ABSTRACT
Objective: To perform a systematic review relating the existence of root resorption during orthodontic treatment. Methods: The research was performed in two electronic databases (PubMed and OpenGrey). The OpenGrey database was used exclusively for searching the "grey literature", avoiding selection and publication bias. Eligibility criteria included full texts available online, but with no language restriction. Aiming to work with more current articles on the subject, a filter for thelast ten years was applied. Articles that had no direct relation with the main outcome of this study were excluded, as well as clinical case reports and opinions, literature review articles, editorials, and letters to the editor. All eligible studies were assessed for risk of bias and individual quality, and all research steps were performed independently by two eligibility reviewers. Results: Initially, 77 articles were selected, but after the application of exclusion criteria, only 71 were included. Six articles were eligible for qualitative assessment. Overall, incisors are the teeth most affected by root resorption and there is a higher rate of root resorption in retraction mechanics. Conclusion: There is a relationship between root resorption and orthodontic treatment.
ABSTRACT
Objetivou-se com este trabalho apresentar uma metodologia de identificação e modelagem da autocorrelação residual considerando ajustes individuais do modelo de Wood às lactações de cabras leiteiras e também avaliar a influência de tal modelagem na qualidade do ajuste. O modelo de Wood foi ajustado individualmente às lactações, considerando três estruturas residuais. Na primeira, assumiu-se independência dos erros (EI) para todas as lactações, na segunda, assumiu-se a estrutura de erros autoregressivos de primeira ordem (AR1) para todas as lactações e, na terceira, nomeada por EI-AR1, foi utilizada a estrutura de erros AR1 somente para as lactações que apresentaram autocorrelação residual, segundo o teste de Durbin-Watson, e de EI para as demais. As três situações de ajuste foram comparadas pelos percentuais de convergência e pelas médias dos quadrados médios dos erros (QME) e dos coeficientes de determinação ajustados (R²aj). As médias dos QME e dos R²aj apresentaram valores semelhantes nas três situações de estrutura residual. No entanto, o modelo com estrutura EI-AR1 apresentou maior convergência, o que consiste em uma vantagem, já que permite que um maior número de animais seja avaliado quanto à sua curva de lactação. Portanto, em função da maior convergência obtida, o ajuste do modelo de Wood com a estrutura EI-AR1 consiste na opção mais indicada para grandes conjuntos de dados.
The objective of this research was to present a methodology for identification and modeling of residual autocorrelation considering individual adjustments of the Wood's model to lactation dairy goats and evaluate the influence of such modeling in the quality of adjustment. The Wood's model was adjusted individually for lactations in three different ways, the first have assumed independence of errors (IE) for all lactations, the second have assumed autoregressives first order errors (AR1) for all lactations and the third, named (IE-AR1), was used the AR1 errors structure only for lactations that showed residual autocorrelation according to Durbin-Watson test, and the IE errors structure for the other lactations. The three ways of adjustment were compared by the percentage of convergence and the average of the mean square errors (MSE) and coefficients of determination adjusted (R²adj). The average of MSE and R²aj were very similar in the three cases of residual structure. However, the model with IE-AR1 residual structure showed a higher rate of convergence, which is an advantage, as it allows a greater number of animals are evaluated for their lactation curve. Therefore, due to the increasing convergence obtained, the fit of the Wood's model with IE-AR1 residual structure is the option most suitable for large data sets.