It can be concluded that plaque induced and prosthetically and surgically triggered peri-implantitis are different entities associated with distinguishing predictive profiles; hence, the appropriate causal treatment approach remains necessary. The advanced data mining model developed in this study seems to be a promising tool for diagnostics of peri-implantitis subtypes.
This study showed that microbiological profile at all three experimental sites is differently characterized between patients suffering peri-implantitis and healthy controls. Data mining analysis identified Parvimonas micra as a highly accurate predictor of peri-implantitis when present in peri-implant pocket while this method generally seems to be promising for diagnosis of such complex infections.
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