Fracture experience among participants from the FROCAT study: what thresholding is appropriate using the FRAX tool?

ObjectiveTo perform an external validation of FRAX algorithm thresholds for reporting level of risk of fracture in Spanish women (low <5%; intermediate ?5% and <7.5%; high ?7.5%) taken from a prospective cohort “FRIDEX”.MethodsA retrospective study of 1090 women aged ?40 and ?90 years old obtained from the general population (FROCAT cohort). FRAX was calculated with data registered in 2002. All fractures were validated in 2012. Sensitivity analysis was performed.ResultsWhen analyzing the cohort (884) excluding current or past anti osteoporotic medication (AOM), using our nominated thresholds, among the 621 (70.2%) women at low risk of fracture, 5.2% [CI95%: 3.4–7.6] sustained a fragility fracture; among the 99 at intermediate risk, 12.1% [6.4–20.2]; and among the 164 defined as high risk, 15.9% [10.6–24.2]. Sensitivity analysis against model risk stratification FRIDEX of FRAX Spain shows no significant difference. By including 206 women with AOM, the sensitivity analysis shows no difference in the group of intermediate and high risk and minimal differences in the low risk group.ConclusionsOur findings support and validate the use of FRIDEX thresholds of FRAX when discussing the risk of fracture and the initiation of therapy with patients

Piecewise Approximate Bayesian Computation: fast inference for discretely observed Markov models using a factorised posterior distribution

Many modern statistical applications involve inference for complicated stochastic models for which the likelihood function is difficult or even impossible to calculate, and hence conventional likelihood-based inferential techniques cannot be used. In such settings, Bayesian inference can be performed using Approximate Bayesian Computation (ABC). However, in spite of many recent developments to ABC methodology, in many applications the computational cost of ABC necessitates the choice of summary statistics and tolerances that can potentially severely bias the estimate of the posterior. We propose a new “piecewise” ABC approach suitable for discretely observed Markov models that involves writing the posterior density of the parameters as a product of factors, each a function of only a subset of the data, and then using ABC within each factor. The approach has the advantage of side-stepping the need to choose a summary statistic and it enables a stringent tolerance to be set, making the posterior “less approximate”. We investigate two methods for estimating the posterior density based on ABC samples for each of the factors: the first is to use a Gaussian approximation for each factor, and the second is to use a kernel density estimate. Both methods have their merits. The Gaussian approximation is simple, fast, and probably adequate for many applications. On the other hand, using instead a kernel density estimate has the benefit of consistently estimating the true piecewise ABC posterior as the number of ABC samples tends to infinity. We illustrate the piecewise ABC approach with four examples; in each case, the approach offers fast and accurate inference

La educación inclusiva frente a las desigualdades sociales: un estado de la cuestion y algunas reflexiones geograficas

Este artículo establece un estado de la cuestión e la educación inclusiva en el mundo y sugiere algunas reflexiones al respecto. El primer apartado recuerda las conexiones ineludibles entre las preocupaciones educativas por la educación inclusiva y las preocupaciones más generales por la desigualdad. El segundo consigna los criterios de búsqueda de las publicaciones académicas, y observa dos grandes temas en sus contenidos: sobre todo, el cambio interno de las escuelas atrae las miradas, pero en segundo plano también el entorno territorial despierta algunas inquietudes. El tercero anota los criterios de búsqueda de la documentación del Banco Mundial, la OCDE y la UNESCO. En este ámbito los simposios de la Oficina Internacional de la Educación de UNESCO revelan una interpretación dispar, aunque convergente, del concepto de educación inclusiva en las distintas regiones mundiales. Asimismo, todas las publicaciones oficiales muestran una atención prioritaria a las dinámicas internas de las escuelas, puesto que apenas algunas esbozan ciertas relaciones entre la educación inclusiva y las políticas públicas. El último apartado adelanta varios argumentos a favor de una mayor consideración de las escalas local y estatal de la educación inclusiva. Las principales razones para atender a la dimensión local provienen de la causalidad acumulativa de las privaciones sociales, de la necesidad de articular la acción de las escuelas y de la posibilidad de abrir un espacio significativo para la participación ciudadana. Asimismo, las principales razones para atender a la dimensión estatal surgen de las posibles sinergias entre la educación inclusiva y la expansión educativa (p. ej. ¿es correlativo el avance de la escolarización en los distintos ciclos escolares?) como también entre la educación inclusiva y la protección social (p. ej. ¿tienen una implicación pedagógica consistente las abundantes condiciones educativas de las transferencias sociales?

Usage of a cardiology service associated to a private health insurance in Spain (2019-2022)

This synthetic dataset includes the number of visits to a cardiology service associated to a private health insurance per policyholder (column "Visits") in each year of the period 2019-2022. Each row represent a policyholder, and the dataset includes their sex (column "Sex", 0 means female and 1 means male), age group (column "Age", 0 means under 60 and 1 means over 60 years old) and year (column "Year", within the period 2019-2022). As policyholders with no visits in the period were not included in the original dataset, the zeros were synthetically generated by means of a zero-truncated Poisson model, accounting for age category, sex and year. The code used to generate these zeros can be found in https://github.com/dmorinya/BSTS_HealthInsurance (script poisson_cross_sectional_Cardio.R), although the original dataset is not available due to privacy issues. The policy numbers in this dataset (column "Policy") are randomly generated (although the same policy number corresponds to the same policyholder)

Analysis of the impact of lockdown on the reproduction number of the SARS-Cov-2 in Spain [Análisis del impacto del confinamiento en el número de reproducción del SARS-Cov-2 en España]

Objective: The late 2019 COVID-19 outbreak has put the health systems of many countries to the limit of their capacity. The most affected European countries are, so far, Italy and Spain. In both countries (and others), the authorities decreed a lockdown, with local specificities. The objective of this work is to evaluate the impact of the measures undertaken in Spain to deal with the pandemic. Method: We estimated the number of cases and the impact of lockdown on the reproducibility number based on the hospitalization reports up to April 15th 2020. Results: The estimated number of cases shows a sharp increase until the lockdown, followed by a slowing down and then a decrease after full quarantine was implemented. Differences in the basic reproduction ratio are also significant, dropping from 5.89 (95% confidence interval [95%CI]: 5.46-7.09) before the lockdown to 0.48 (95%CI: 0.15-1.17) afterwards. Conclusions: Handling a pandemic like COVID-19 is complex and requires quick decision making. The large differences found in the speed of propagation of the disease show us that being able to implement interventions at the earliest stage is crucial to minimise the impact of a potential infectious threat. Our work also stresses the importance of reliable up to date epidemiological data in order to accurately assess the impact of Public Health policies on viral outbreak. © 2020 SESPA

Usage of a cardiology service associated to a private health insurance in Spain (2019-2022)

This synthetic dataset includes the number of visits to a cardiology service associated to a private health insurance per policyholder (column "Visits") in each year of the period 2019-2022. Each row represent a policyholder, and the dataset includes their sex (column "Sex", 0 means female and 1 means male), age group (column "Age", 0 means under 60 and 1 means over 60 years old) and year (column "Year", within the period 2019-2022). As policyholders with no visits in the period were not included in the original dataset, the zeros were synthetically generated by means of a zero-truncated Poisson model, accounting for age category, sex and year. The code used to generate these zeros can be found in https://github.com/dmorinya/BSTS_HealthInsurance (script poisson_cross_sectional_Cardio.R), although the original dataset is not available due to privacy issues. The policy numbers in this dataset (column "Policy") are randomly generated (although the same policy number corresponds to the same policyholder).THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Probability estimation of a Carrington-like geomagnetic storm

Intense geomagnetic storms can cause severe damage to electrical systems and communications. This work proposes a counting process with Weibull inter-occurrence times in order to estimate the probability of extreme geomagnetic events. It is found that the scale parameter of the inter-occurrence time distribution grows exponentially with the absolute value of the intensity threshold defining the storm, whereas the shape parameter keeps rather constant. The model is able to forecast the probability of occurrence of an event for a given intensity threshold; in particular, the probability of occurrence on the next decade of an extreme event of a magnitude comparable or larger than the well-known Carrington event of 1859 is explored, and estimated to be between 0.46% and 1.88% (with a 95% confidence), a much lower value than those reported in the existing literature. © 2019, The Author(s)

Fitting tails by the empirical residual coefficient of variation: The ercv Package

This article is a self-contained introduction to the R package ercv and to the methodology on which it is based through the analysis of nine examples. The methodology is simple and trustworthy for the analysis of extreme values and relates the two main existing methodologies. The package contains R functions for visualizing, fitting and validating the distribution of tails. It also provides multiple threshold tests for a generalized Pareto distribution, together with an automatic threshold selection algorithm. © 2020, Technische Universitaet Wien

Estimating the real burden of disease under a pandemic situation: The SARS-CoV2 case

The present paper introduces a new model used to study and analyse the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) epidemic-reported-data from Spain. This is a Hidden Markov Model whose hidden layer is a regeneration process with Poisson immigration, Po-INAR(1), together with a mechanism that allows the estimation of the under-reporting in non-stationary count time series. A novelty of the model is that the expectation of the unobserved processs innovations is a time-dependent function defined in such a way that information about the spread of an epidemic, as modelled through a Susceptible-Infectious-Removed dynamical system, is incorporated into the model. In addition, the parameter controlling the intensity of the under-reporting is also made to vary with time to adjust to possible seasonality or trend in the data. Maximum likelihood methods are used to estimate the parameters of the model. © 2020 Fernández-Fontelo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

InterCardioRisk: a novel online tool for estimating doses of ionising radiation to occupationally-exposed medical staff and their associated health risks.

Those working in interventional cardiology and related medical procedures are potentially subject to considerable exposure to x-rays. Two types of tissue of particular concern that may receive considerable doses during such procedures are the lens of the eye and the brain. Ocular radiation exposure results in lens changes that, with time, may progress to partial or total lens opacification (cataracts). In the early stages, such opacities do not result in visual disability; the severity of such changes tends to increase progressively with dose and time until vision is impaired and cataract surgery is required. Scattered radiation doses to the eye lens of an interventional cardiologist in typical working conditions can exceed 34 μGy min(-1) in high-dose fluoroscopy modes and 3 μGy per image during image acquisition (instantaneous rate values) when radiation protection tools are not used. A causal relation between exposure to ionising radiation and increased risk of brain and central nervous system tumours has been shown in a number of studies. Although absorbed doses to the brain in interventional cardiology procedures are lower than those to the eye lens by a factor between 3.40 and 8.08 according to our simulations, doses to both tissues are among the highest occupational radiation doses documented for medical staff whose work involves exposures to x-rays. We present InterCardioRisk, a tool featuring an easy-to-use web interface that provides a general estimation of both cumulated absorbed doses experienced by medical staff exposed in the interventional cardiology setting and their estimated associated health risks. The tool is available at http://intercardiorisk.creal.cat