BACKGROUND: Long-term studies worldwide indicate that peri-implant inflammation is a frequent finding and that the prevalence of peri-implantitis correlates with loading time. Implant loss, although less frequent, has serious oral health and economic consequences. An understanding of predictive factors for peri-implant disease and implant loss would help providers and patients make informed decisions. METHODS: A cross-sectional study was performed on 96 patients with 225 implants that were placed between 1998 and 2003. Implant placement data were collected from patient records, and patients presented for a clinical and radiographic follow-up examination. Implant status and periodontal status were determined, the data were analyzed to determine the prevalence of peri-implant disease or implant loss, and a predictive model was tested. RESULTS: The mean follow-up time for the patients was 10.9 years. The implant survival rate was 91.6%. Peri-implant mucositis was found in 33% of the implants and 48% of the patients, and peri-implantitis occurred in 16% of the implants and 26% of the patients. Individuals with peri-implantitis were twice as likely to report a problem with an implant as individuals with healthy implants. Peri-implantitis is associated with younger ages and diabetes at the time of placement and with periodontal status at the time of follow-up. Implant loss is associated with diabetes, immediate placement, and larger-diameter implants. CONCLUSIONS: One in four patients and one in six implants have peri-implantitis after 11 years. The data suggest that periodontal and diabetes status of the patient may be useful for predicting implant outcomes.
BACKGROUND: Long-term studies worldwide indicate that peri-implant inflammation is a frequent finding and that the prevalence of peri-implantitis correlates with loading time. Implant loss, although less frequent, has serious oral health and economic consequences. An understanding of predictive factors for peri-implant disease and implant loss would help providers and patients make informed decisions. METHODS: A cross-sectional study was performed on 96 patients with 225 implants that were placed between 1998 and 2003. Implant placement data were collected from patient records, and patients presented for a clinical and radiographic follow-up examination. Implant status and periodontal status were determined, the data were analyzed to determine the prevalence of peri-implant disease or implant loss, and a predictive model was tested. RESULTS: The mean follow-up time for the patients was 10.9 years. The implant survival rate was 91.6%. Peri-implant mucositis was found in 33% of the implants and 48% of the patients, and peri-implantitis occurred in 16% of the implants and 26% of the patients. Individuals with peri-implantitis were twice as likely to report a problem with an implant as individuals with healthy implants. Peri-implantitis is associated with younger ages and diabetes at the time of placement and with periodontal status at the time of follow-up. Implant loss is associated with diabetes, immediate placement, and larger-diameter implants. CONCLUSIONS: One in four patients and one in six implants have peri-implantitis after 11 years. The data suggest that periodontal and diabetes status of the patient may be useful for predicting implant outcomes.
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: Mia Rakic; Pablo Galindo-Moreno; Alberto Monje; Sandro Radovanovic; Hom-Lay Wang; David Cochran; Anton Sculean; Luigi Canullo Journal: Clin Oral Investig Date: 2017-12-07 Impact factor: 3.573
Authors: Rafał Pokrowiecki; Urszula Szałaj; Damian Fudala; Tomasz Zaręba; Jacek Wojnarowicz; Witold Łojkowski; Stefan Tyski; Krzysztof Dowgierd; Agnieszka Mielczarek Journal: Int J Nanomedicine Date: 2022-04-12
Authors: Alex E Pozhitkov; Diane Daubert; Ashley Brochwicz Donimirski; Douglas Goodgion; Mikhail Y Vagin; Brian G Leroux; Colby M Hunter; Thomas F Flemmig; Peter A Noble; James D Bryers Journal: PLoS One Date: 2015-10-13 Impact factor: 3.240