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Purpose Biofilm-free implant surface is ultimate prerequisite for successful soft and bone tissue integration. Objective of the study was to estimate the effects of argon plasma healing abutment pre-treatment (PT) on peri-implant soft-tissue phenotype (PiSP), inflammation, plaque accumulation and the microbiome (PiM) between non-treated (NPT) and treated (PT) abutments following 3-months healing period. The hypothesis was that cell-conductive and antimicrobial properties of PT would yield optimal conditions for soft tissue integration. Material and Methods Two months following second-phase surgery, microbiological and clinical parameters were assessed around thirty-six healing abutments with two types of microtopography, smooth surface (MACHINED) and ultrathin threaded microsurface (ROUGH). A two level randomization schema was used to achieve equal distribution and abutments were randomly divided into rough and machined groups, and then divided into PT and NPT groups. PiM was assessed using next-generation DNA sequencing. Results PiM bacterial composition was highly diverse already two months post-implantation, consisting of key-stone pathogens, early and late colonizers, while the mycobiome was less diverse. PT was associated with lower plaque accumulation and inflammation without significant impact on PiSP, while in NPT clinical parameters were increased and associated with periopathogens. NPT mostly harbored late colonizers, while PT exerted higher abundance of early colonizers suggesting less advanced plaque formation. Interaction analysis in PT demonstrated S. mitis co-occurrence with pro-healthy Rothia dentocariosa and co-exclusion with Parvimonas micra, Porphyromonas endodontalis and Prevotella oris. PiSP parameters were generally similar between the groups, but significant association between PiM and keratinized mucosa width was observed in both groups, with remarkably more expressed diversity in NPT compared to PT. PT resulted in significantly lower BOP and PI around rough and machined abutments, respectively, without specific effect on PiM and PiSP. Conclusions PT contributed to significantly the less advanced biofilm accumulation and inflammation without specific effects on PiSP.

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Background: The aim of the present study was to highlight clinical and radiographical differences among implants sharing the same macro-geometry but with two different prosthodontic connections. Methods: Patients requiring at least 2 implants in the posterior area of the jaw were randomly divided into two groups (Conical (CS) and Internal Hexagonal (IH) connection). At implant surgery (T0), insertion torque, implant stability quotient (ISQ values recorded by resonance frequency analysis, RFA), and soft tissue thickness (STH) were assessed. A 1-abutment/1-time protocol was applied, and the prosthesis was realized following a fully digital workflow. At the 36-month follow-up periapical x-rays were taken. In order to statistically analyse differences among the two groups and the different variables, paired T-test was used. Linear regression analysis was conducted to analyze how marginal bone loss (MBL) was affected by other independent variables. A neural network created to predict the success (good or not good) of the implant itself was implemented. Results: 30 out of 33 patients (14 males, 16 females, mean age: 68.94 ± 13.01 years) (32 CS and 32 IH) were analyzed. No implants failed. Marginal bone loss at the 3-year time-point was 0.33 ± 0.34 mm and 0.43 ± 0.37 mm respectively for CS and IH with a significant difference between the two groups (p = 0.004). The presence of keratinized gingiva (p = 0.034) significantly influenced MBL. Conclusions: Both the implant connections investigated presented optimal clinical outcomes with minimal marginal bone loss; however, CS implants and implants with the presence of a greater width of keratinized tissue presented significantly lower MBL.