Peri-implant diseases are known as undesirable conditions that can occur after implant therapy. Although several risk indicators are becoming clear, the causes of peri-implant diseases have not been completely investigated. The purpose of this review was to summarize the prevalence and risk indicators for peri-implant diseases by referring to current papers from various angles. Many studies have reported the varied prevalence of peri-implant mucositis (23.9%–88.0% at the patient level and 9.7%–81.0% at the implant level) and peri-implantitis (8.9%–45% at the patient level and 4.8%–23.0% at the implant level). Additionally, several studies concluded that poor oral hygiene and lack of regular maintenance were strongly correlated with the development of both peri-implant mucositis and peri-implantitis. Diabetes and a history of periodontitis were revealed as risk indicators for peri-implantitis. However, there was no definitive conclusion about the correlations between peri-implant diseases and other factors such as smoking, the shape of the implant superstructure, and the condition of the keratinized mucosa. Further studies useful for evidence-based decision-making are needed for predictable implant therapy in the long term.

Background: To evaluate the effect of several representative decontamination methods of oral biofilms on different implant surfaces. Material and methods: Eleven participants wore a hard resin splint carrying 6 rough (GC Aadva® implant; 3.3-mm diameter, 8-mm length) or machined (not commercially available) surface implants for 4 days to accumulate dental plaque naturally on the titanium surfaces of the implants. Apart from surface roughness, the morphology of all implants was identical. After detaching the implants from the splints, the ability of the following decontamination methodsgauze soaked in saline (G), ultrasonic scaler (US), air abrasive (Air), rotary stainless steel instrument (Rot), and Er:YAG laser (Las)-to cleanse the contaminated implant surface for 1 min extra-orally was tested. The control (Cont) group did not receive any decontamination. Scanning electron microscopic (SEM) investigation of one participant's samples was employed to examine the post-instrumented implant surface for qualitative analysis, and bacterial culture of the remaining 10 participants' samples was performed to count the number of colony-forming units (CFU) for quantitative analysis. The experimental sequence was initially performed for the rough surface implants and then similarly repeated for the machined surface implants. Bacterial CFU counts among the six groups were analyzed using the Steel-Dwass test, and differences between rough and machined surface implants were determined using the Mann-Whitney U test. Results: G and Rot eliminated most biofilms on machined surface implants according to SEM analysis. G, Air, and Rot removed significantly more of the biofilms on rough and machined surface implants compared with US according to CFU counts. Moreover, G significantly reduced more biofilms than Las on machined surface implants. The analysis between rough and machined surface implants showed that Cont, G, and US were better able to cleanse biofilms on machined surface implants compared with rough surface implants.

Background Marginal bone stability is considered one of the most important issues in implant dentistry. It is essential to understand how various factors influence bone resorption around implants. The purpose of this retrospective longitudinal study was to identify potential risk indicators associated with marginal bone resorption around implants in function for at least 4 years. Methods Several systemic‐related, intraoral‐related, implant‐related factors were collected. Marginal bone level change (MBLC) was determined by comparing intraoral radiographs taken at baseline (1 year after prosthesis delivery), and at follow‐up (over 3 years from baseline). A hierarchical regression analysis using liner mixed‐effects models was performed to examine correlations between MBLC and various factors. Results Overall, 514 patients with 1535 implants were analyzed. The mean age of the participants was 62.9 years. Mean annual MBLC was 0.048 mm, and mean functional time was 5.96 years. The result showed that the following explanatory variables had significant effects on MBLC: functional time, plaque control record > 20%, Eichner index C1‐3, maxilla, cement‐retained superstructure, and keratinized mucosa width < 2 mm. We did not find statistically significant associations between bone resorption and some variables known as risk factors, such as diabetes, smoking, and history of periodontitis. Conclusions Within the limits of this study, longer functional time, poor oral hygiene, loss of occlusal support, location in the maxilla, cement‐retained superstructure, and less keratinized mucosa should be considered as risk indicators for bone resorption around implants.

Bone remodeling occurred within the early healing phase. During the full 20 weeks of observation, PS-implants demonstrated significantly less crestal bone loss compared to PM-implants.