ABSTRACT
Background: The prediction of the length of stay at the moment of hospital admission is of outmost importance. Many studies have used lineal models to predict this variable, but there are inherent limitations to these models. The use of non lineal models has been scarce. Aim: To develop a non lineal model to predict length of stay in intensive care units. Material and methods: Retrospective analysis of 294 patients admitted to two intensive care units in Santiago, Chile. The severity of the disease motivating the admission was nominally quantified. This and other physiological variables were included in the model. The length of stay was modeled using Artificial Neural Networks. Results: The model yielded an error of 8.7 percent (3.6 ñ 0.4 days, CI 95 percent) and a correlation coefficient of 0.9 (p <0.001) for the prediction of length of stay. Using net sensitivity analysis, the model determined that gastrointestinal diseases, infections and respiratory problems were the main causes of prolongation of intensive care unit stay. Conclusions: Intensive care units should have, in the future, computer systems that gather vital information to predict length of stay
Subject(s)
Humans , Male , Female , Intensive Care Units , Neural Networks, Computer , Survivors , Severity of Illness Index , Models, Theoretical , Forecasting/methods , Length of Stay/statistics & numerical dataABSTRACT
Charles Darwin es el pensador que más ha influido en la visión que tiene el mundo la gente corriente. Los conceptos de Darwin se han expandido, por otros autores más allá de la Biología, a veces con resultados no afortunados. Desde hace cerca de una década ha surgido una nueva disciplina, la Medicina Darwiniana o Evolutiva, que pretende buscar explicaciones para los procesos patológicos en la Teoría de la Evolución Darwin. Estas ideas han estado latentes durante mucho tiempo, y sólo los espectaculares avances de la Génetica en la actualidad han permitido encontrar ventajas adaptativas en genes alterados. En este trabajo se buscan las bases de esta nueva disciplina, y se discuten ejemplos específicos de algunos fen¢menos patológicos que resultan dificiles de explicar por el pensamiento tradicional de la Medicina