Abstract
ObjectivesThis study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice.MethodsWe collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem) placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement) and T2 (before dental restoration). A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval.ResultsThe need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5). In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2). Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2.ConclusionsThese findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice.
Highlights
Dental implantation has become one of the most widely used treatment options for partially or completely edentulous patients in the past several decades
The need for bone grafting as a predictor significantly influenced implant stability quotient (ISQ) values in all three groups at T1
These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice
Summary
Dental implantation has become one of the most widely used treatment options for partially or completely edentulous patients in the past several decades. Primary stability plays a dominant role in implant stability in the first week after implantation and decreases significantly thereafter to a minimal level at approximately 5 weeks [1]. Secondary stability is based on the biological process osseointegration, during which a direct structural contact between the implant surfaces and the new surrounding bone tissues is formed [2]. Implant stability is used as a major indicator in clinical practice to determine the time frame for loading and prognosis of the implants (failure) [3]. Many methods, such as resonance frequency analysis (RFA), have been developed to estimate implant stability
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