BACKGROUND: High prevalence rates of peri-implant diseases have been reported; however, the lack of standardization of definition criteria has lead to variations in the observed estimates. In addition, scarce data are available concerning patient and implant related factors associated to peri-implantitis. The aim of this study was to determine the prevalence of peri-implant diseases and their risk indicators at the patient and implant levels. METHODS: One hundred forty-seven patients with 490 dental implants were included. Dental implants were clinically and radiographically evaluated to determine their peri-implant conditions. Patient-related conditions and implant and prosthetic-related factors were recorded. Multivariable Poisson regression was fitted and prevalence ratios (PR) were reported. RESULTS: 85.3% of implants (95%CI 80.2 to 90.4) had mucositis and 9.2% (95%CI 4.7 to 13.7) had peri-implantitis. 80.9% (95%CI 73.8 to 86.8), and 19.1% (95%CI 12.6 to 25.5) of patients had mucositis and peri-implantitis. At the patient level, it was observed an increased probability of peri-implantitis in individuals with pocket depths ≥6 mm (PR = 2.47) and with ≥4 implants (PR = 1.96). Smoking increased the probability of peri-implantitis by three times (PR = 3.49). The final multilevel Poisson regression model at the implant level indicated that platform switching reduced the probability of peri-implantitis (PR = 0.18) and implants in function for ≥5 years increased this probability (PR = 2.11). The final model including patient and implant level indicators demonstrated that higher time of function (PR = 2.76) and smoking (PR = 6.59) were associated with peri-implantitis. CONCLUSION: Peri-implant diseases are highly prevalent in the studied sample, and factors associated with the occurrence of peri-implantitis were presence of pockets ≥6 mm, smoking, time of function, and type of platform.
BACKGROUND: High prevalence rates of peri-implant diseases have been reported; however, the lack of standardization of definition criteria has lead to variations in the observed estimates. In addition, scarce data are available concerning patient and implant related factors associated to peri-implantitis. The aim of this study was to determine the prevalence of peri-implant diseases and their risk indicators at the patient and implant levels. METHODS: One hundred forty-seven patients with 490 dental implants were included. Dental implants were clinically and radiographically evaluated to determine their peri-implant conditions. Patient-related conditions and implant and prosthetic-related factors were recorded. Multivariable Poisson regression was fitted and prevalence ratios (PR) were reported. RESULTS: 85.3% of implants (95%CI 80.2 to 90.4) had mucositis and 9.2% (95%CI 4.7 to 13.7) had peri-implantitis. 80.9% (95%CI 73.8 to 86.8), and 19.1% (95%CI 12.6 to 25.5) of patients had mucositis and peri-implantitis. At the patient level, it was observed an increased probability of peri-implantitis in individuals with pocket depths ≥6 mm (PR = 2.47) and with ≥4 implants (PR = 1.96). Smoking increased the probability of peri-implantitis by three times (PR = 3.49). The final multilevel Poisson regression model at the implant level indicated that platform switching reduced the probability of peri-implantitis (PR = 0.18) and implants in function for ≥5 years increased this probability (PR = 2.11). The final model including patient and implant level indicators demonstrated that higher time of function (PR = 2.76) and smoking (PR = 6.59) were associated with peri-implantitis. CONCLUSION: Peri-implant diseases are highly prevalent in the studied sample, and factors associated with the occurrence of peri-implantitis were presence of pockets ≥6 mm, smoking, time of function, and type of platform.
Authors: Pedro Diaz; Esther Gonzalo; Luis J Gil Villagra; Barbara Miegimolle; Maria J Suarez Journal: BMC Oral Health Date: 2022-10-19 Impact factor: 3.747
Authors: Maximilian Koch; Maximilian Göltz; Meng Xiangjun; Matthias Karl; Stefan Rosiwal; Andreas Burkovski Journal: J Clin Med Date: 2020-02-09 Impact factor: 4.241