Valoración fisiológica del ejercicio físico en medicina del trabajo

Inclou referències bibliogràfique

Utilización de patrones de estacionalidad e impactos de variables con retardo en el tiempo para la planificación de los nacimientos en sistemas vacunos lecheros.

Con el objetivo de demostrar la posibilidad de utilizar los patrones de comportamiento estacional de las variables con retardos en el tiempo para planificar la mejor época del año para concentrar los partos, se recolectaron todos los boletines mensuales de reproducción correspondientes a las empresas de la cuenca lechera Camagüey-Jimaguayú con las variables año (1982 a 2005), mes (enero a diciembre), hembras inseminadas pendientes a diagnóstico de gestación, hembras recentinas, hembras vacías, incorporaciones a la reproducción, desechos de la reproducción, hembras detectadas en el primer estro, hembras detectadas en total de estros, hembras gestantes en el diagnóstico, hembras no gestantes en el diagnóstico y total de nacimientos. Se realizó el proceso descomposición estacional y el cruce bivariado de las combinaciones entre todas las series en estudio mediante la función de correlación cruzada de series cronológicas utilizando retardos de hasta 24 meses. Fueron determinadas las relaciones de interdependencia de las variables con retardos, mediante la técnica SEM (modelación de ecuaciones estruc-turales). El modelo estructural obtenido, partiendo de un enfoque global utilizando los patrones de comportamiento estacional y las relaciones de dependencia en el tiempo, permitió la planificación de laépoca de los nacimientos mediante la optimización en los escalones precedentes de la variable con mayor impacto en el sistema (RECTOT 10).Using Seasonality Patterns and Time-Lagged Variables Impact for Birth Planning in Dairy Farm-ing SystemABSTRACTThe current study demonstrates the possibility of using seasonal performance patterns derived from time-lagged variables to devise a plan dealing with seasonal calving herds. To this end, data were collected from every monthly bulletin on reproduction from livestock centers in Camagüey-Jimaguayú dairy basin using the following variables: year (1982-2005), month (January-December), inseminated heifers without undergoing a pregnancy diagnosis process, puerperal heifers, non-pregnant heifers, incorporations to reproduction, culled heifers, heifers at first estrus, heifers at total estrus, heifers diagnosed as pregnant, heifers diagnosed as non-pregnant, and total of births. The seasonal de-tached procedure and bivariate crossing of combinations among all the assessed series were performed by crossed correlations of chronological series with lags scored up to 24 months. Lagged variables interdependence relations were determine by the SEM technique (structural equation models). An initial global approach including seasonal performance and time dependent relations was the starting point to find out the structural model to be implemented. This model was useful in planning seasonal births aided by RECTOT 10 software that optimized the highest impact variable

Prevalence and prognostic implications of myocardial injury across different waves of COVID-19

IntroductionThe prognostic ability of myocardial injury across different waves of the COVID-19 pandemic is not well established. The purpose of this study was to evaluate the prevalence and prognostic implications of myocardial injury in the first and sixth wave of COVID-19.MethodsWe conducted a retrospective observational study that included patients admitted to the emergency department with COVID-19 with data on concentrations of cardiac troponin during the first and sixth wave. We compared the prevalence of myocardial injury and its predictive capacity for 30-day all-cause death in both waves.Results and discussionA total of 346 patients were included (1st wave 199 and 6th wave 147 patients). The prevalence of myocardial injury was 21% with non-significant differences between waves. Myocardial injury was associated, in both waves, with a higher prevalence of comorbidities and with an increased risk of 30-day all-cause death [1st wave HR: 3.73 (1.84–7.55); p < 0.001 and 6th wave HR: 3.13 (1.23–7.92); p = 0.016], with non-significant differences in predictive capacity between groups after ROC curve analysis [AUC: 1st wave 0.829 (95% CI: 0.764–0.895) and 6th wave 0.794 (95% CI: 0.711–0.876)]. As limitations, this is a retrospective study with a relatively small simple size and troponin assay was performed at the discretion of the emergency physician so selection bias could be present. In conclusion, the prevalence of myocardial injury and its prognostic capacity was similar in both waves despite vaccination programs. Myocardial injury predicts short-term mortality in all COVID-19 patients, so they should be treated intensively

Constructing bilayer and volumetric atrial models at scale.

To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk)

CALYPSO 2019 Cruise Report: field campaign in the Mediterranean

This cruise aimed to identify transport pathways from the surface into the interior ocean during the late winter in the Alborán sea between the Strait of Gibraltar (5°40’W) and the prime meridian. Theory and previous observations indicated that these pathways likely originated at strong fronts, such as the one that separates salty Mediterranean water and the fresher water in owing from the Atlantic. Our goal was to map such pathways and quantify their transport. Since the outcropping isopycnals at the front extend to the deepest depths during the late winter, we planned the cruise at the end of the Spring, prior to the onset of thermal stratification of the surface mixed layer.Funding was provided by the Office of Naval Research under Contract No. N000141613130

Table1_Prevalence and prognostic implications of myocardial injury across different waves of COVID-19.docx

IntroductionThe prognostic ability of myocardial injury across different waves of the COVID-19 pandemic is not well established. The purpose of this study was to evaluate the prevalence and prognostic implications of myocardial injury in the first and sixth wave of COVID-19.MethodsWe conducted a retrospective observational study that included patients admitted to the emergency department with COVID-19 with data on concentrations of cardiac troponin during the first and sixth wave. We compared the prevalence of myocardial injury and its predictive capacity for 30-day all-cause death in both waves.Results and discussionA total of 346 patients were included (1st wave 199 and 6th wave 147 patients). The prevalence of myocardial injury was 21% with non-significant differences between waves. Myocardial injury was associated, in both waves, with a higher prevalence of comorbidities and with an increased risk of 30-day all-cause death [1st wave HR: 3.73 (1.84–7.55); p < 0.001 and 6th wave HR: 3.13 (1.23–7.92); p = 0.016], with non-significant differences in predictive capacity between groups after ROC curve analysis [AUC: 1st wave 0.829 (95% CI: 0.764–0.895) and 6th wave 0.794 (95% CI: 0.711–0.876)]. As limitations, this is a retrospective study with a relatively small simple size and troponin assay was performed at the discretion of the emergency physician so selection bias could be present. In conclusion, the prevalence of myocardial injury and its prognostic capacity was similar in both waves despite vaccination programs. Myocardial injury predicts short-term mortality in all COVID-19 patients, so they should be treated intensively.</p