Clustering Disjoint HJ-Biplot: A new tool for identifying pollution patterns in geochemical studies.

This paper introduces a new mathematical algorithm termed Clustering Disjoint HJ-Biplot (CDBiplot), which searches for the underlying data structure in order to find the best classification of the object groups in a reduced space. To this end, disjoint factorial axes are generated, in which each variable only contributes to the formation of one factorial axis. A graphical representation of the individuals and variables is performed using the HJ-Biplot method. In order to facilitate the use of this new method within any practical context, a function in the language R has been developed. This work applies the CDBiplot to study an environmental geochemistry case involving environmental pollution in river surface sediments. The study focuses on an area close to an important mining and metallurgical site, where sediments share a similar geological origin and chemical composition. The algorithm permitted a detailed study of the geochemical interactions and performed an excellent separation of the samples. Thus, the groups obtained were formed according to a similar geological origin, location, and nature of the anthropogenic inputs based only on chemical composition data. These results allowed clear identification of the sources of pollution and the delimitation of the polluted zones. All things considered, we conclude that the proposed algorithm is a powerful tool for studying environmental geochemistry data sets, and suggest that the application of this methodology be extended to other research fields.

Characteristics of patients registered with chronic renal disease in Castilla y León and survival analysis of transplanted patients and their grafts.

INTRODUCTION: Chronic kidney disease (CKD) is an important public health problem. Kidney transplantation is associated with increase survival and improvement of quality of life. OBJECTIVES: To describe the sociodemographic and clinical characteristics of patients registered in Castilla y León. To perform a survival analysis of transplant patients and their grafts. To evaluate survival depending on the transplant centre. METHODS: Descriptive study with data collected until 31 December 2008 from the Registro de Diálisis y Trasplante Renal de la Comunidad de Castilla y León (REDI). The data was described differentiating prevalent and incidents patients. Survival data was assessed with the Kaplan-Meier method. RESULTS: On 31 December 2008, 2.498 patients were on Renal Replacement Therapy (RRT) (976.8 pmp); in 2008, 337 started treatment (131.8 pmp) and 94 received kidney transplant (36.8 pmp). The first cause of CKD for incident patients is diabetes (25.0%), followed by vascular diseases (18.1%). For prevalent patients: glomerulonephritis (16.5%) and diabetes (14.4%). Differences (p = 0.0021) were observed for the treatment initiation age, group of disease and prevalent patients (p <0.0001). During 11 years 1.062 transplants were performed in 1.012 patients and 879 are still functioning (83%). In this period, the survival probability for the transplant patients is 81.076% (± 0.023), and for the 838 patients with first functioning graft is 89.336% (± 0.016). Median graft survival is between 8.7 and 9.3 years (95% confidence). CONCLUSIONS: Most of the transplants during the last 11 years are still functioning. There are no differences when comparing graft survival at the approved centers in Castilla y León (p = 0.358).

Características de los pacientes registrados con enfermedad renal crónica en Castilla y León y análisis de supervivencia de los trasplantados y de sus injertos / Characteristics of patients registered with chronic renal disease in Castilla y León and survival analysis of transplanted patients and their grafts

Introducción: La enfermedad renal crónica (ERC) es un problema importante de salud pública. El trasplante renal se relaciona con el aumento de la supervivencia y con la mejora en la calidad de vida. Objetivos: Describir las características sociodemográficas y clínicas de los pacientes registrados en Castilla y León. Realizar un análisis de supervivencia de los pacientes sometidos a trasplante y de sus injertos. Evaluar la supervivencia en función del centro de trasplante. Métodos: Estudio descriptivo con datos recogidos hasta 31 de diciembre de 2008 en el Registro de Diálisis y Trasplante Renal de la Comunidad de Castilla y León (REDI). Descripción general de los pacientes, diferenciando incidentes de prevalentes. Se realizaron análisis de supervivencia utilizando el método de Kaplan-Meier. Resultados: A 31 de diciembre de 2008, había 2.498 pacientes en tratamiento sustitutivo renal (TSR) (976,8 pacientes por millón de población, pmp); en 2008, 337 iniciaron tratamiento (131,8 pmp) y 94 fueron sometidos a trasplante (36,8 pmp). La causa más frecuente de ERC en pacientes incidentes es la diabetes (25,0%), seguida de las enfermedades vasculares (18,1%). En pacientes prevalentes las causas más frecuentes son glomerulonefritis (16,5%) y diabetes (14,4%). Hay diferencias (p = 0,0021) en la edad de inicio del tratamiento, según grupo de enfermedad (en prevalentes también, p <0,0001) (AU)

Introduction: Chronic kidney disease (CKD) is an important public health problem. Kidney transplantation is associated with increase survival and improvement of quality of life. Objectives: To describe the sociodemographic and clinical characteristics of patients registered in Castilla y León. To perform a survival analysis of transplant patients and their grafts. To evaluate survival depending on the transplant centre. Methods: Descriptive study with data collected until 31 December 2008 from the Registro de Diálisis y Trasplante Renal de la Comunidad de Castilla y León (REDI). The data was described differentiating prevalent and incidents patients. Survival data was assessed with the Kaplan-Meier method. Results: On 31 December 2008, 2.498 patients were on Renal Replacement Therapy (RRT) (976.8 pmp); in 2008, 337 started treatment (131.8 pmp) and 94 received kidney transplant (36.8 pmp) (AU)

Tamaño de la muestra en investigación clínica / Size of sample in clinical investigation

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Identifying molecular markers associated with classification of genotypes by External Logistic Biplots.

UNLABELLED: For characterization of genetic diversity in genotypes several molecular techniques, usually resulting in a binary data matrix, have been used. Despite the fact that in Cluster Analysis (CA) and Principal Coordinates Analysis (PCoA) the interpretation of the variables responsible for grouping is not straightforward, these methods are commonly used to classify genotypes using DNA molecular markers. In this article, we present a novel algorithm that uses a combination of PCoA, CA and Logistic Regression (LR), as a better way to interpret the variables (alleles or bands) associated to the classification of genotypes. The combination of three standard techniques with some new ideas about the geometry of the procedures, allows constructing an External Logistic Biplot (ELB) that helps in the interpretation of the variables responsible for the classification or ordination. An application of the method to study the genetic diversity of four populations from Africa, Asia and Europe, using the HapMap data is included. AVAILABILITY: The Matlab code for implementing the methods may be obtained from the web site: http://biplot.usal.es.

[Use of multilevel models in health research]. / Utilización de los modelos multinivel en investigación sanitaria.

OBJECTIVE: The aim of this study was to analyze the use of multilevel methodology in health sciences. DESIGN: A literature search was performed in Medline for articles published between 1995 and 2001. Fifteen search words were used, some of which were "multilevel model", "multilevel analysis", "hierarchical linear model", "mixed model", and "random effects model". A total of 1288 abstracts were retrieved. Two hundred twenty-two of the articles on theoretical and/or applied issues related to multilevel methods were examined to determine their current use, the type of model, the number of levels, the units of analysis and the outcome variables related to health sciences. RESULTS: 66.7% of the articles studied was found with the keywords: "multilevel analysis", "multilevel modelling" and "multilevel model". Fifty-six percent of the articles were multilevel applications in different health sciences. However, in 10% of the articles, the main objective was to present and disseminate the methodology in a language comprehensible to non-specialists. CONCLUSIONS: The use of multilevel modelling in health has increased with time and is being applied in different health areas and specialties. However, it is still not considered a commonly used technique.

Utilización de los modelos multinivel en investigación sanitaria / Use of multilevel models in health research

OBJETIVO: El propósito de este artículo es analizar el uso de la metodología multinivel en las ciencias de la salud. DISEÑO: Se llevó a cabo una búsqueda bibliográfica en Medline de los artículos publicados entre 1995 y 2001, utilizando 15 palabras de búsqueda, entre las que se encuentran «multilevel model», «multilevel analysis», «hierarchical linear model», «mixed model» y «random effects model», obteniéndose un total de 1.288 resúmenes de artículos. Se examinaron los 222 artículos teóricos y/o aplicaciones realmente relacionadas con métodos multinivel, para determinar el nivel de uso actual, el tipo de modelo, el número de niveles, las unidades de análisis y las variables de respuesta a través de las especialidades en salud. RESULTADOS: El 66,7% de los artículos estudiados se encontraron con las palabras de búsqueda «multilevel analysis», «multilevel modelling» y «multilevel model». El 56% de los artículos son aplicaciones de multinivel en diferentes áreas de la salud; no obstante, merece destacar que un 10% de los trabajos tienen como objetivo exponer y difundir la metodología en un lenguaje comprensible para los no especialistas. CONCLUSIONES: El uso de los modelos multinivel en salud ha aumentado con los años, aplicándose en diferentes áreas o especialidades de salud, pero aún no se los considera una técnica de uso habitual

OBJECTIVE: The aim of this study was to analyze the use of multilevel methodology in health sciences. DESIGN: A literature search was performed in Medline for articles published between 1995 and 2001. Fifteen search words were used, some of which were «multilevel model», «multilevel analysis», «hierarchical linear model», «mixed model», and «random effects model». A total of 1288 abstracts were retrieved. Two hundred twenty-two of the articles on theoretical and/or applied issues related to multilevel methods were examined to determine their current use, the type of model, the number of levels, the units of analysis and the outcome variables related to health sciences. RESULTS: 66.7% of the articles studied was found with the keywords: «multilevel analysis», «multilevel modelling» and «multilevel model». Fifty-six percent of the articles were multilevel applications in different health sciences. However, in 10% of the articles, the main objective was to present and disseminate the methodology in a language comprehensible to non-specialists. CONCLUSIONS: The use of multilevel modelling in health has increased with time and is being applied in different health areas and specialties. However, it is still not considered a commonly used technique