Multifactorial risk assessment for survival of abutments of removable partial dentures based on practice-based longitudinal study
Available online 1 August 2013
Abstract
Objectives
Predicting
the tooth survival is such a great challenge for evidence-based
dentistry. To prevent further tooth loss of partially edentulous
patients, estimation of individualized risk and benefit for each
residual tooth is important to the clinical decision-making. While there
are several reports indicating a risk of losing the abutment teeth of
RPDs, there are no existing reports exploring the cause of abutment loss
by multifactorial analysis. The aim of this practice-based longitudinal
study was to determine the prognostic factors affecting the survival
period of RPD abutments using a multifactorial risk assessment.
Methods
One
hundred and forty-seven patients had been previously provided with a
total of 236 new RPDs at the Osaka University Dental Hospital; the 856
abutments for these RPDs were analyzed. Survival of abutment teeth was
estimated using the Kaplan–Meier method. Multivariate analysis was
conducted by Cox's proportional hazard modelling.
Results
The
5-year survival rates were 86.6% for direct abutments and 93.1% for
indirect abutments, compared with 95.8% survival in non-abutment teeth.
The multivariate analysis showed that abutment survival was
significantly associated with crown-root ratio (hazard ratio (HR):
3.13), root canal treatment (HR: 2.93), pocket depth (HR: 2.51), type of
abutments (HR: 2.19) and occlusal support (HR: 1.90).
Conclusion
From
this practice-based longitudinal study, we concluded that RPD abutment
teeth are more likely to be lost than other residual teeth. From the
multifactorial risk factor assessment, several prognostic factors, such
as occlusal support, crown-root ratio, root canal treatment, and pocket
depth were suggested.
Clinical significance
These
results could be used to estimate the individualized risk for the
residual teeth, to predict the prognosis of RPD abutments and to
facilitate an evidence-based clinical decision making.
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