Use of animals in dental research: Trends and ethical reflections.

This study aimed to survey and analyze the profile of experimental dental research in animals, verifying its trends. We evaluated studies developed with the use of animals in vivo, published in 10 dental journals with high impact factors, from 2015 to 2020. From 1652 studies retrieved, 594 involved in vivo experimentation on animals and were analyzed further. Rats were the species most used and with the highest mean of animals per study. Ferrets, although presenting the lowest rate of publications, had the second highest mean of animals per study. Periodontics was the dental specialty with the highest number of publications, while oral rehabilitation had the lowest number. The data on the institution responsible for reviewing animal research protocols approval, sample size, anesthesia and analgesia were provided in 93.10%, 83%, 70.54% and 23.74% of studies, respectively. In 53% of studies, euthanasia was specified and anesthetic overdose was the method most used. Over the period analyzed, there was a reduction in animal studies in vivo, and periodontics was the specialty that most used this experimental model. Although most studies mentioned approval by an ethics committee, some publications neglected to mention sample size, anesthesia and euthanasia. The omission of essential information may raise scientific and ethical concerns.

A odontologia legal no contexto de ensino da FORP-USP: um levantamento histórico / Forensic Dentistry in the teaching context of the School of Dentistry of Ribeirão Preto ­ University of São Paulo: a historical survey

A Odontologia Legal (OL) é uma especialidade da Odontologia que teve seu surgimento associado a anseios sociais relacionados à identificação humana. Logo se percebeu a contribuição que poderia fornecer no atuar profissional, especialmente se inserida no currículo acadêmico. Esse artigo teve como objetivo realizar um levantamento histórico dos componentes curriculares da área de OL da Faculdade de Odontologia de Ribeirão Preto da Universidade de São Paulo (FORP-USP) e analisar o desenvolvimento de suas ementas disciplinares. Foi realizada uma pesquisa documental com abordagem descritiva e qualitativa dos dados da estrutura curricular do curso de graduação da referida instituição entre os anos de 1962 e 2019. Assim, a coleta das informações deu-se utilizando livros e sítios eletrônicos que continham as ementas disciplinares. A disciplina de OL esteve presente no ensino da FORP-USP desde que se tem registro (1962), quando era denominada "Odontologia Legal, Legislação e Ética Profissional". A área manteve-se vigente, apesar das modificações que culminaram na criação e extinção de determinadas disciplinas. A Odontologia Legal é fundamental na orientação das condutas éticas e legais da profissão e, dessa forma, esteve presente no curso de graduação da FORP-USP desde os primórdios da instituição, e vem sendo trabalhada e desenvolvida com o passar dos anos. Conclui-se que foi possível determinar a trajetória, cronologia e arranjo das alterações das disciplinas relacionadas com a área de Odontologia Legal da FORP-USP a partir de 1962, o que permitiu observar a evolução da área, sobretudo no que diz respeito às metodologias e conteúdos, bem como a diversificação de material bibliográfico utilizado no ensino.

Improving preoperative risk-of-death prediction in surgery congenital heart defects using artificial intelligence model: A pilot study.

BACKGROUND: Congenital heart disease accounts for almost a third of all major congenital anomalies. Congenital heart defects have a significant impact on morbidity, mortality and health costs for children and adults. Research regarding the risk of pre-surgical mortality is scarce. OBJECTIVES: Our goal is to generate a predictive model calculator adapted to the regional reality focused on individual mortality prediction among patients with congenital heart disease undergoing cardiac surgery. METHODS: Two thousand two hundred forty CHD consecutive patients' data from InCor's heart surgery program was used to develop and validate the preoperative risk-of-death prediction model of congenital patients undergoing heart surgery. There were six artificial intelligence models most cited in medical references used in this study: Multilayer Perceptron (MLP), Random Forest (RF), Extra Trees (ET), Stochastic Gradient Boosting (SGB), Ada Boost Classification (ABC) and Bag Decision Trees (BDT). RESULTS: The top performing areas under the curve were achieved using Random Forest (0.902). Most influential predictors included previous admission to ICU, diagnostic group, patient's height, hypoplastic left heart syndrome, body mass, arterial oxygen saturation, and pulmonary atresia. These combined predictor variables represent 67.8% of importance for the risk of mortality in the Random Forest algorithm. CONCLUSIONS: The representativeness of "hospital death" is greater in patients up to 66 cm in height and body mass index below 13.0 for InCor's patients. The proportion of "hospital death" declines with the increased arterial oxygen saturation index. Patients with prior hospitalization before surgery had higher "hospital death" rates than who did not required such intervention. The diagnoses groups having the higher fatal outcomes probability are aligned with the international literature. A web application is presented where researchers and providers can calculate predicted mortality based on the CgntSCORE on any web browser or smartphone.