| Title |
Mathematical evaluation of the influence of multiple factors on implant stability quotient values in clinical practice: a retrospective study
|
|---|---|
| Published in |
Therapeutics and Clinical Risk Management, October 2016
|
| DOI | 10.2147/tcrm.s113764 |
| Pubmed ID | |
| Authors |
Hairong Huang, Daniel Wismeijer, Xianhong Shao, Gang Wu |
| Abstract |
The objective of this study is to mathematically evaluate the influence of multiple factors on implant stability quotient values in clinical practice. Resonance frequency analysis was performed at T1 (measured immediately at the time of implant placement) and at T2 (measured before dental restoration) in 177 patients (329 implants). Using a multivariate linear regression model, we analyzed the influence of the following eleven candidate factors: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting (presence or absence), insertion torque, I-/II-stage healing pattern, implant diameter, implant length, and T1-T2 time interval. The following factors were identified to significantly influence the implant stability quotient (ISQ) values at T1: insertion torque, bone grafting, I-/II-stage healing pattern, immediate/delayed implantation, maxillary/mandibular location, implant diameter, and sex. In contrast, the ISQ values at T2 were significantly influenced only by three factors: implant diameter, T1-T2 time interval, and insertion torque. Among the eleven candidate factors, seven key factors were found to influence the T1-ISQ values, while only three key factors influenced the T2-ISQ values. Both T1 and T2-ISQ values were found to be influenced by implant diameter and insertion torque. T1 was influenced specifically by the sex of the patient, the location (maxillary or mandibular), the implantation mode (immediate/delayed implantation), the healing stage, and the absence or presence of bone graft materials. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 17% |
| Researcher | 3 | 9% |
| Student > Doctoral Student | 3 | 9% |
| Student > Bachelor | 3 | 9% |
| Professor | 2 | 6% |
| Other | 9 | 26% |
| Unknown | 9 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 51% |
| Business, Management and Accounting | 2 | 6% |
| Chemistry | 2 | 6% |
| Economics, Econometrics and Finance | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 10 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2016.
All research outputs
#16,721,717
of 25,374,647 outputs
Outputs from Therapeutics and Clinical Risk Management
#810
of 1,323 outputs
Outputs of similar age
#207,199
of 332,576 outputs
Outputs of similar age from Therapeutics and Clinical Risk Management
#18
of 36 outputs
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