Prediction of Failure of Dental Implants

The aim of the study is to identify predictors in patient profiles and implant characteristics and to develop and calibrate a prediction model for failure of implants. Patients' demographic characteristics, lifestyle habits, general health, dental health, and implant characteristics were regarded as potential predictors. The failure of implants and the follow-up time in days of implants were considered the outcome. Multivariate Cox proportional hazards regression analysis is used to find out the important risk factors for failure of dental implants and to develop the model for prediction of failure of dental implants at follow-up. The performance and clinical values of the model is determined.