algorithms
BACKGROUND: The American Academy of Periodontology has recently stated that, "[risk assessment will become] increasingly important in periodontal treatment planning and should be part of every comprehensive dental and periodontal evaluation." (J Periodontol 2006;77:1608). Unaided risk assessment and prognostication show significant variability because chronic periodontitis is a multifactorial disease. This report summarizes the clinical validation of an algorithm for chronic periodontitis risk assessment and prognostication. The algorithm is a Web-based analytic tool that integrates some 20 risk predictors and calculates scores indicating levels of risk for chronic periodontitis for the dentition (Level I) and, if an elevated risk is found, prognosticates disease progression tooth by tooth (Level II). METHODS: An independent clinical validation sample was generated in an open, prospective clinical trial and analyzed in a predetermined validation plan. RESULTS: The analyses identified two threshold scores above which significant progression of periodontitis was found. Based on these scores, sufficiently high explanatory values with significant and increasing parameter estimates for increasing risk were established in Level I, justifying detailed analysis tooth by tooth in Level II. Subsequent prognostication of chronic periodontitis in Level II was found to be accompanied by clinically relevant measures of quality in relation to rates of disease progression. Three score intervals representing increasing levels of periodontitis progression were identified corresponding to increasing levels of significant annual marginal bone loss. CONCLUSIONS: The predictors included in the algorithm reflect a relevant selection for periodontitis risk assessment. Risk assessment and prognostication with the algorithm provides the clinician with a validated, reliable, consistent, and objective tool supporting treatment planning.
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Problems and proposals for recording gingivitis and plaque.