Successive Reimplantation of Dental Implants Into Sites of Previous Failure.

ABSTRACT

PURPOSE: To evaluate the survival rates of dental implants that had been reimplanted in sites of previous failure, including first, second, and third reimplantations, and investigate the various factors that could affect the reimplantation outcomes. MATERIALS AND METHODS: All dental implants placed in sites of previous implant failure were identified, including first, second, and third reimplantations. The survival rates were assessed, and epidemiologic and clinical data were collected and analyzed to evaluate the effects on reimplantation survival. RESULTS: The survival rate for the total number of initial implants placed was 95.4% (5280 of 5532). For the 208 patients with failed implants, the survival rate was 62.0% (412 of 664). The survival rate of the implants placed in the sites of previous failure (first reimplantation) was 77.4% (137 of 177 implants). A statistically significant difference was found (P = .0001) between the survival rates of implants placed for the first time and implants placed into sites of previous failure. The survival rate of the second reimplantations was 72.7% (16 of 22). The survival rate of the third reimplantations was 50.0% (1 of 2). Each implant and reimplant group demonstrated a statistically significant greater percentage of postoperative pain reports in the failure group than in the survival group. A significantly greater percentage of early failures (failures occurring before abutment connection) occurred compared with late failures for each implant and reimplant group. CONCLUSIONS: Dental implants placed in sites of previous implant failure had lower survival rates than those of the initial implants, and our findings suggested that the survival rates will be consecutively lower with each successive reimplantation at the same site. Implant and reimplant failures were associated with higher rates of postoperative pain reports and were more often early failures. Such suggestions could improve clinicians' prediction for implant failure and allow for optimization of the conditions to improve implant survival.