Ensayos de caracterización del comportamiento frente al agua de la piedra natural

This paper presents an experimental analysis of the stone behaviour in contact with water in the different construction uses. In any of these cases is analyse how the water penetrates into the material. As a result of the study the need of modification of the UNE test standards is concluded. It is proposed a procedure to determinate the material's properties and a method to compare and analyse the result obtained that keep into consideration the climate factors. The method have been applied to sandstone of Villamayor (Spain) showing its utility in the analysis of the stone properties.Se expone la necesidad de revisión de las normas UNE de ensayo para la determinación del comportamiento frente al agua de las rocas porosas teniendo en cuenta las formas de exposición que suponen las distintas aplicaciones constructivas y los mecanismos de penetración del agua que en cada caso operan. Se propone para ello una sistemática de ensayos y un método comparado de análisis de resultados basado en la consideración de los factores climatológicos. La utilidad del método se ilustra con un ejemplo de aplicación al estudio de la Arenisca de Villamayo

Método de análisis para determinar el contenido de humedad adecuado para la obtención de resistencias en fachadas trasventiladas de piedra natural sometidas al agua de lluvia.

El artículo muestra la influencia que tiene la consideración del contenido de humedad en el diseño de las fachadas trasventiladas hechas de piedra natural porosa. Se comprueba cómo este factor influye en la resistencia de las placas y condiciona sus dimensiones. Por ello se propone realizar un análisis más amplio del comportamiento frente al agua, que el propuesto por las normas EN. A través de un ejemplo, se muestra cómo realizar dicho análisis y se dan pautas para elegir un contenido de humedad que represente el grado de absorción que la piedra pueda alcanzar en este tipo de fachadas. Con este contenido, se determinarán las resistencias mecánicas de las placas. El estudio se ha aplicado a tres areniscas de la misma zona del noreste español, obteniendo resultados que demuestran la utilidad del análisis que se propon

Retrospective cohort analysis of Spanish national trends of coronary artery bypass grafting and percutaneous coronary intervention from 1998 to 2017

Introduction Spain is one of the countries with the lowest rates of revascularisation and highest ratio of percutaneous coronary intervention (PCI) to coronary artery bypass grafting (CABG). Objectives To investigate the changes and trends in the two revascularisation procedures between 1998 and 2017 in Spain. Design Retrospective cohort study. Analysis of in-hospital outcomes. Setting Minimum basic data set from the Spanish National Department of Health: mandatory database collecting information of patients who are attended in the Spanish public National Health System. Participants 603 976 patients who underwent isolated CABG or PCI in the Spanish National Health System. The study period was divided in four 5-year intervals. Patients with acute myocardial infarction on admission were excluded. Primary and secondary outcomes We investigated the volume of procedures nationwide, the changes of the risk profile of patients and in-hospital mortality of both techniques. Results We observed a 2.2-fold increase in the rate of any type of myocardial revascularisation per million inhabitants-year: 357 (1998) to 776 (2017). 93 682 (15.5%) had a coronary surgery. PCI to CABG ratio rose from 2.2 (1998-2002) to 8.1 (2013-2017). Charlson's index increased by 0.8 for CABG and 1 for PCI. The median annual volume of PCI/hospital augmented from 136 to 232, while the volume of CABG was reduced from 137 to 74. In the two decades, we detected a significant reduction of CABG in-hospital mortality (6.5% vs 2.6%, p<0.001) and a small increase in PCI (1.2% vs 1.5%, p<0.001). Risk adjusted mortality rate was reduced for both CABG (1.51 vs 0.48, p<0.001), and PCI (1.42 vs 1.05, p<0.001). Conclusion We detected a significant increase in the volume of revascularisations (particularly PCI) in Spain. Risk-adjusted in-hospital mortality was significantly reduce

Detection of cytomegalovirus in bronchoalveolar lavage fluid from immunocompromised patients with pneumonitis by viral culture and DNA quantification

Altres ajuts: acords transformatius de la UABTo compare the detection of human cytomegalovirus (HCMV) in bronchoalveolar lavage (BAL) fluid by viral culture and quantitative polymerase chain reaction (qPCR), and to establish a viral load threshold that can identify cases of HCMV replication indicative of pneumonitis. There is currently no universal viral load cut-off to differentiate between patients with and without pneumonitis, and the interpretation of qPCR results is challenging. 176 consecutive BAL samples from immunosuppressed hosts with signs and/or symptoms of respiratory infection were prospectively studied by viral culture and qPCR. Concordant results were obtained in 81.25% of the BAL samples. The rest were discordant, as only 34% of the qPCR-positive BAL samples were positive by culture. The median HCMV load was significantly higher in culture-positive than in culture-negative BAL samples (5038 vs 178 IU/mL). Using a cut-off value of 1258 IU/mL of HCMV in BAL, pneumonia was diagnosed with a sensitivity of 76%, a specificity of 100%, a VPP of 100% and VPN of 98%, and HCMV was isolated in 100% of the BAL cultures. We found that a qPCR-negative was a quick and reliable way of ruling out HCMV pneumonitis, but a positive result did not always indicate clinically significant replication in the lung. However, an HCMV load in BAL fluid of ≥ 1258 IU/mL was always associated with disease, whereas < 200 IU/mL rarely so

Molecular epidemiology of an enterovirus A71 outbreak associated with severe neurological disease, Spain, 2016

IntroductionEnterovirus A71 (EV-A71) is an emerging pathogen that causes a wide range of disorders including severe neurological manifestations. In the past 20 years, this virus has been associated with large outbreaks of hand, foot and mouth disease with neurological complications in the Asia-Pacific region, while in Europe mainly sporadic cases have been reported. In spring 2016, however, an EV-A71 outbreak associated with severe neurological cases was reported in Catalonia and spread further to other Spanish regions.AimOur objective was to investigate the epidemiology and clinical characteristics of the outbreak.MethodsWe carried out a retrospective study which included 233 EV-A71-positive samples collected during 2016 from hospitalised patients. We analysed the clinical manifestations associated with EV-A71 infections and performed phylogenetic analyses of the 3'-VP1 and 3Dpol regions from all Spanish strains and a set of EV-A71 from other countries.ResultsMost EV-A71 infections were reported in children (mean age: 2.6 years) and the highest incidence was between May and July 2016 (83%). Most isolates (218/233) were classified as subgenogroup C1 and 217 of them were grouped in one cluster phylogenetically related to a new recombinant variant strain associated with severe neurological diseases in Germany and France in 2015 and 2016. Moreover, we found a clear association of EV-A71-C1 infection with severe neurological disorders, brainstem encephalitis being the most commonly reported.ConclusionAn emerging recombinant variant of EV-A71-C1 was responsible for the large outbreak in 2016 in Spain that was associated with many severe neurological cases.S

Molecular epidemiology of an enterovirus A71 outbreak associated with severe neurological disease, Spain, 2016

Altres ajuts: We wish to thank I Bustillo, H del Pozo and P Higueras for their technical assistance. We also sincerely wish to thank all technical staff from microbiology departments and medical staff from paediatrics departments from all participating hospitals. Some of the samples are included in an ongoing project (PI15CIII-00020) which was supported by a grant by the Health Research System (AES).Introduction: Enterovirus A71 (EV-A71) is an emerging pathogen that causes a wide range of disorders including severe neurological manifestations. In the past 20 years, this virus has been associated with large outbreaks of hand, foot and mouth disease with neurological complications in the Asia-Pacific region, while in Europe mainly sporadic cases have been reported. In spring 2016, however, an EV-A71 outbreak associated with severe neurological cases was reported in Catalonia and spread further to other Spanish regions. Aim: Our objective was to investigate the epidemiology and clinical characteristics of the outbreak. Methods: We carried out a retrospective study which included 233 EV-A71-positive samples collected during 2016 from hospitalised patients. We analysed the clinical manifestations associated with EV-A71 infections and performed phylogenetic analyses of the 3'-VP1 and 3Dpol regions from all Spanish strains and a set of EV-A71 from other countries. Results: Most EV-A71 infections were reported in children (mean age: 2.6 years) and the highest incidence was between May and July 2016 (83%). Most isolates (218/233) were classified as subgenogroup C1 and 217 of them were grouped in one cluster phylogenetically related to a new recombinant variant strain associated with severe neurological diseases in Germany and France in 2015 and 2016. Moreover, we found a clear association of EV-A71-C1 infection with severe neurological disorders, brainstem encephalitis being the most commonly reported. Conclusion: An emerging recombinant variant of EV-A71-C1 was responsible for the large outbreak in 2016 in Spain that was associated with many severe neurological cases

Re-emergence of enterovirus D68 in Europe after easing the COVID-19 lockdown, September 2021

We report a rapid increase in enterovirus D68 (EV-D68) infections, with 139 cases reported from eight European countries between 31 July and 14 October 2021. This upsurge is in line with the seasonality of EV-D68 and was presumably stimulated by the widespread reopening after COVID-19 lockdown. Most cases were identified in September, but more are to be expected in the coming months. Reinforcement of clinical awareness, diagnostic capacities and surveillance of EV-D68 is urgently needed in Europe.Peer Reviewe

Role of age and comorbidities in mortality of patients with infective endocarditis

Purpose: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. Methods: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015. Patients were stratified into three age groups:<65 years, 65 to 80 years, and = 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. Results: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 = 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients =80 years who underwent surgery were significantly lower compared with other age groups (14.3%, 65 years; 20.5%, 65-79 years; 31.3%, =80 years). In-hospital mortality was lower in the <65-year group (20.3%, <65 years;30.1%, 65-79 years;34.7%, =80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%, =80 years; p = 0.003).Independent predictors of mortality were age = 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI = 3 (HR:1.62; 95% CI:1.39–1.88), and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared, the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. Conclusion: There were no differences in the clinical presentation of IE between the groups. Age = 80 years, high comorbidity (measured by CCI), and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT

The main objective of this work is to develop and evaluate an artificial intelligence system based on deep learning capable of automatically identifying, quantifying, and characterizing COVID-19 pneumonia patterns in order to assess disease severity and predict clinical outcomes, and to compare the prediction performance with respect to human reader severity assessment and whole lung radiomics. We propose a deep learning based scheme to automatically segment the different lesion subtypes in nonenhanced CT scans. The automatic lesion quantification was used to predict clinical outcomes. The proposed technique has been independently tested in a multicentric cohort of 103 patients, retrospectively collected between March and July of 2020. Segmentation of lesion subtypes was evaluated using both overlapping (Dice) and distance-based (Hausdorff and average surface) metrics, while the proposed system to predict clinically relevant outcomes was assessed using the area under the curve (AUC). Additionally, other metrics including sensitivity, specificity, positive predictive value and negative predictive value were estimated. 95% confidence intervals were properly calculated. The agreement between the automatic estimate of parenchymal damage (%) and the radiologists' severity scoring was strong, with a Spearman correlation coefficient (R) of 0.83. The automatic quantification of lesion subtypes was able to predict patient mortality, admission to the Intensive Care Units (ICU) and need for mechanical ventilation with an AUC of 0.87, 0.73 and 0.68 respectively. The proposed artificial intelligence system enabled a better prediction of those clinically relevant outcomes when compared to the radiologists' interpretation and to whole lung radiomics. In conclusion, deep learning lesion subtyping in COVID-19 pneumonia from noncontrast chest CT enables quantitative assessment of disease severity and better prediction of clinical outcomes with respect to whole lung radiomics or radiologists' severity score