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Evaluation of marginal/internal fit of fixed dental prostheses after digital, conventional, and combination impression techniques: A systematic review.

Katia SarafidouMaria ChatziparaskevaDimitrios ChatzikamagiannisVasileios MpotskarisDimitrios TortopidisAthina BakopoulouMaria Kokoti
Published in: European journal of oral sciences (2022)
Advances of digital technology are rapidly adopted in dental practice. This systematic review aimed to collect evidence on the accuracy of fit of different types of fixed dental prostheses (FDPs) fabricated through digital, conventional, or combination impression techniques. Data collection was based on the guidelines of the preferred reporting items for systematic reviews and meta-analyses (PRISMA). Two databases (PubMed, Scopus) were searched for articles in English published between 2010 and 2021 resulting in 480 articles. Of those, 35 studies fulfilled the inclusion criteria. These articles referred to three groups of materials/techniques including all-ceramic (zirconia; lithium disilicate) and porcelain-fused-to-metal (PFM) restorations. Results showed clinically acceptable marginal fit (< 120 μm) for all materials and impression techniques. Α fully digital workflow appears more promising for the construction of short-span zirconia FDPs. Nevertheless, most articles evaluated marginal/internal fit of single crowns or short-span FDPs in vitro, while clinical data are limited for long-span FDPs. The necessity for gingival retraction remains a major drawback of all impression techniques, increasing procedural time and patient discomfort. Besides, factors related to the fabrication process, including milling and 3D printing of working models significantly influence the outcome. Overall, there still some way to go before digital technology can be incorporated in complex treatment plans in prosthodontics.
Keyphrases
  • meta analyses
  • systematic review
  • randomized controlled trial
  • electronic health record
  • oral health
  • primary care
  • emergency department
  • health insurance
  • quality improvement
  • data analysis