BACKGROUND: The most common form of periodontitis is a variably progressive dynamic pathologic process that causes attachment loss, destroys the alveolar bone supporting a tooth, and terminates with tooth loss. We evaluated the loss of teeth of treated periodontal patients categorized by severity and risk. METHODS: Each of nine periodontists evaluated 100 consecutive periodontal maintenance patients. The disease severity and risk level were determined from data at the initial examination. The number of teeth lost was determined from data at the initial and maintenance visits. RESULTS: A stepwise regression analysis showed that disease (P = 0.0000478) and risk (P = 0.00129) scores predicted the mean tooth loss rate. The adjusted R(2) statistic was 88.56%. The ordinal logistic regression model showed that only the disease score (P <0.0005) was significantly associated with the probability of patients losing a specific number of teeth. CONCLUSIONS: Categorizing a patient by severity may be beneficial in the management of the periodontal patient. The disease score can be used to establish a criterion and target for care. For example, treatment can result in nearly no lost teeth when the severity is low, and this benefit is lost when the severity is high. The disease score provides an objective means to quickly determine severity. An increase in the disease score provides evidence that a new treatment plan is needed. Therefore, the effect of the routine use of the disease score could result in fewer patients with severe disease and reduce the number of teeth lost.
BACKGROUND: The most common form of periodontitis is a variably progressive dynamic pathologic process that causes attachment loss, destroys the alveolar bone supporting a tooth, and terminates with tooth loss. We evaluated the loss of teeth of treated periodontal patients categorized by severity and risk. METHODS: Each of nine periodontists evaluated 100 consecutive periodontal maintenance patients. The disease severity and risk level were determined from data at the initial examination. The number of teeth lost was determined from data at the initial and maintenance visits. RESULTS: A stepwise regression analysis showed that disease (P = 0.0000478) and risk (P = 0.00129) scores predicted the mean tooth loss rate. The adjusted R(2) statistic was 88.56%. The ordinal logistic regression model showed that only the disease score (P <0.0005) was significantly associated with the probability of patients losing a specific number of teeth. CONCLUSIONS: Categorizing a patient by severity may be beneficial in the management of the periodontal patient. The disease score can be used to establish a criterion and target for care. For example, treatment can result in nearly no lost teeth when the severity is low, and this benefit is lost when the severity is high. The disease score provides an objective means to quickly determine severity. An increase in the disease score provides evidence that a new treatment plan is needed. Therefore, the effect of the routine use of the disease score could result in fewer patients with severe disease and reduce the number of teeth lost.
Authors: John A Martin; Ashley C Grill; Abigail G Matthews; Don Vena; Van P Thompson; Ronald G Craig; Frederick A Curro Journal: J Periodontol Date: 2012-06-15 Impact factor: 6.993
Authors: Kenneth E Izuora; Echezona E Ezeanolue; Michael F Neubauer; Civon L Gewelber; Gayle L Allenback; Guogen Shan; Guillermo E Umpierrez Journal: Am J Med Sci Date: 2016-04-23 Impact factor: 2.378
Authors: Meredith M D'Amore; Debbie M Cheng; Nancy R Kressin; Judith Jones; Jeffrey H Samet; Michael Winter; Theresa W Kim; Richard Saitz Journal: J Subst Abuse Treat Date: 2011-04-06
Authors: Kenneth E Izuora; Echezona E Ezeanolue; Michael F Neubauer; Civon L Gewelber; Gayle L Allenback; Guillermo E Umpierrez Journal: J Clin Transl Endocrinol Date: 2016-06