Abstract
BACKGROUND: Implants are being widely used as a treatment option and are considered the best line of treatment owing to their high level of predictability. However, over 5 years, 0-14.4% of dental implants have demonstrated peri-inflammatory reactions associated with loss of crestal bone and ultimately loss of the implant. Peri-implant diseases are categorized into peri-implant mucositis and peri-implantitis. There are a number of risk factors associated with these conditions, and the early detection of these possible risk factors, change in the treatment protocol whenever required along with a regular follow-up, can ensure a better survival rate of dental implants. In the present study, an attempt has been made to evaluate the risk factors associated with peri-implant diseases and also to correlate these risk factors to the prevalence of peri-implant diseases using the formulated risk assessment model. Methodology. The risk assessment model was prepared based on existing literature explaining the risk factors for peri-implant diseases. This study was conducted as a pilot study, and the method of complete sampling was used wherein all subjects in whom implants have been placed at the Department of Periodontology and Department of Prosthodontics were recalled and assessed. The model was then evaluated on patients in whom dental implants were placed and the implants were loaded for a year. A total of 13 subjects with 21 implants were assessed for the presence or absence of risk factors, and a score was given. Test of proportion and chi-square test was done. Results and Discussion. Of the 21 implants assessed, 15 implants were found to be at low risk and 6 implants with moderate risk of peri-implant disease. The number of implants with low risk was higher in implants with peri-implant mucositis (25%) whereas the implants with moderate risk was higher in implants with peri-implantitis (75%). This comparison was statistically significant with a p value of 0.022. CONCLUSION: This risk assessment tool can be used in the early detection of peri-implant disease, and identifying the risk factor may help in the success rate of the implant survival.