IADR Abstract Archives
Imaging Predictors of Maxillary Canine Impaction. A Systematic Review
Objectives: To assess the validity of imaging predictors to determine maxillary canine impaction (MCI).
Methods: Literature search were carried out electronically in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Bireme and Scielo between 1960 and 2018, including all languages. Observational analytical studies were identified. The data were collected and extracted by two independent authors. The methodology of selected studies was assessed using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). The quality of evidence and strength of recommendation was assessed by The Grading of Recommendations Assessment Tool, Development and Evaluation (GRADE).
Results: 4998 potentially eligible articles were identified in the first approach and finally 10 studies were included according to inclusion criteria. The quality of evidence was low due to high risk of bias. None of the studies fulfilled all of the QUADAS-2 methodological quality criteria to evaluate validity of predictor. According to the evidence available, Principal Component Analysis (PCA) from panoramic and cephalometric data (SN-GoMe angle, interincisal angle, angle α, distance d in panoramic and cephalometric), would be the studies with the best methodological quality. Only one study based on PCA analysis have reliable accuracy in predicting MCI (predicting canine eruption of 88.3%).
Conclusions: The quality of evidence available is insufficient to establish definitive conclusions. However, it is suggested that some radiographic measures from cephalometric data such as: SN-GoMe Angle, Distance d, Angle α and Interincisal angle could be used as predictive values to determine MCI.
Methods: Literature search were carried out electronically in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Bireme and Scielo between 1960 and 2018, including all languages. Observational analytical studies were identified. The data were collected and extracted by two independent authors. The methodology of selected studies was assessed using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2). The quality of evidence and strength of recommendation was assessed by The Grading of Recommendations Assessment Tool, Development and Evaluation (GRADE).
Results: 4998 potentially eligible articles were identified in the first approach and finally 10 studies were included according to inclusion criteria. The quality of evidence was low due to high risk of bias. None of the studies fulfilled all of the QUADAS-2 methodological quality criteria to evaluate validity of predictor. According to the evidence available, Principal Component Analysis (PCA) from panoramic and cephalometric data (SN-GoMe angle, interincisal angle, angle α, distance d in panoramic and cephalometric), would be the studies with the best methodological quality. Only one study based on PCA analysis have reliable accuracy in predicting MCI (predicting canine eruption of 88.3%).
Conclusions: The quality of evidence available is insufficient to establish definitive conclusions. However, it is suggested that some radiographic measures from cephalometric data such as: SN-GoMe Angle, Distance d, Angle α and Interincisal angle could be used as predictive values to determine MCI.