Quantcast

Periodontitis severity plus risk as a tooth loss predictor.

Research paper by John A JA Martin, Roy C RC Page, Elizabeth Krall EK Kaye, Mohamed T MT Hamed, Carl F CF Loeb

Indexed on: 04 Feb '09Published on: 04 Feb '09Published in: Journal of periodontology



Abstract

Tooth loss can be a consequence of the natural history of periodontitis. Stratification of periodontitis severity, risk, and tooth loss exists within the United States adult population, and tooth loss correlates to severity and risk. We evaluated the loss of teeth for a periodontitis-affected population categorized by the combination of severity and risk in which the subjects predominantly did not receive periodontal treatment.The clinical records of 523 subjects enrolled in the Veterans Affairs Dental Longitudinal Study, covering a period of 15 years, were used. Disease severity, risk level, and the number of teeth lost for each subject were determined.A stepwise regression analysis showed that disease and risk scores predicted mean tooth loss rate. The P value for the disease score was <0.0005, and the P value for the risk score was 0.001. The ordinal logistic regression model showed that disease (P = 0.002) and risk scores (P = 0.000) were significantly associated with the probability of subjects losing a specific number of teeth.Tooth loss is more precisely and accurately predicted by the combination of risk score and periodontal disease score than by either score alone. The combined scores may be a surrogate variable for periodontal status. Because the scores are derived from routine clinical measurements, they may be useful for population surveillance and dynamics, practice management, patient care decisions, practice-based research, and the determination of treatment effectiveness and the factors required for successful treatment, resulting in improved oral health and higher clinician productivity and income.