Status of research on prediction models for severity in confirmed Covid-19 patients

Abstract

Introduction: Previous knowledge in the scientific literature on clinical prediction models in patients with COVID-19 may be useful for the development of new research. Objective: To describe the sources, authors, documents and key issues that are part of the research front; identify which models, outcome variables, predictors and algorithms have been relevant; and identify to what extent the available models could meet the quality attributes and what characteristics they must have to be applicable to the Cuban context. Material and Methods: A review and scientometric analysis was carried out on the ongoing research, along with a validation of clinical predictive models for COVID-19. Scientometric indicators were used and a thematic map was made for the analysis of the conceptual structure of the subject. Results: The subject was of great interest, with papers published in the highest impact journals. It is possible to distinguish a context of low and high risk application according to the primary and secondary health care levels. The systematic review published by Wynants et al. was the publication with the greatest impact and an important source for the identification of models, main components, as well as possible causes of bias. Conclusions: The literature recognizes that most of the published models are not recommended for general use in clinical practice, so it is an open research front. However, the data obtained could be useful for the development and validation of Cuban models.

Keywords

• pronóstico, triaje, modelos teóricos, covid-19, sars-cov-2, pandemia.