A critical analysis of research methods and experimental models to study the load capacity and clinical behaviour of the root filled teeth

• Autor(a) principal: Ordinola-Zapata, Ronald
• Data de Publicação: 2022
• Outros Autores: Lin, Fei, Nagarkar, Sanket, Perdigão, Jorge
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.14/37314
• topic: Clinical trials; Cyclic loading; Finite element analysis; Load capacity

The prognosis of root-filled teeth depends not only on a successful root canal treatment but also on the restorative prognosis. This critical review discusses the advantages and limitations of various methodologies used to assess the load capacity or clinical survivability of root-filled teeth and restorations. These methods include static loading, cyclic loading, finite element analysis and randomized clinical trials. In vitro research is valuable for preclinical screening of new dental materials or restorative modalities. It also can assist investigators or industry to decide whether further clinical trials are justified. It is important that these models present high precision and accuracy, be reproducible, and present adequate outcomes. Although in vitro models can reduce confounding by controlling important variables, the lack of clinical validation (accuracy) is a downside that has not been properly addressed. Most importantly, many in vitro studies did not explore the mechanisms of failure and their results are limited to rank different materials or treatment modalities according to the maximum load capacity. An extensive number of randomized clinical trials have also been published in the last years. These trials have provided valuable insight on the survivability of the root-filled tooth answering numerous clinical questions. However, trials can also be affected by the selected outcome and by intrinsic and extrinsic biases. For example, selection bias, loss to follow-up and confounding. In the clinical scenario, hypothesis-based studies are preferred over observational and retrospective studies. It is recommended that hypothesis-based studies minimize error and bias during the design phase.