Artigo
Capsular contracture in breast reconstruction: A systematic review and meta-analysis
SUMMARY
Background: Capsular contracture after implant-based breast reconstruction is not an uncommon problem and affects reconstruction outcomes. It can be influenced by various factors, such as the plane of implant placement, implant surface and implant type. This systematic review and meta-analysis aimed to evaluate how the abovementioned risk factors can
affect capsular contracture rates.
Methods: A systematic review and meta-analysis was performed. PubMed MEDLINE, EMBASE (OvidSP) and Cochrane Library were searched. Comparison groups included subpectoral versus prepectoral implant placement, smooth versus textured implants and saline versus silicone implants. Odds ratios (ORs) were calculated for capsular contracture for each group. The level of evidence was evaluated using the Oxford Centre for Evidence-Based Medicine.
Results: Twenty-three studies met the inclusion criteria. Sixteen studies compared subpectoral versus prepectoral implant placement, with no statistically significant differences in capsular contracture rates [OR, 1.21; 95% confidence interval (95% CI), 0.75–1.95; P = 0.44]. Five studies compared smooth versus textured implants, with no statistically capsular contracture rates (OR, 0.99; 95% CI, 0.50–1.93; P = 0.97). Two studies compared saline versus silicone implants for capsular contracture. Patients receiving saline implants had significantly lower capsular contracture rates than silicone implants (OR, 0.19; 95% CI, 0.08–0.43; P < 0.0001).
Conclusions: Implant-based breast reconstruction using saline implants demonstrated reduced capsular contracture rates compared to silicone implants. However, no significant differences were observed in capsular contracture rates between subpectoral versus prepectoral implant placement and smooth versus textured implants.
© 2024 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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