Our results confirm previous observations of altered ceramide levels in AD, which however appear to show no clear relationship with FLG mutations.

Asthma is no longer considered a single disease, but a common label for a set of heterogeneous conditions with shared clinical symptoms but associated with different cellular and molecular mechanisms. Several wheezing phenotypes coexist at preschool age but not all preschoolers with recurrent wheezing develop asthma at school-age; and since at the present no accurate single screening test using genetic or biochemical markers has been developed to determine which preschooler with recurrent wheezing will have asthma at school age, the asthma diagnosis still needs to be based on clinical predicted models or scores. The purpose of this review is to summarize the existing and most frequently used asthma predicting models, to discuss their advantages/disadvantages, and their accomplishment on all the necessary consecutive steps for any predictive model. Seven most popular asthma predictive models were reviewed (original API, Isle of Wight, PIAMA, modified API, ucAPI, APT Leicestersher, and ademAPI). Among these, the original API has a good positive LR~7.4 (increases the probability of a prediction of asthma by 2–7 times), and it is also simple: it only requires four clinical parameters and a peripheral blood sample for eosinophil count. It is thus an easy model to use in any rural or urban health care system. However, because its negative LR is not good, it cannot be used to rule out the development of asthma.

Numerous diagnostic tests report their results quantitatively, using continuous scales. Receiver operating characteristic curve (ROC) analysis provides a statistical method for the assessment of the diagnostic accuracy of these tests, being used for three specific purposes: determine of the cutoff value with the highest sensitivity and specificity, evaluate the discriminative capacity of the diagnostic test, in other words, its ability to differentiate healthy versus sick individuals, and compare the discriminative capacity of two or more diagnostic tests that express their results as continuous scales. Based on a real clinical investigation, this article illustrates theoretical aspects regarding the construction of ROC curves, being its objective to help readers and investigators interpret correctly their results.

The GRADE system: a change in the way of assessing the quality of evidence and the strength of recommendations L as diferentes personas y grupos que toman decisiones en salud no solo deben considerar la magnitud de los efectos de diferentes cursos de acción (intervenciones) sino también la confianza que es posible tener en dichas estimaciones, ya sea en el contexto de una revisión sistemática o en la elaboración de recomendaciones para una guía de práctica clínica. El concepto "calidad de la evidencia" refleja la confianza que podemos tener en que conocemos los efectos de una intervención. La "fuerza de la recomendación" distingue situaciones en donde la evidencia muestra que una alternativa es claramente superior y, en consecuencia, como clínicos debiéramos tomar esa alternativa con todos o casi todos nuestros pacientes, de situaciones donde hay incertidumbre respecto de cuál es la mejor alternativa y, por tanto, debiéramos considerar los valores y preferencias de los pacientes y las circunstancias clínicas para tomar una decisión (idealmente utilizando un enfoque de decisiones compartidas).Hasta hace poco tiempo existían decenas de sistemas para clasificar la calidad de la evidencia y la fuerza de las recomendaciones 1 . Muchos de ellos utilizados únicamente por el grupo u organización que los había desarrollado. Afortunadamente,

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