Abstract
Background: Resonance frequency analysis (RFA) has been proposed as a non-invasive tool for evaluating implant stability. It provides quantitative measurements (implant stability quotients, ISQs) supplementary to conventional clinical and radiographic assessments, but eliminates the subjectiveness that may be involved with other evaluations. Long-term clinical studies validating its association with other clinical parameters are limited, therefore, the aim of this study was to retrospectively assess ISQ values from patients that were followed up for 10 years, and evaluate any correlation between ISQs and clinical parameters such as change of marginal bone level (MBL).
Methods: One hundred and seventy-three participants (65 males and 108 females; age range 21 to 85 years), and 383 implants were followed up for 10 years. Implant locations, MBLs, and ISQs recorded at various recall times were entered for statistical analysis. Mixed model analysis was applied with the level of significance set at P < 0.05.
Results: Twenty out of 21 implants failed within 1 year of functional loading, resulting in a 10-year cumulative implant survival estimate of 95%. The failed implants had lower ISQs at surgery (52.3±7.03) and baseline (52.5±4.20) when compared to surviving implants, and the difference was statistically significant at surgery (P < 0.05). The mean ISQ values generally increased over time, with various patterns of change between implants when grouped according to patient sex and implant locations. There was no correlation between the changes in the ISQ values and the MBLs.
Conclusions: ISQ values may help to identify the implants at higher risk of failure. There may be various patterns of change over time in addition to an overall increase in ISQ values. Both similar and contradictory findings were found when compared with earlier literature, and a correlation between RFA and MBL change could not be identified. Despite limitations, the present study provides an overview of the clinical performance of RFA based on long-term clinical data.