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Accuracy of Digital Implant Impression

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Know the risks and potential benefits of clinical studies and talk to your health care provider before participating. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04627649
Recruitment Status : Not yet recruiting
First Posted : November 13, 2020
Last Update Posted : November 13, 2020
Sponsor:
Information provided by (Responsible Party):
Zhuofan Chen, Sun Yat-sen University

Study Description
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Brief Summary:
This study aims to investigate the accuracy of complete-arch digital implant impression using newly designed scan bodies with extensional structure.

Condition or disease
Edentulous Jaw

Detailed Description:
Fully edentulous patients with 2-6 dental implants are included in this study. For each patient, the follow three impressions are made: conventional splinted open-tray impression, digital impression using scan bodies without extensional structure, and digital impression using scan bodies with extensional structure. The accuracy of the three impressions is compared in an inspection software.
Study Design
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Study Type : Observational
Estimated Enrollment : 15 participants
Observational Model: Other
Time Perspective: Prospective
Official Title: Accuracy of Complete-arch Digital Implant Impression With Newly Designed Scan Bodies
Estimated Study Start Date : December 2020
Estimated Primary Completion Date : February 2021
Estimated Study Completion Date : February 2021
Groups and Cohorts
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Outcome Measures
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Primary Outcome Measures :
  1. accuracy [ Time Frame: 0 day ]
    the accuracy is evaluated by comparing the test scans with the reference scan


Eligibility Criteria
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Ages Eligible for Study:   18 Years to 80 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
15 patients are anticipated.
Criteria

Inclusion Criteria:

  • At least 18 years old and able to understand an informed consent
  • Fully edentulous jaw
  • 2-6 dental implants have been placed in the edentulous jaw
  • The implants have been osseointegrated
  • Mouth opening larger than 4.5 cm

Exclusion Criteria:

  • Poor oral hygiene
  • Presence of peri-implantitis or peri-implant mucositis
  • Presence of temporamandibular joint disease
  • Unwilling to paticipate in the research
Contacts and Locations
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Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04627649


Contacts
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Contact: Ruoxuan Huang, MDS 86-18819472978 huangrx3@mail2.sysu.edu.cn
Contact: Zhipeng Li, DDS 86-15920395261 implants@163.com

Locations
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China, Guangdong
Guanghua school of stomatology, hospital of stomtology, Sun Yat-sen University
Guangzhou, Guangdong, China, 510000
Sponsors and Collaborators
Sun Yat-sen University
Investigators
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Study Director: Zhuofan Chen, DDS Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-sen University
  Study Documents (Full-Text)

Documents provided by Zhuofan Chen, Sun Yat-sen University:
Study Protocol  [PDF] October 10, 2020

More Information
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Publications:

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Responsible Party: Zhuofan Chen, Professor, Sun Yat-sen University
ClinicalTrials.gov Identifier: NCT04627649    
Other Study ID Numbers: RuoxuanHuang
First Posted: November 13, 2020    Key Record Dates
Last Update Posted: November 13, 2020
Last Verified: November 2020

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by Zhuofan Chen, Sun Yat-sen University:
dental implant
digital impression
scan body
accuracy
Additional relevant MeSH terms:
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Jaw, Edentulous
Mouth, Edentulous
Mouth Diseases
Stomatognathic Diseases
 Tooth Diseases
Jaw Diseases
Musculoskeletal Diseases