Kinji Noda1, Hikaru Arakawa1, Aya Kimura-Ono1, Seiya Yamazaki1, Emilio Satoshi Hara1, Wataru Sonoyama1, Kenji Maekawa1, Kazuo Okura2, Ayumi Shintani3, Yoshizo Matsuka2, Takuo Kuboki4. 1. Oral Rehabilitation and Regenerative Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Japan. 2. Department of Stomatognathic Function and Occlusal Reconstruction, Institute of Health Biosciences, Tokushima University Graduate School, Japan. 3. Department of Clinical Epidemiology and Biostatistics, Osaka University, Japan. 4. Oral Rehabilitation and Regenerative Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Japan. Electronic address: kuboki@md.okayama-u.ac.jp.
Abstract
PURPOSE: Many studies have identified risk factors for dental implant failure, although few have investigated the correlation among implant fixtures within single patients. A better analytical method may include repeated measures analysis including generalized estimating equations (GEE). This retrospective cohort study aimed to (1) identify the risk factors for failure of dental implantation and (2) evaluate an analytical method using GEE analysis. METHODS: We analyzed data on early and late implant failures in 296 patients providing 721 rough surface dental implants (2.44 implants per patient). Potential predictors of implant failure included age, gender, smoking, location of implant, use of bone augmentation, number of remaining teeth, opposing tooth condition, fixture length, fixture diameter and type of suprastructure (fixed or removable partial denture). The likelihood of early and late implant failure was estimated by GEE. RESULTS: The early failure rate was 1.5% (11/721 implants, 7/296 patients) and the 10-year cumulative survival rate was 94.0% (7/710 implants, 5/293 patients). The GEE analysis revealed that a significant risk factor for early implant failure was smoking (p<0.01), whereas significant risk factors for late failure were maxillary implant (p=0.02), posterior implant (p<0.01), number of remaining teeth (≥20) (p<0.01), opposing unit being a removable partial denture or nothing (p=0.04) and having a removable type suprastructure (p<0.01). CONCLUSIONS: GEE analysis showed that smoking was a risk factor for early implant failure, and several risk factors were identified for late implant failure.
PURPOSE: Many studies have identified risk factors for dental implant failure, although few have investigated the correlation among implant fixtures within single patients. A better analytical method may include repeated measures analysis including generalized estimating equations (GEE). This retrospective cohort study aimed to (1) identify the risk factors for failure of dental implantation and (2) evaluate an analytical method using GEE analysis. METHODS: We analyzed data on early and late implant failures in 296 patients providing 721 rough surface dental implants (2.44 implants per patient). Potential predictors of implant failure included age, gender, smoking, location of implant, use of bone augmentation, number of remaining teeth, opposing tooth condition, fixture length, fixture diameter and type of suprastructure (fixed or removable partial denture). The likelihood of early and late implant failure was estimated by GEE. RESULTS: The early failure rate was 1.5% (11/721 implants, 7/296 patients) and the 10-year cumulative survival rate was 94.0% (7/710 implants, 5/293 patients). The GEE analysis revealed that a significant risk factor for early implant failure was smoking (p<0.01), whereas significant risk factors for late failure were maxillary implant (p=0.02), posterior implant (p<0.01), number of remaining teeth (≥20) (p<0.01), opposing unit being a removable partial denture or nothing (p=0.04) and having a removable type suprastructure (p<0.01). CONCLUSIONS: GEE analysis showed that smoking was a risk factor for early implant failure, and several risk factors were identified for late implant failure.
Authors: Mariane B Sordi; Vittoria Perrotti; Flavia Iaculli; Keila C R Pereira; Ricardo S Magini; Stefan Renvert; Stefano Antonio Gattone; Adriano Piattelli; Marco A Bianchini Journal: Clin Oral Investig Date: 2020-11-05 Impact factor: 3.573