Design of a predictive model for the early diagnosis of ectopic pregnancy

Abstract

Introduction: Despite advances in science and the introduction of new technology and biochemical markers for early diagnosis of EE, it is still diagnosed late, which puts the reproductive future and the life of the woman at risk. In addition, good anamnesis and physical examination, if complemented with these advances, would allow this diagnosis to be made in a shorter time and thus improve morbidity and mortality due to this cause. Materials and methods: An analytical observational study of the case-control type was carried out in patients operated on with a diagnosis of EE at the Materno Norte "Tamara Bunke Bíder" and "Materno Sur Mariana Grajales Coello" Gynecological and Obstetric Hospitals in Santiago de Cuba, in the period from January 2010 to December 2017. The theoretical methods used to develop the predictive model for the early diagnosis of ectopic pregnancy were analysis and synthesis, historical-logical, induction-deduction, documentary review, and holistic-dialectical. Results: A multivariate binary logistic regression analysis was performed to develop the logistic model to estimate the predictive capacity of the independent factors involved in explaining the development of ectopic pregnancy. Discussion: The design of a predictive model must be based on the tools of clinical epidemiology for observational studies. This is the methodological strategy used in this research. Conclusions: Its particularities are demonstrated in the way of approaching the construction of the model, based on the search for risk factors in the population under study and in the way of applying one of the established paths to achieve this goal.