Literature DB >> 29067778

Dentists' Most Common Practices when Selecting an Implant System.

Ahed Al-Wahadni1, Mohamed S Barakat2, Khladoon Abu Afifeh3, Yusuf Khader4.   

Abstract

PURPOSE: To report a comprehensive description of dental implant system selection practices among dentists practicing implantology worldwide.
MATERIALS AND METHODS: An online questionnaire was designed and sent to members of 15 dental implant organizations. The survey questions addressed: dental implant system selection criteria, implant design variables, dentists' perspective to implant quality stamps, and dentists' satisfaction with their implant system(s). Responses were compiled and analyzed to determine correlation of responses using the chi-squared test (level of significance α ≤ 0.05).
RESULTS: Out of 4264 invitations sent, a total of 2001 (response rate = 46.9%) dentists participated in the survey. Approximately half of survey respondents (48.7%) were general dentists. More than two-thirds of the survey respondents (72.5%) were performing both the surgical and prosthetic implant phases. Implant-abutment connections were the most important dental implant system selection criterion (84.7%), followed by scientific evidence available on the implant system (82.8%), and simplicity of prosthetic steps (81.4%). Patient preferences (19.8%) were rated as the least important aspect. Sandblasted large gritted acid etched implant surfaces (SLA) were the most commonly used implant surfaces (75.8%); fluoride coated surfaces were the least commonly used (15.4%).
CONCLUSION: According to the results of this survey, most survey respondents practiced both surgical and prosthetic phases of dental implantology. The majority of survey respondents agreed on the importance of implant-abutment connections, scientific evidence available on implant systems, and simplicity of prosthetic steps when selecting implant systems.
© 2017 by the American College of Prosthodontists.

Entities:  

Keywords:  Dental implants; implant system selection practices; survey questionnaire

Mesh:

Substances:

Year:  2017        PMID: 29067778     DOI: 10.1111/jopr.12691

Source DB:  PubMed          Journal:  J Prosthodont        ISSN: 1059-941X            Impact factor:   2.752


  4 in total

1.  A Performance Comparison between Automated Deep Learning and Dental Professionals in Classification of Dental Implant Systems from Dental Imaging: A Multi-Center Study.

Authors:  Jae-Hong Lee; Young-Taek Kim; Jong-Bin Lee; Seong-Nyum Jeong
Journal:  Diagnostics (Basel)       Date:  2020-11-07

2.  Deep learning improves implant classification by dental professionals: a multi-center evaluation of accuracy and efficiency.

Authors:  Jae-Hong Lee; Young-Taek Kim; Jong-Bin Lee; Seong-Nyum Jeong
Journal:  J Periodontal Implant Sci       Date:  2022-06       Impact factor: 2.086

3.  Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

Authors:  Jong-Eun Kim; Na-Eun Nam; June-Sung Shim; Yun-Hoa Jung; Bong-Hae Cho; Jae Joon Hwang
Journal:  J Clin Med       Date:  2020-04-14       Impact factor: 4.241

4.  Maxillary sinus floor augmentation and simultaneous dental implant placement in a patient with Guillain-Barre syndrome: A case report.

Authors:  Fardin Faraji; Mojtaba Bayani; Maryam Jafarpour; Fateme Abdolalian
Journal:  Clin Case Rep       Date:  2019-10-17
  4 in total

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