Hipotiroidismo congénito: comparativa entre punto de partida y resultados finales

El despistaje del hipotiroidismo congénito se generalizó en España en la década de los 80 del siglo pasado. Basado en la determinación en papel de filtro de TSH, como en el resto de países europeos, llega ahora el momento de evaluar el impacto conseguido sobre la prevención de la subnormalidad. En el presente trabajo se contraponen dos experiencias: la del último año de screening en la Comunidad de Castilla y León con los pacientes hipotiroideos diagnosticados entre 1990-2002, que han alcanzado la madurez incipiente. Se analizan diferentes variables, como la edad del diagnóstico e inicio del tratamiento y se elabora una base de datos que podrá ser ampliada y completada en el futuro.Grado en Medicin

Predicting Clinical Outcome with Phenotypic Clusters in COVID-19 Pneumonia: An Analysis of 12,066 Hospitalized Patients from the Spanish Registry SEMI-COVID-19

(1) Background: Different clinical presentations in COVID-19 are described to date, from mild to severe cases. This study aims to identify different clinical phenotypes in COVID-19 pneumonia using cluster analysis and to assess the prognostic impact among identified clusters in such patients. (2) Methods: Cluster analysis including 11 phenotypic variables was performed in a large cohort of 12,066 COVID-19 patients, collected and followed-up from 1 March to 31 July 2020, from the nationwide Spanish Society of Internal Medicine (SEMI)-COVID-19 Registry. (3) Results: Of the total of 12,066 patients included in the study, most were males (7052, 58.5%) and Caucasian (10,635, 89.5%), with a mean age at diagnosis of 67 years (standard deviation (SD) 16). The main pre-admission comorbidities were arterial hypertension (6030, 50%), hyperlipidemia (4741, 39.4%) and diabetes mellitus (2309, 19.2%). The average number of days from COVID-19 symptom onset to hospital admission was 6.7 (SD 7). The triad of fever, cough, and dyspnea was present almost uniformly in all 4 clinical phenotypes identified by clustering. Cluster C1 (8737 patients, 72.4%) was the largest, and comprised patients with the triad alone. Cluster C2 (1196 patients, 9.9%) also presented with ageusia and anosmia; cluster C3 (880 patients, 7.3%) also had arthromyalgia, headache, and sore throat; and cluster C4 (1253 patients, 10.4%) also manifested with diarrhea, vomiting, and abdominal pain. Compared to each other, cluster C1 presented the highest in-hospital mortality (24.1% vs. 4.3% vs. 14.7% vs. 18.6%; p 20 bpm, lower PaO2/FiO2 at admission, higher levels of C-reactive protein (CRP) and lactate dehydrogenase (LDH), and the phenotypic cluster as independent factors for in-hospital death. (4) Conclusions: The present study identified 4 phenotypic clusters in patients with COVID-19 pneumonia, which predicted the in-hospital prognosis of clinical outcomes

Rationale and design of the Concordance study between FFR and iFR for the assessment of lesions in the left main coronary artery. The ILITRO-EPIC-07 Trial

Introduction and objectives: Patients with left main coronary artery (LMCA) stenosis have been excluded from the trials that support the non-inferiority of the instantaneous wave-free ratio (iFR) compared to the fractional flow reserve (FFR) in the decision-making process of coronary revascularization. This study proposes to prospectively assess the concordance between the two indices in LMCA lesions and to validate the iFR cut-off value of 0.89 for clinical use. Methods: National, prospective, and observational multicenter registry of 300 consecutive patients with intermediate lesions in the LMCA (angiographic stenosis, 25% to 60%. A pressure gudiewire study and determination of the RFF and the iFR will be performed: in the event of a negative concordant result (FFR > 0.80/iFR > 0.89), no treatment will be performed; in case of a positive concordant result (FFR 0.80/iFR 0.89), an intravascular echocardiography will be performed and revascularization will be delayed if the minimum lumen area is > 6 mm(2). The primary clinical endpoint will be a composite of cardiovascular death, LMCA lesion-related non-fatal infarction or need for revascularization of the LMCA lesion at 12 months. Conclusions: Confirm that an iFR-guided decision-making process in patients with intermediate LMCA stenosis is clinically safe and would have a significant clinical impact. Also, justify its systematic use when prescribing treatment in these potentially high-risk patients

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Cetoacidosis diabética como guía diagnóstica: Caso clínico

Resumen: La cetoacidosis diabética es una complicación de la diabetes mellitus que se da con más frecuencia en pacientescon DM tipo 1. Los factores desencadenantes pueden ser desde falta de adherencia al tratamiento a infecciones,siendo estas últimas las más frecuentes. Sin embargo, en ocasiones, detrás de esta situación subyacen problemasneoplásicos. La DM se asocia con diversas neoplasias, entre las que destaca, la neoplasia de páncreas. Abstract: Diabetic ketoacidosis is a complication of diabetes mellitus that occurs more frequently in patients with Type1 Diabetes Mellitus. The triggers can be from lack of adherence to treatment to infections, the latter beingthe most frequent. However, sometimes behind this situation lie neoplastic problems. DM is associated withvarious neoplasms, among which, the pancreatic neoplasm stands out. Palabras clave: Cetoacidosis diabética, Cáncer de páncreas, Keywords: Diabetic ketoacidosis: Pancreatic cance

Anales de Edafología y Agrobiología Tomo 35 Número 5-6

2019-08.- CopyBook.- Libnova.- Biblioteca ICA.Evolución de las propiedades física:; en suelos de prados naturales, por S. Cuadrado Sánchez y A. Blanco de Pablos (con la colaboración técnica de l. Hernández Pombero).-- Distribución y .características de los suelos canarios. Isla de La Palma, por J. J. Bravo Rodríguez, E. Fernández Caldas y F. Monturiol.-- Medida de la capacidad reductora de raíces de maíz, por F. Costa, A. M. Pujalte y O. Carpena.-- Estudios sobre la resistencia del castaño a la enfermedad de la «tinta». Efectos fungitóxicos de algunos compuestos fenólicos de C. mollisima, por M. R. Nimo y E. Vieitez.--Efectos de la evolución de diferentes fosfatos cálcicos sobre el crecimiento y el estado de nutrición del Rye-Grass, por C. Mazuelos, P. de Arambarri, L. Catalina y L. Madrid.-- Contribución al estudio de la capacidad total de cambio de suelos mediante diversos métodos analíticos, por J. A. Egido, A. García Rodríguez y J. F. Gallardo.-- Efecto de la utilización del azufre como fertilizante por vía foliar en judía, por C. Lluch, M. Gómez y J. Olivares.-- Tipos de suelos desarrollados sobre las serpentinas de la Sierra de Carratraca (Málaga), por A. García, M. Delgado y J. Aguilar.-- Uso de herbicidas en la implantación de praderas, por J. Segura, R. Fábregas y E. Vieitez.-- Carácter anfótero de la superficie del óxido de titanio (anatasa), por J. Contejo y H. P. Boehm.-- Estudios sobre la resistencia de Lolium perenne L. al Dalapón (2,2-dicloropropionato sódico). I. Efectos bajo las condiciones de campo, por J. Segura, E. Vieitez y R. Fábregas.-- Estudio de la adsorción de aminoácidos, péptidos y proteínas en minerales de arcilla, por M. l. Tellería.-- Real Decreto J361/1976, de 18 de junio, por el que se suprimen las SecretaríasGenerales de la División de Ciencias Matemáticas, Médicas y de la Naturaleza, y del Patronato de Investigación Científica y Técnica Juan de la Cierva, asumiendo sus funciones la Secretaría General del C. S. I. C.-- Real Decreto 1380/1976, de 18 de junio, por el que cesa don Octavio Carpena Artés como Secretario general del C. S. l. C.-- Real Decreto 1381/1976, de 18 de junio, por el que se nombra Secretario general del C. S. I. C. a don Jaime Suárez Alvarez.-- Nombramiento de Vicesecretarios del C. S. I. C.-- Nombramiento del Pro f. Lucena Conde.-- Nombramiento del Pro f. Rivas Goday.-- Nombramiento del Prof. Rivas-Martínez.- Cese del Vicedirector de la Estación Experimental de Aula Dei.-- Variaciones en los Centros.-- Viajes al extranjeros.-- Reunión del Consejo Ejecutivo de la Fundación Europea de la Ciencia.-- Seminario sobre Prioridades de Investigación.-- Grupo de Prioridades del ESRC (Comité de los Consejos de Investigaciones Científicas Europeos).-- BibliografíaPeer reviewe

Impacto de la COVID-19 en el tratamiento del infarto agudo de miocardio con elevación del segmento ST. La experiencia Española

The COVID-19 outbreak has had an unclear impact on the treatment and outcomes of patients with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to assess changes in STEMI management during the COVID-19 outbreak. Using a multicenter, nationwide, retrospective, observational registry of consecutive patients who were managed in 75 specific STEMI care centers in Spain, we compared patient and procedural characteristics and in-hospital outcomes in 2 different cohorts with 30-day follow-up according to whether the patients had been treated before or after COVID-19. Suspected STEMI patients treated in STEMI networks decreased by 27.6% and patients with confirmed STEMI fell from 1305 to 1009 (22.7%). There were no differences in reperfusion strategy (> 94% treated with primary percutaneous coronary intervention in both cohorts). Patients treated with primary percutaneous coronary intervention during the COVID-19 outbreak had a longer ischemic time (233 [150-375] vs 200 [140-332] minutes, P < .001) but showed no differences in the time from first medical contact to reperfusion. In-hospital mortality was higher during COVID-19 (7.5% vs 5.1%; unadjusted OR, 1.50; 95%CI, 1.07-2.11; P < .001); this association remained after adjustment for confounders (risk-adjusted OR, 1.88; 95%CI, 1.12-3.14; P = .017). In the 2020 cohort, there was a 6.3% incidence of confirmed SARS-CoV-2 infection during hospitalization. The number of STEMI patients treated during the current COVID-19 outbreak fell vs the previous year and there was an increase in the median time from symptom onset to reperfusion and a significant 2-fold increase in the rate of in-hospital mortality. No changes in reperfusion strategy were detected, with primary percutaneous coronary intervention performed for the vast majority of patients. The co-existence of STEMI and SARS-CoV-2 infection was relatively infrequent.S

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)