Aparicio, J.(Miguel Hernandez University of Elche); Santin, D. (Complutense University of Madrid).
Abstract: Aparicio, Crespo-Cebada, Pedraja-Chaparro, and Santin (2017) recently extended the Camanho and Dyson (2006) Malmquist-type index (CDMI) for determining group performance in cross-sectional studies to panel or pseudo-panel databases. In that paper, it was shown that the pseudo-panel Malmquist index (PPMI) can be easily interpreted as the ratio of aggregated productivity changes in two groups of decision making units over time, if and only if a new difficult-to-interpret term, the so called ‘divergence component’ (DC), is equal to one. The aim of this paper is twofold. First, based upon considering a baseline group technology, we define a new base-group base-period PPMI where the DC always vanishes. Second, when more than two groups are analyzed, we show that under this framework the new base-group base-period PPMI, the new base-group CDMI and the components of both indexes satisfy the circular relation. Both results will make it easier for practitioners applying the two indexes in different economic sectors, regardless of how many groups are being compared.
Ponente: Mariano Matilla-García (UNED)
Título: TESTING FOR LINEAR AND NONLINEAR CAUSALITY FROM ECONOMIC TIME SERIES.
Fecha: 13/03/2018, 12:00h
Lugar: Sala de seminarios del CIO (Edificio Torretamarit), UMH.
Abstract: En el seminario se abordará el tema de las relaciones causales en la economía, y se presentarán y compararán algunas técnicas estadístico-econométricas disponibles. Se ilustrará la discusión y la presentación con un caso real de relaciones entre series financieras. De especial interés será el rol que desempeña la linealidad o no linealidad en las relaciones que potencialmente puedan establecerse entre distintos tipos de variables.
Ena, J.(Hospital Marina Baixa); Gaviria, A.Z.(Hospital de Fuenlabrada); Romero Sánchez, M. (Hospital de Fuenlabrada); Carretero Gómez, J. (Hospital de Zafra, Badajoz); Carrasco Sánchez, F.J. (Hospital Juan Ramón Jiménez); Segura Heras, J.V. (Universidad Miguel Hernández); Porto Pérez, A.B. (Complexo Hospitalario Universitario de A Coruña); Vázquez Rodríguez, P. (Complexo Hospitalario Universitario de A Coruña); González Bezerra, C.(Hospital San Juan de Dios); Gómez Huelgas, R. (Hospital Regional Universitario).
Background An objective and simple prognostic model for hospitalized patients with hypoglycemia could be helpful in guiding initial intensity of treatment. Methods We carried out a derivation rule for hypoglycemia using data from a nationwide retrospective cohort study of patients with diabetes or hyperglycemia carried out in 2014 (n = 839 patients). The rule for hypoglycemia was validated using a second data set from a nationwide retrospective cohort study carried out in 2016 (n = 561 patients). We derived our prediction rule using logistic regression with hypoglycemia (glucose less than 70 mg/dL) as the primary outcome. Results The incidence of hypoglycemia in the derivation cohort was 10.3%. Patient’s characteristics independently associated with hypoglycemia included episodes of hypoglycemia during the previous three months (odds ratio [OR]: 6.29, 95% confidence interval [95%CI]: 3.37–11.79, p < 0.001) estimated glomerular filtration rate lower than 30 mL/min/1.73 m2 (OR: 2.32, 95%CI: 1.23–4.35, p = 0.009), daily insulin dose greater than 0.3 units per Kg (OR: 1.74, 95%CI: 1.06–2.85, p = 0.028), and days of hospitalization (OR: 1.03, 95%CI: 1.01–1.04, p = 0.001). The model showed an area under the curve (AUC): 0.72 (95%CI: 0.66–0.78, p < 0.001). The AUC in the validation cohort was: 0.71 (95%CI: 0.63–0.79, p < 0.001). Conclusions The rule showed fair accuracy to predict hypoglycemia. Implementation of the rule into computer systems could be used in guiding initial insulin therapy. © 2017 European Federation of Internal Medicine.
Galarza, M. (University of Murcia); Giménez, A.( University Miguel Hernández); Amigó, J.M.(University Miguel Hernández); Schuhmann, M.(University Hospital Tuebingen); Gazzeri, R. (San Giovanni Addolorata Hospital); Thomale, U. (Charité Universitätsmedizin Berlin); McAllister, J.P. (Washington University School of Medicine)
Background: The flow pattern of the cerebrospinal fluid is probably the most important factor related to obstruction of ventricular catheters during the normal treatment of hydrocephalus. To better comprehend the flow pattern, we have carried out a parametric study via numerical models of ventricular catheters. In previous studies, the flow was studied under steady and, recently, in pulsatile boundary conditions by means of computational fluid dynamics (CFD) in three-dimensional catheter models. Objective: This study aimed to bring in prototype models of catheter CFD flow solutions as well to introduce the theory behind parametric development of ventricular catheters. Methods: A preceding study allowed deriving basic principles which lead to designs with improved flow patterns of ventricular catheters. The parameters chosen were the number of drainage segments, the distances between them, the number and diameter of the holes on each segment, as well as their relative angular position. Results: CFD results of previously unreleased models of ventricular catheter flow solutions are presented in this study. Parametric development guided new designs with better flow distribution while lowering the shear stress of the catheters holes. High-resolution 3D printed catheter solutions of three models and basic benchmark testing are introduced as well. Conclusions: The next generation of catheter with homogeneous flow patterns based on parametric designs may represent a step forward for the treatment of hydrocephalus, by possibly broadening their lifespan. © 2017, Springer-Verlag GmbH Germany.