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Published on: June 24, 2018
Evidence-based research in alternative protocols to dental implantology: a closer look at publication bias
David R Moradi1, Peter K Moy, Francesco Chiappelli
1Division of Oral Biology and Medicine, University of California, Los Angeles, School of Dentistry, 90095-1668, USA.
Abstract:
Several techniques exist for the surgical placement of dental implants. The aim of this study was to assess systematically, the efficacy of these protocols by the evidence-based perspective. Five best-case studies involving 607 early/immediately loaded implants and 300 conventionally loaded implants were identified by examining the available literature and rigorous inclusion/exclusion criteria. Overall analyses demonstrated a 98.4 percent success rate for the early/immediate procedure and a 95.3 percent for the conventional protocol. Success rates in the articles reviewed were based on implant survival over a follow-up period of between one to two years. A meta-analysis was generated to evaluate the presented evidence and to aid in decision-making. Despite its common implementation, this technique presents many caveats, among which publication bias is one of the most common. To investigate the possible presence of publication bias, a funnel plot analysis complemented several statistical tests. By means of the systematic investigation of dental implants, the authors' results confirm the presence of publication bias in implant dentistry literature, which strongly suggests that clinicians ought not base their decisions solely on the results presented by a few published studies. Rather, it is recommended that clinicians cautiously draw conclusions and seek studies that present accountable and clinically relevant results. Furthermore, it is suggested that clinicians attend seminars to learn of the effective advances in evidence-based dentistry, so as to develop the ability to easily detect inadequate literature due to attempted correlation with the most current research. It is also recommended that additional research is necessary to analyze which fields of research are more prone to bias, thus forewarning clinicians before formulating clinical conclusions.
