Using multivariate sequential patterns to improve survival prediction in intensive care burn unit

Resuscitation and stabilization are key issues in Intensive Care Burn Units and early survival predictions help to decide the best clinical action during these phases. Current survival scores of burns focus on clinical variables such as age or the body surface area. However, the evolution of other parameters (e.g. diuresis or fluid balance) during the first days is also valuable knowledge. In this work we suggest a methodology and we propose a Temporal Data Mining algorithm to estimate the survival condition from the patient’s evolution. Experiments conducted on 480 patients show the improvement of survival prediction.

Aprendizaje integrado de Epidemiología y Bioestadística en el Grado de Medicina: valoración de los estudiantes

Los objetivos fueron conocer la valoración de los alumnos de 2º de Medicina sobre la inte-gración Epidemiología-Bioestadística y comparar su percepción a comienzo y final de curso. Se elaboraron dos cuestionarios con afirmaciones que los alumnos valoraron mediante una escala tipo Likert. Participaron 102 estudiantes. Para comparar los resultados a principio y final de curso se utilizó la prueba de rangos con signo de Wilcoxon. El 83% creía al finalizar el curso que comprendían la importancia de Epidemiología-Bioestadística en Medicina y les parecía interesante estudiarlas de forma integrada. Al inicio de curso, un 46,1% pensaba que la asignatura iba a ser interesante y al final este porcentaje fue 69,6%. Al inicio, el 69,6% veía la relación entre la Medicina y la Estadística y al final, el 83,3%. El 41% creía al inicio que iban a adquirir competencias fundamentales para el desempeño profesional y al final lo creía el 57,8%.

Taking advantage of an old concept, "illegitimate transcription", for a proposed novel method of genetic diagnosis of McArdle disease

McArdle disease is a metabolic disorder caused by pathogenic mutations in the PYGM gene. Timely diagnosis can sometimes be difficult with direct genomic analysis, which requires additional studies of cDNA from muscle transcripts. Although the "nonsense-mediated mRNA decay" (NMD) eliminates tissue-specific aberrant transcripts, there is some residual transcription of tissue-specific genes in virtually all cells, such as peripheral blood mononuclear cells (PBMCs).We studied a subset of the main types of PYGM mutations (deletions, missense, nonsense, silent, or splicing mutations) in cDNA from easily accessible cells (PBMCs) in 12 McArdle patients.Analysis of cDNA from PBMCs allowed detection of all mutations. Importantly, the effects of mutations with unknown pathogenicity (silent and splicing mutations) were characterized in PBMCs. Because the NMD mechanism does not seem to operate in nonspecific cells, PBMCs were more suitable than muscle biopsies for detecting the pathogenicity of some PYGM mutations, notably the silent mutation c.645G>A (p.K215=), whose effect in the splicing of intron 6 was unnoticed in previous muscle transcriptomic studies.We propose considering the use of PBMCs for detecting mutations that are thought to cause McArdle disease, particularly for studying their actual pathogenicity.