Objetivo: Determinar las actitudes hacia la investigación de internos de obstetricia rotantes en el Hospital Sergio E. Bernales (HSEB) durante diciembre 2018 a enero 2019. Métodos: Estudio transversal. La población estuvo constituida por internos de obstetricia que realizaban prácticas profesionales a quienes se les aplicó una escala validada de 28 ítems distribuidos en 6 dimensiones, que evaluó actitudes hacia la investigación. Resultados: Participaron del estudio 57 internos de obstetricia. La edad promedio fue de 23,5 ± 2,1 años y 96,5% eran de sexo femenino. El 54,4% de internos presentó actitud regular hacia la investigación científica, el 24,6% tuvo una buena actitud y 21% una mala actitud. El 93,0% de internos estuvo de acuerdo o muy de acuerdo con que la publicación en una revista ayuda a mejorar la práctica clínica, la mayoría se sentía capaz de interpretar un artículo científico (68,4%) y preparados para realizar una investigación relacionada con la carrera (54,3%); por otro lado, consideraban que para realizar investigaciones de calidad en la universidad debían contar con herramientas básicas físicas y virtuales (94,7%) y que el curso de redacción científica debía centrarse en la enseñanza de la elaboración de un artículo (84,2%). La mayoría estuvo muy en desacuerdo y en desacuerdo en optar por otra modalidad de graduación que no sea la tesis (50,9%). Conclusión: Más de la mitad de los internos de obstetricia del HSEB tenían actitud regular hacia la investigación. Los resultados evidencian la necesidad de continuar fortaleciendo y promoviendo la investigación en los estudiantes de obstetricia.

Objective. To perform a bibliometric analysis of scientific production related to gut microbiota and Parkinson’s disease between 2011 and 2020. Methods. A descriptive, retrospective, cross-sectional, and bibliometric study was carried out. The Scopus database was used as a source to evaluate the worldwide scientific production on intestinal microbiota and its relationship with Parkinson’s disease. Data were extracted from Scopus using a formula developed with thesaurus terms MeSH (Medline) and Emtree (Embase). Results. A total of 591 documents were found. The retrieved manuscripts received an average of 41.9 citations per document. Four of the 10 most productive authors were Italian. The University of Helsinki (Finland) was the institution with the highest scientific production (19 papers) and the highest impact (5921 citations). In terms of productivity and impact, Movement Disorders ranked first with 38 papers and 2782 citations, and those papers published in Q1 quartile journals exceeded the sum of the remaining quartiles. Papers with international collaboration were the most cited. Keyword analysis showed that the terms Parkinson Disease, Disease, and Intestine Flora were the most frequent. Conclusion. The number of papers on Parkinson’s disease and gut microbiota has been increasing; however, high-quality journals maintain the same high publication rate. International collaboration from high-income countries played an important role in the impact generated by the publications.

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A BSTRACT Objective: The aim of this study was to describe artificial intelligence, machine learning, and “Dentronics” applications and perspectives in dentistry. Materials and Methods: A literature review was carried out to identify the applications of artificial intelligence in the field of dentistry. A specialized search for information was carried out in three databases such as Scopus, PubMed, and Web of Science. Manuscripts published from January 1988 to November 2021 were analyzed. Articles were included without any restriction by language or country. Results: Scopus, PubMed, and Web of Science were found to have 215, 1023, and 98 registered manuscripts, respectively. Duplicates (191 manuscripts) were eliminated. Finally, 4 letters, 12 editorials, 5 books, 1 erratum, 54 conference papers, 3 conference reviews, and 222 reviews were excluded. Conclusions: Artificial intelligence has revolutionized prediction, diagnosis, and therapeutic management in modern dentistry. Finally, artificial intelligence is a potential complement to managing future data in this area.

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