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Probing Depth Reduction Following Peri-Implantitis Treatment: A Systematic Review and Component Network Meta-Analysis
Yun-Chen Liu1, Yih-Yun Sun2, Anna Simonelli3
1Institute of Health Data Analytics and Statistics, College of Public Health, National Taiwan University, Taipei, Taiwan.
Objective:
In this update of a previous systematic review, we compared the effects of surgical and non-surgical treatments for peri-implantitis through the component network meta-analysis (CNMA) with probing depth (PD) reduction as the outcome.
Materials And Methods:
Literature search was conducted in PubMed, Cochrane Central Register of Controlled Trials, and Embase databases from August 2010 to June 2023. Randomized controlled trials (RCTs), comparing non-surgical or surgical treatments for peri-implantitis with 6-12 months of follow-up and reported changes in PD, were included. Treatment effects were assessed using a CNMA model based on additivity assumption. We calculated the intraclass correlation coefficient (ICC) to adjust the standard errors for multiple implants within the same patient.
Results:
Our systematic review identified 44 RCTs, which included 46 treatment regimens consisting of 15 components. These RCTs formed a disconnected network consisting of 11 subnetworks. Surgical treatments with bone grafts and membranes generally attained greater PD reduction than non-surgical treatments, although bone grafts and membranes as components provided moderate benefits. The effect size of antibiotics is greater in non-surgical than surgical treatments, while there is considerable uncertainty regarding the effect size of implantoplasty. Additionally, the effectiveness of components varied between surgical and non-surgical treatments.
Conclusion:
Current evidence does not yield sufficiently robust estimates for identifying optimal surgical and non-surgical treatment regimens for peri-implantitis, so the findings of our study should be interpreted cautiously. A coordinated strategy is required for designing future trials to fill the gaps in our current knowledge and develop more reliable recommendations.
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