INFLUENCIA DEL VOLUMEN DE ENTRENAMIENTO EN LA SINTOMATOLOGÍA DE ANSIEDAD Y DEPRESIÓN DURANTE LA ADOLESCENCIA TARDÍA

Objetivo: determinar las asociaciones transversales entre la práctica o no de deporte y según el nivel de competición con la sintomatología de ansiedad y depresión durante la adolescencia tardía.Metodología: evaluamos en 6791 adolescentes (3220 chicas), 5327 de 14-16 años y 1464 de 17-19 años la sintomatología de ansiedad (Escala de Ansiedad de Zung) y depresión (Inventario de Depresión de Beck). 918 sujetos no hacían deporte, 2521 hacían deporte no competitivo, 1914 competían a nivel local-autonómico y 1438 a nivel nacional-internacional en modalidades incluidas en el programa de los JJOO de verano.Resultados: los adolescentes que no realizaban deporte mostraron mayor sintomatología de ansiedad y depresión que los que realizaban deporte no competitivo (p = 0.000). Los adolescentes que realizaban deporte no competitivo mostraron mayor sintomatología de ansiedad y depresión que los que realizaban deporte competitivo (p = 0.000). Los adolescentes que competían a nivel nacional-internacional tuvieron menores niveles de ansiedad y depresión que los que competían a nivel local-regional, pero las diferencias fueron menores y solo significativas para la ansiedad en chicos. Las chicas, especialmente las de mayor edad, tuvieron mayor sintomatología de ansiedad y depresión que los chicos (p = 0.000), pero sin influencia en la asociación con la práctica de deporte y con el nivel de competición.Conclusiones: la práctica de deporte, especialmente de deporte competitivo está asociado con menor sintomatología de ansiedad y depresión en sujetos de ambos sexos durante la adolescencia tardía. La competición al máximo nivel durante la adolescencia tardía no se asocia con mayor sintomatología de ansiedad y depresión.Palabras clave: ansiedad, depresión, nivel de competición, sexo, adolescencia.<br /

La desmotivación del alumnado en Educación Física y sus consecuencias

Estrategias y propuestas de actuación, transcritas a través de las diferentes asignaturas del Máster, para el tratamiento de la desmotivación de los alumnos en clases de Educación Física

Correction to: Prognostic influence of prior chronic obstructive pulmonary disease in patients admitted for their first episode of acute heart failure

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Low co-morbidity, low levels of malnutrition, and low risk of falls in a community-dwelling sample of 85-year-old are associated with succesful aging: the Octabaix study

The population is aging throughout the world. Preserving physical and cognitive functions is crucial to successful aging. The aim of this study was to determine the proportion of 85-year-old community-dwelling subjects aging successfully, applying a quantitative approach, and assessing the association of successful aging with sociodemographic data, global geriatric assessment, and co-morbidity. This was a community-based survey of inhabitants aged 85 years, with 328 out of 487 subjects born in 1924 assigned to seven primary health-care teams, representing a participation rate of 67.5%. Sociodemographic variables, Barthel index (BI), the Spanish version of the Mini-Mental State Examination (MEC), Mini Nutritional Assessment (MNA), Charlson Index, Gait Rating Scale, social risk, quality of life (QoL), and prevalent chronic diseases were assessed. Subjects scoring higher than 90 on the BI and higher than 24 on the MEC were compared with the rest. Multiple regression analysis was performed. Using these criteria, successful aging status was defined in 162 (49.3%) subjects. Using multiple logistic regression analysis, successful agers had significantly lower co-morbidity scores (p 0.0001). Almost half of the individuals presented successful aging. Successful agers had less co-morbidity and a lower risk of falls or malnutrition, and they had higher scores on the QoL scale

The Series Bridge Converter (SBC): design of a compact modular multilevel converter for grid applications

This paper presents a novel hybrid modular multilevel voltage source converter suitable for grid applications. The proposed converter retains the advantages of other modular multilevel topologies and can be made more compact making it attractive for offshore stations and other footprint critical applications like city infeeds. In this paper, the basic operating principle and design criteria for the converter implementation are presented. The submodule capacitor requirements which have significant influence on the size of a converter station are also evaluated and compared to the MMC. The performance of the converter is supported by simulation results from a representative medium voltage scaled demonstrator

Movilidad ascendente de la inmigración en España : ¿asimilación o segmentación ocupacional?

Background of INCASI Project H2020-MSCA-RISE-2015 GA 691004. WP1: CompilationLa posibilidad de movilidad ascendente de la población inmigrante es un factor importante a la hora de explicar su integración social. Asimismo, a nivel individual, la expectativa de movilidad puede contribuir a aumentar o disminuir la incertidumbre socioeconómica. El objetivo de este artículo es analizar la movilidad ocupacional vertical de la inmigración. Tratamos de explicar cuales son las variables clave en el acceso de los inmigrantes a los salarios altos. Una regresión logística nos permite ver como interactúan las variables individuales, como la antigüedad y el nivel de estudios, con las variables estructurales, como el tamaño de la empresa y el sector de actividad. Además, un análisis factorial de correspondencias múltiples nos permite agrupar todas las variables y ofrecer una tipología que clasifica las trayectorias laborales con arreglo a la segmentación del mercado de trabajo.Possibilities for occupational mobility are an important factor in the explanation of the integration of immigrant workers into receiving societies. Moreover, at the individual level, the prospects for upward occupational mobility determine the uncertainty facing immigrant workers. In this paper, we examine the upward occupational mobility of immigrant workers in Spain. We attempt to explain the key variables determining immigrants' access to high wages. A multinomial logistic regression examines the interaction between individual variables such as age and education level, and structural variables such as company size and sector. In addition, a factor analysis allows us to group these variables into a typology that classifies career paths according to labour market segmentation

Utility of geriatric assessment to predict mortality in the oldest old: the Octabaix Study 3-year follow-up

Objective: Few studies have prospectively evaluated the utility of geriatric assessment tools as predictors of mortality in the oldest population. We investigated predictors of death in an oldest-old cohort after 3 years of follow-up. Methods: The Octabaix study is a prospective, community-based study with a follow-up period of 3 years involving 328 subjects aged 85 at baseline. Data were collected on functional and cognitive status, co-morbidity, nutritional and falls risk, quality of life, social risk, and long-term drug prescription. Vital status for the total cohort was evaluated after 3 years of follow-up. Results: Mortality after 3 years was 17.3%. Patients who did not survive had significantly poorer baseline functional status for basic and instrumental activities of daily living (Barthel and Lawton Index), higher co-morbidity (Charlson), higher nutritional risk (Mini Nutritional Assessment), higher risk of falls (Tinetti Gait Scale), poor quality of life (visual analog scale of the Quality of Life Test), and higher number of chronic drugs prescribed. Cox regression analysis identified the Lawton Index (hazard ratio [HR] 0.82, 95% confidence interval [CI] 0.73-0.89) and the number of chronic drugs prescribed (HR 1.09, 95% CI 1.01-1.18) as independent predictors of mortality at 3 years. Conclusions: Among the variables studied, the ability to perform instrumental activities of daily living and using few drugs on a chronic basis at baseline are the best predictors of which oldest-old community-dwelling subjects survive after a 3-year follow-up period

Red Blood Cell Distribution Width as a Prognostic Factor of Mortality in Elderly Patients Firstly Hospitalized Due to Heart Failure

BACKGROUND: Red blood cell distribution width (RDW) is a risk factor related to adverse outcome in patients with heart failure (HF). Less is known about its role in patients in their first hospitalization for HF.AIMSOur objective was to investigate the prognostic role of RDW in elderly patients hospitalized for acute HF for the first time. METHODS: We reviewed all patients aged 65 years or older admitted to a tertiary-care university hospital with a main diagnosis of acute HF during a 2-year period ( January 2013 to December 2014). Patients were divided into 2 groups according to admission RDW values (<15% or ≥15%). RESULTS: A total of 897 patients were included in the study. Mean (SD) age was 80.25 (7.6) years. Admission RDW was 15% or higher in 474 patients (52.8%), with a mean (SD) RDW of 15.5% (2.3%). Multivariable analysis confirmed the relationship between a higher RDW on admission and a previous diagnostic history of diabetes and higher serum sodium concentrations on admission. All -cause mortality was higher among patients with RDW of 15% or more at 1 year follow -up (29.6% vs 23.2%, P = 0.03). Multivariate analysis confirmed the association between RDW and higher risk of 1-year mortality, as well as with older age, higher Charlson comorbidity index, higher potassium serum concentrations, and no hypertension as a previous diagnosis. CONCLUSIONS: In elderly patients experiencing their first admission due to acute HF, a higher RDW at baseline might help identify those at higher risk for 1-year all -cause mortality

Effort Oxygen Saturation and Effort Heart Rate to Detect Exacerbations of Chronic Obstructive Pulmonary Disease or Congestive Heart Failure

Background: current algorithms for the detection of heart failure (HF) and chronic obstructive pulmonary disease (COPD) exacerbations have poor performance. Methods: this study was designed as a prospective longitudinal trial. Physiological parameters were evaluated at rest and effort (walking) in patients who were in the exacerbation or stable phases of HF or COPD. Parameters with relevant discriminatory power (sensitivity (Sn) or specificity (Sp) 80%, and Youden index 0.2) were integrated into diagnostic algorithms. Results: the study included 127 patients (COPD: 56, HF: 54, both: 17). The best algorithm for COPD included: oxygen saturation (SaO(2)) decrease 2% in minutes 1 to 3 of effort, end-of-effort heart rate (HR) increase 10 beats/min and walking distance decrease 35 m (presence of one criterion showed Sn: 0.90 (95%, CI(confidence interval): 0.75-0.97), Sp: 0.89 (95%, CI: 0.72-0.96), and area under the curve (AUC): 0.92 (95%, CI: 0.85-0.995)); and for HF: SaO(2) decrease 2% in the mean-of-effort, HR increase 10 beats/min in the mean-of-effort, and walking distance decrease 40 m (presence of one criterion showed Sn: 0.85 (95%, CI: 0.69-0.93), Sp: 0.75 (95%, CI: 0.57-0.87) and AUC 0.84 (95%, CI: 0.74-0.94)). Conclusions: effort situations improve the validity of physiological parameters for detection of HF and COPD exacerbation episodes

Machine learning for the development of diagnostic models of decompensated heart failure or exacerbation of chronic obstructive pulmonary disease

Heart failure (HF) and chronic obstructive pulmonary disease (COPD) are two chronic diseases with the greatest adverse impact on the general population, and early detection of their decompensation is an important objective. However, very few diagnostic models have achieved adequate diagnostic performance. The aim of this trial was to develop diagnostic models of decompensated heart failure or COPD exacerbation with machine learning techniques based on physiological parameters. A total of 135 patients hospitalized for decompensated heart failure and/or COPD exacerbation were recruited. Each patient underwent three evaluations: one in the decompensated phase (during hospital admission) and two more consecutively in the compensated phase (at home, 30 days after discharge). In each evaluation, heart rate (HR) and oxygen saturation (Ox) were recorded continuously (with a pulse oximeter) during a period of walking for 6 min, followed by a recovery period of 4 min. To develop the diagnostic models, predictive characteristics related to HR and Ox were initially selected through classification algorithms. Potential predictors included age, sex and baseline disease (heart failure or COPD). Next, diagnostic classification models (compensated vs. decompensated phase) were developed through different machine learning techniques. The diagnostic performance of the developed models was evaluated according to sensitivity (S), specificity (E) and accuracy (A). Data from 22 patients with decompensated heart failure, 25 with COPD exacerbation and 13 with both decompensated pathologies were included in the analyses. Of the 96 characteristics of HR and Ox initially evaluated, 19 were selected. Age, sex and baseline disease did not provide greater discriminative power to the models. The techniques with S and E values above 80% were the logistic regression (S: 80.83%; E: 86.25%; A: 83.61%) and support vector machine (S: 81.67%; E: 85%; A: 82.78%) techniques. The diagnostic models developed achieved good diagnostic performance for decompensated HF or COPD exacerbation. To our knowledge, this study is the first to report diagnostic models of decompensation potentially applicable to both COPD and HF patients. However, these results are preliminary and warrant further investigation to be confirmed