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Prevalence and Predictive Factors for Peri‐Implant Disease and Implant Failure: A Cross‐Sectional Analysis
Authors:Diane M Daubert  Bradley F Weinstein  Sandra Bordin  Brian G Leroux  Thomas F Flemmig
Institution:1. Department of Periodontics, University of Washington, Seattle, Washington.;2. Department of Oral Health Sciences, University of Washington.;3. School of Dentistry, University of Hong Kong, Hong Kong.
Abstract: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.
Keywords:Dental implants  diabetes mellitus  follow‐up studies  peri‐implantitis  periodontitis  risk factors
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