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The accuracy of static computer-aided implant surgery: A systematic review and meta-analysis

  • A. Tahmaseb
  • , V. Wu
  • , D. Wismeijer
  • , W. Coucke
  • , C. Evans

Research output: Contribution to JournalReview articleAcademicpeer-review

Abstract

Objectives: To assess the literature on the accuracy of static computer-assisted implant surgery in implant dentistry.
Materials and Methods: Electronic and manual literature searches were conducted to collect information about the accuracy of static computer-assisted implant systems. Meta-regression analysis was performed to summarise the accuracy studies.
Results: From a total of 372 articles. 20 studies, one randomised controlled trial (RCT), eight uncontrolled retrospective studies and 11 uncontrolled prospective studies were selected for inclusion for qualitative synthesis. A total of 2,238 implants in 471 patients that had been placed using static guides were available for review. The meta-analysis of the accuracy (20 clinical) revealed a total mean error of 1.2 mm (1.04 mm to 1.44 mm) at the entry point, 1.4 mm (1.28 mm to 1.58 mm) at the apical point and deviation of 3.5°(3.0° to 3.96°). There was a significant difference in accuracy in favour of partial edentulous comparing to full edentulous cases.
Conclusion: Different levels of quantity and quality of evidence were available for static computer-aided implant surgery (s-CAIS). Based on the present systematic review and its limitations, it can be concluded that the accuracy of static computer-aided implant surgery is within the clinically acceptable range in the majority of clinical situations. However, a safety marge of at least 2 mm should be respected. A lack of homogeneity was found in techniques adopted between the different authors and the general study designs.
Original languageEnglish
Pages (from-to)416-435
JournalClinical Oral Implants Research
Volume29
Issue numberS16
DOIs
Publication statusPublished - 2018

Bibliographical note

In special issue: Proceedings of the Sixth ITI Consensus Conference.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 10 - Reduced Inequalities
    SDG 10 Reduced Inequalities

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