Introduction of a prediction model to assigning periodontal prognosis based on survival time.

AIMS: To develop a prediction model for tooth loss due to periodontal disease (TLPD) in patients following periodontal maintenance (PM), and assess its performance using a multicentre approach. MATERIAL AND METHODS: A multilevel analysis of eleven predictors of TLPD in 500 patients following PM was carried out to calculate the probability of TLPD. This algorithm was applied to three different TLPD samples (369 teeth) gathered retrospectively by nine periodontist, associating several intervals of probability with the corresponding survival time, based on significant differences in the mean survival time. The reproducibility of these associations was assessed in each sample (One-way ANOVA and pairwise comparison with Bonferroni corrections). RESULTS: The model presented high specificity and moderate sensitivity, with optimal calibration and discrimination measurements. Seven intervals of probability were associated with seven survival time and these associations contained close to 80% of the cases: the probability predicted the survival time at this percentage. The model performed well in the three samples, as the mean survival time of each association were significantly different within each sample, while no significant differences between the samples were found in pairwise comparisons of means. CONCLUSIONS: This model might be useful for predicting survival time in different TLPD samples.

A comprehensive approach to assigning periodontal prognosis.

AIM: The purpose of this retrospective case series study was to evaluate the usefulness and performance of a comprehensive approach to assigning periodontal prognosis by assessing the risk of tooth loss due to periodontal disease (TLPD) and estimate the survival time (ST) of periodontally compromised teeth (PCT). MATERIAL AND METHODS: The Long-Term Outcome (LTO) index was utilized to assess the risk of TLPD, at baseline, in 100 patients following periodontal maintenance for a mean 24.7 year (±2.4). A TLPD prediction model was utilized to assign ST to PCT. The performance of the TLPD prediction based on both parameters was assessed. RESULTS: The mean TLPD rate increased as the LTO index increased (Kruskal-Wallis p < .001). The percentage of TLPD increased as the ST decreased, with significantly differences between the LTO categories <4 and ≥4 for all ST intervals (Mann-Whitney p < .001 to p .021). Only 21% of PCT were lost. This percentage was 58% for teeth assigned the shortest ST and increased to 71% and 88% for these teeth in LTO ≥4 patients. CONCLUSIONS: This approach might be useful to predict TLPD in patients with an initial higher risk of TLPD while it was not useful in patients with lower risk of TLPD.

Predictors of long-term outcomes in patients undergoing periodontal maintenance.

AIM: This retrospective study aimed to characterize the baseline status of patients following periodontal maintenance, analysing the association between the long-term outcome of these patients, smoking, bruxism, and the main clinical and radiographic variables. MATERIAL AND METHODS: A sample of 174 patients with moderate to severe periodontitis was refined into homogeneous subsamples according to smoking and bruxism and the rate of tooth loss due to periodontal disease (TLPD): 0, 1-2, and >2 teeth. The association and the distribution (χ² test) of the variables within the subsamples were analysed. RESULTS: Smoking and bruxism were significantly associated with higher TLPD rates. Vertical and circumferential bone defects (p < .0001), and abfractions (p < .0001) were associated with bruxism and particularly with bruxism and TLPD >2. Furcation defects (p = .0002), fewer radio-opaque subgingival calculus (χ² p < .0001), a lower mean Gingival index (χ² p = .027), and increased mean recessions >1.5 mm (χ² p = .0026) were associated with smoking and higher TLPD rates. The mean baseline mobility, abfractions, and recessions characterized two basic types of TLPD. CONCLUSIONS: Smoking, bruxism, and routine clinical and radiological parameters can be used to characterize the baseline status of patients with worse outcomes.

Predictors of tooth loss due to periodontal disease in patients following long-term periodontal maintenance.

AIM: To analyse patient-related factors (PRFs) and tooth-related factors (TRFs) associated with tooth loss due to periodontal disease (TLPD) in patients undergoing periodontal maintenance (PM). MATERIAL AND METHODS: The sample consisted of 500 patients (mean follow-up of 20 years). The impact of PRFs on TLPD was analysed with Poisson regression and multivariate logistic regression. The simultaneous impact of PRFs and TRFs was analysed with multilevel logistic regression and Cox regression. RESULTS: Tooth loss due to periodontal disease was 515 (mean 0.05 patient/year). The significant PRFs were severe periodontitis (p < 0.001), aggressive periodontitis (p < 0.001), smoking (p = 0.018), bruxism (p = 0.022) and baseline number of teeth (p = 0.001). These PRFs allowed characterizing patients losing more teeth. The whole TRFs analysed were significant, depending on the type of tooth and the category of each factor (e.g. mobility 0, 1, 2, and 3). The significant PRFs increased the risk of TLPD by 2 to 3 times while TRFs increased the risk to a higher extent. Mobility was the main TRF. CONCLUSIONS: Severe periodontitis, aggressive periodontitis, smoking, bruxism and baseline number of teeth, as well as the whole TRFs analysed, were associated with TLPD.

Control de placa e higiene bucodental. Resumen de los resultados del 1er workshop ibérico / Plaque control and oral hygiene. Summary results from the 1st iberian workshop

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