Peri‐implantitis prevalence, incidence rate, and risk factors: A study of electronic health records at a U.S. dental school

Abstract

Objectives:We assessed peri-implantitis prevalence, incidence rate, and associated risk factors by analyzing electronic oral health records (EHRs) in an educational institution. Methods:We used a validated reference cohort comprising all patients receiving dental implants over a 3.5-year period (2,127 patients and 6,129 implants). Electronic oral health records of a random 10% subset were examined for an additional followup of ≥2.5 years to assess the presence of radiographic bone loss, defined as >2 mm longitudinal increase in the distance between the implant shoulder and the supporting peri-implant bone level (PBL) between time of placement and follow-up. "Intact" implants had no or ≤2 mm PBL increase from baseline. Electronic oral health record notes were reviewed to corroborate a definitive peri-implantitis diagnosis at implants with progressive bone loss. A nested case-control analysis of peri-implantitis-affected implants randomly matched by age with "intact" implants from peri-implantitis-free individuals identified putative risk factors. Results:The prevalence of peri-implantitis over an average follow-up of 2 years was 34% on the patient level and 21% on the implant level. Corresponding incidence rates were 0.16 and 0.10 per patient-year and implant-year, respectively. Multiple conditional logistic regression identified ill-fitting fixed prosthesis (OR = 5.9; 95% CI: 1.6-21.1), cement-retained prosthesis (OR = 4.5; 2.1-9.5), and radiographic evidence of periodontitis (OR = 3.6; 1.7-7.6) as statistically associated with peri-implantitis. Implant location in the mandible (OR = 0.02; 0.003-0.2) and use of antibiotics in conjunction with implant surgery (OR = 0.19; 0.05-0.7) emerged as protective exposures.Conclusions: Approximately 1/3 of the patients and 1/5 of all implants experienced peri-implantitis. Ill-fitting/ill-designed fixed and cement-retained restorations, and history of periodontitis emerged as the principal risk factors for peri-implantitis. K E Y W O R D S epidemiology, periodontology, soft tissue-implant interactions | 307 KORDBACHEH CHANGI Et Al.

Implant Disease Risk Assessment IDRA–a tool for preventing peri‐implant disease

“…Furthermore, iatrogenic factors such as poor marginal fit and submucosal excess cement deposits provide habitats for biofilm accumulation and hence are documented factors for the development of biological complications. Recently, this has been confirmed in a large population study by(Kordbacheh Changi et al, 2019). In order to represent a low risk for disease development the prosthesis must be well-fitting, cleanable, screw-retained or with no excess cement.…”

“…There is strong evidence from longitudinal and cross-sectional studies that patients with a history of periodontitis are susceptible to peri-implantitis (Derks et al, 2016;Karoussis et al, 2003;Kordbacheh Changi, Finkelstein, & Papapanou, 2019;Roccuzzo, De, Angelis, Bonino, & Aglietta, 2010). Hence, a patient who has a history of periodontitis or who has lost teeth to be replaced by implants due to periodontitis is at high risk.…”

The effect of different surface topographies of titanium implants on bacterial biofilm: a systematic review

“…Peri-implantitis is a microbial biofilm-induced inflammatory process which results in the loss of supporting bone around an osseointegrated dental implant [38]. Approximately one-third of patients with dental implants and onefifth of all dental implants experienced peri-implantitis [31]. Patients with bleeding on gentle probing (BOP) had a 33.8% probability to be diagnosed with peri-implantitis [25].…”

Using big data to promote precision oral health in the context of a learning healthcare system

“…Yoon et al used big data and deep learning algorithms on a large sample of Latino patients to identify demographic, behavioral, and psychological factors associated with tooth mobility and other indicators of oral health status in older adults . Other studies utilized big data in order to develop risk prediction profiles for development of periodontal disease, implant failure, peri‐implantitis, and alveolar osteitis . Using big EHR data, Boehm A et al uncovered patient determinants of care utilization compliance in a student dental clinic .…”