Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values

Hairong Huang, Zanzan Xu, Xianhong Shao, Daniel Wismeijer, Ping Sun, Jingxiao Wang and Gang Wu

PLOS ONE, 2017, vol. 12, issue 10, 1-11

Abstract: Objectives: This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice. Methods: We 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. Results: The 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. Conclusions: These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0187010

DOI: 10.1371/journal.pone.0187010

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