14 resultados para Asthma severity

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Public authorities and road users alike are increasingly concerned by recent trends in road safety outcomes in Barcelona, which is the European city with the highest number of registered Powered Two-Wheel (PTW) vehicles per inhabitant,. In this study we explore the determinants of motorcycle and moped accident severity in a large urban area, drawing on Barcelona’s local police database (2002-2008). We apply non-parametric regression techniques to characterize PTW accidents and parametric methods to investigate the factors influencing their severity. Our results show that PTW accident victims are more vulnerable, showing greater degrees of accident severity, than other traffic victims. Speed violations and alcohol consumption provide the worst health outcomes. Demographic and environment-related risk factors, in addition to helmet use, play an important role in determining accident severity. Thus, this study furthers our understanding of the most vulnerable vehicle types, while our results have direct implications for local policy makers in their fight to reduce the severity of PTW accidents in large urban areas.

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We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

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This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described

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Estudio descriptivo transversal llevado a cabo en un centro urbano de atención primaria, con una muestra de 250 asmáticos, de entre 536 registrados en el centro, que pretende estudiar su calidad de vida y su relación con diferentes variables (edad, sexo, tabaquismo, patologías crónicas más prevalentes, ansiedad y/o depresión, rinitis alérgica, tipo de asma y grado de control). Para ello se les aplicó el test Mini-AQLQ, que valora la calidad de vida en una escala del 1 al 7 (15 preguntas), donde 1 supone el mayor grado de discapacidad y 7 el mayor grado de autonomía.

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Importa si una guerra civil es combat com un conflicte irregular, convencional o simètric no convencional? En altres paraules, tenen les “tecnologies de la rebel·lió” un impacte sobre la gravetat d’una guerra, la seva durada o el seu resultat? Aquest treball mostra que els conflictes irregulars duren més que els altres tipus de conflicte, mentre els convencionals tendeixen a ser més greus en termes de letalitat al camp de batalla. D’altra banda, els conflictes irregulars tendeixen a ser guanyats pels governs, mentre els altres són més propensos a acabar en empat. Substancialment, aquests resultats ens ajuden a donar sentit a l’evolució de les guerres civils, les quals tendeixen a ser més curtes, més intenses i més difícils per als governs. Teòricament, aquests resultats donen suport a la importància de la tecnologia de rebel·lió a l’estudiar la gravetat, la durada i els resultats de les guerres civils; a més, contribueixen a una millor comprensió de la contribució històrica de la guerra irregular a la construcció de l’Estat i al canvi social.

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Our purpose is to determine the inflammatory changes in the airways of allergic paediatric asthma patients treated with omalizumab, measured by the percentage of eosinophils in induced sputum and exhaled nitric oxide (FENO). We observed a progressive and statistically significant decrease of eosinophil count in the induced sputum meanwhile FENO, although very sensible, was a less reproducible and thus a less reliable method to evaluate chronic airway inflammation in this population. Induced sputum seems to be a better method to monitor chronic inflammation and thus the response to chronic omalizumab treatment while FENO measurement would be more useful to monitor acute events preceding exacerbations.

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Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.

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Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections.

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Background: Development of three classification trees (CT) based on the CART (Classification and Regression Trees), CHAID (Chi-Square Automatic Interaction Detection) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR). Methods: Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%). Results: CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69- 75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)). Conclusion: With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.

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Background During the 2009 influenza pandemic, a change in the type of patients most often affected by influenza was observed. The objective of this study was to assess the role of individual and social determinants in hospitalizations due to influenza A (H1N1) 2009 infection. Methods We studied hospitalized patients (cases) and outpatients (controls) with confirmed influenza A (H1N1) 2009 infection. A standardized questionnaire was used to collect data. Variables that might be related to the hospitalization of influenza cases were compared by estimation of the odds ratio (OR) and 95% confidence intervals (CI) and the variables entered into binomial logistic regression models. Results Hospitalization due to pandemic A (H1N1) 2009 influenza virus infections was associated with non-Caucasian ethnicity (OR: 2.18, 95% CI 1.17 − 4.08), overcrowding (OR: 2.84, 95% CI 1.20 − 6.72), comorbidity and the lack of previous preventive information (OR: 2.69, 95% CI: 1.50 − 4.83). Secondary or higher education was associated with a lower risk of hospitalization (OR 0.56, 95% CI: 0.36 − 0.87) Conclusions In addition to individual factors such as comorbidity, other factors such as educational level, ethnicity or overcrowding were associated with hospitalization due to A (H1N1) 2009 influenza virus infections.

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Background To determine generic utilities for Spanish chronic obstructive pulmonary disease (COPD) patients stratified by different classifications: GOLD 2007, GOLD 2013, GesEPOC 2012 and BODEx index. Methods Multicentre, observational, cross-sectional study. Patients were aged ≥40 years, with spirometrically confirmed COPD. Utility values were derived from EQ-5D-3 L. Means, standard deviations (SD), medians and interquartile ranges (IQR) were computed based on the different classifications. Differences in median utilities between groups were assessed by non-parametric tests. Results 346 patients were included, of which 85.5% were male with a mean age of 67.9 (SD = 9.7) years and a mean duration of COPD of 7.6 (SD = 5.8) years; 80.3% were ex-smokers and the mean smoking history was 54.2 (SD = 33.2) pack-years. Median utilities (IQR) by GOLD 2007 were 0.87 (0.22) for moderate; 0.80 (0.26) for severe and 0.67 (0.42) for very-severe patients (p < 0.001 for all comparisons). Median utilities by GOLD 2013 were group A: 1.0 (0.09); group B: 0.87 (0.13); group C: 1.0 (0.16); group D: 0.74 (0.29); comparisons were statistically significant (p < 0.001) except A vs C. Median utilities by GesEPOC phenotypes were 0.84 (0.33) for non exacerbator; 0.80 (0.26) for COPD-asthma overlap; 0.71 (0.62) for exacerbator with emphysema; 0.72 (0.57) for exacerbator with chronic bronchitis (p < 0.001). Comparisons between patients with or without exacerbations and between patients with COPD-asthma overlap and exacerbator with chronic bronchitis were statistically-significant (p < 0.001). Median utilities by BODEx index were: group 02: 0.89 (0.20); group 34: 0.80 (0.27); group 56: 0.67 (0.29); group 79: 0.41 (0.31). All comparisons were significant (p < 0.001) except between groups 34 and 56. Conclusion Irrespective of the classification used utilities were associated to disease severity. Some clinical phenotypes were associated with worse utilities, probably related to a higher frequency of exacerbations. GOLD 2007 guidelines and BODEx index better discriminated patients with a worse health status than GOLD 2013 guidelines, while GOLD 2013 guidelines were better able to identify a smaller group of patients with the best health.

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Many European states apply score systems to evaluate the disability severity of non-fatal motor victims under the law of third-party liability. The score is a non-negative integer with an upper bound at 100 that increases with severity. It may be automatically converted into financial terms and thus also reflects the compensation cost for disability. In this paper, discrete regression models are applied to analyze the factors that influence the disability severity score of victims. Standard and zero-altered regression models are compared from two perspectives: an interpretation of the data generating process and the level of statistical fit. The results have implications for traffic safety policy decisions aimed at reducing accident severity. An application using data from Spain is provided.

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Bodily injury claims have the greatest impact on the claim costs of motor insurance companies. The disability severity of motor claims is assessed in numerous European countries by means of score systems. In this paper a zero inflated generalized Poisson regression model is implemented to estimate the disability severity score of victims in-volved in motor accidents on Spanish roads. We show that the injury severity estimates may be automatically converted into financial terms by insurers at any point of the claim handling process. As such, the methodology described may be used by motor insurers operating in the Spanish market to monitor the size of bodily injury claims. By using insurance data, various applications are presented in which the score estimate of disability severity is of value to insurers, either for computing the claim compensation or for claim reserve purposes.