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Comparing Complications of Biologic and Synthetic Mesh in Breast Reconstruction: A Systematic Review and Network Meta-Analysis.

Young-Soo ChoiHi-Jin YouTae-Yul LeeDeok-Woo Kim
Published in: Archives of plastic surgery (2023)
Background  In breast reconstruction, synthetic meshes are frequently used to replace acellular dermal matrix (ADM), since ADM is expensive and often leads to complications. However, there is limited evidence that compares the types of substitutes. This study aimed to compare complications between materials via a network meta-analysis. Methods  We systematically reviewed studies reporting any type of complication from 2010 to 2021. The primary outcomes were the proportion of infection, seroma, major complications, or contracture. We classified the intervention into four categories: ADM, absorbable mesh, nonabsorbable mesh, and nothing used. We then performed a network meta-analysis between these categories and estimated the odds ratio with random-effect models. Results  Of 603 searched studies through the PubMed, MEDLINE, and Embase databases, following their review by two independent reviewers, 61 studies were included for full-text reading, of which 17 studies were finally included. There was a low risk of bias in the included studies, but only an indirect comparison between absorbable and non-absorbable mesh was possible. Infection was more frequent in ADM but not in the two synthetic mesh groups, namely the absorbable or nonabsorbable types, compared with the nonmesh group. The proportion of seroma in the synthetic mesh group was lower (odds ratio was 0.2 for the absorbable and 0.1 for the nonabsorbable mesh group) than in the ADM group. Proportions of major complications and contractures did not significantly differ between groups. Conclusion  Compared with ADM, synthetic meshes have low infection and seroma rates. However, more studies concerning aesthetic outcomes and direct comparisons are needed.
Keyphrases
  • breast reconstruction
  • case control
  • risk factors
  • randomized controlled trial
  • rheumatoid arthritis
  • machine learning
  • emergency department
  • working memory
  • wound healing