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Diagnostic accuracy of imaging examinations for peri-implant bone defects around titanium and zirconium dioxide implants: A systematic review and meta-analysis

  • Received : 2021.05.13
  • Accepted : 2021.09.24
  • Published : 2021.12.31

Abstract

Purpose: This systematic review and meta-analysis assessed the diagnostic accuracy of imaging examinations for the detection of peri-implant bone defects and compared the diagnostic accuracy between titanium (Ti) and zirconium dioxide (ZrO2) implants. Materials and Methods: Six online databases were searched, and studies were selected based on eligibility criteria. The studies included in the systematic review underwent bias and applicability assessment using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool and a random-effect meta-analysis. Summary receiver operating characteristic (sROC) curves were constructed to compare the effect of methodological differences in relation to the variables of each group. Results: The search strategy yielded 719 articles. Titles and abstracts were read and 61 studies were selected for full-text reading. Among them, 24 studies were included in this systematic review. Most included studies had a low risk of bias (QUADAS-2). Cone-beam computed tomography (CBCT) presented sufficient data for quantitative analysis in ZrO2 and Ti implants. The meta-analysis revealed high levels of inconsistency in the latter group. Regarding sROC curves, the area under the curve (AUC) was larger for the overall Ti group (AUC=0.79) than for the overall ZrO2 group (AUC=0.69), but without a statistically significant difference between them. In Ti implants, the AUCs for dehiscence defects(0.73) and fenestration defects(0.87) showed a statistically significant difference. Conclusion: The diagnostic accuracy of CBCT imaging in the assessment of peri-implant bone defects was similar between Ti and ZrO2 implants, and fenestration was more accurately diagnosed than dehiscence in Ti implants.

Keywords

Acknowledgement

We would like to thank Jessica Conti Reus, MSc, for the initial evaluation of our statistical analysis for data accuracy.

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