Objectives
To perform an exploratory analysis of factors influencing annual rates of peri‐implant marginal bone loss (RBL) calculated over different time frames, at implants unaffected by peri‐implantitis.
Material and methods
A total of 154 implants from 86 patients were reviewed at 1.6–6.8 years after placement. Marginal bone levels (MBL) were assessed on intraoral radiographs at three time‐points: immediately post‐placement, time of loading, and least 1‐year post‐loading. RBLs (mm/year) were computed using these three time frames and corresponding MBL changes as: RBL placement‐loading, RBL loading‐review, RBL placement‐review. Exploratory ordination of three RBLs, corresponding time durations, and 17 background factors were used for visualization. Hierarchical linear mixed‐effects models (MEM) with predictor selection were applied to RBL outcomes. The correlation of actual MBL with MBLs predicted by RBL placement‐loading and RBL loading‐review was tested.
Results
Median RBL placement‐loading was 0.9 mm/year (IQR = 2.02), loading‐review was 0.06 mm/year (IQR = 0.16), and overall RBL placement‐review was 0.21 mm/year (IQR = 0.33). Among‐patient variance was highest for RBL placement‐loading (SD = 0.66). Longer time predicted lower RBL in all time frames. Shorter time of loading significantly predicted lower RBL placement‐review. Augmentation predicted lower RBL placement‐loading, while anterior location and older age predicted lower RBLs placement‐loading placement‐review. Only MBL projected using RBL placement‐loading significantly correlated with actual MBL.
Conclusions
Exploratory analysis indicated RBL varied with the time duration used for calculation in pre‐ and post‐loading, and overall periods. In each period, RBL declined with increasing time. Earlier loading predicted lower overall RBL. Higher pre‐loading RBL predicted worse actual bone level.
Proximity of implants to adjacent teeth of <1 mm leads to increased prevalence of inflammation and interproximal bone resorption at the teeth adjacent to bone level implants.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.