71 research outputs found
The effect of post-discharge educational intervention on patients in achieving objectives in modifiable risk factors six months after discharge following an episode of acute coronary syndrome, (CAM-2 Project): a randomized controlled trial
<p>Abstract</p> <p>Objectives</p> <p>We investigated whether an intervention mainly consisting of a signed agreement between patient and physician on the objectives to be reached, improves reaching these secondary prevention objectives in modifiable cardiovascular risk factors six-months after discharge following an acute coronary syndrome.</p> <p>Background</p> <p>There is room to improve mid-term adherence to clinical guidelines' recommendations in coronary heart disease secondary prevention, specially non-pharmacological ones, often neglected.</p> <p>Methods</p> <p>In CAM-2, patients discharged after an acute coronary syndrome were randomly assigned to the intervention or the usual care group. The primary outcome was reaching therapeutic objectives in various secondary prevention variables: smoking, obesity, blood lipids, blood pressure control, exercise and taking of medication.</p> <p>Results</p> <p>1757 patients were recruited in 64 hospitals and 1510 (762 in the intervention and 748 in the control group) attended the six-months follow-up visit. After adjustment for potentially important variables, there were, between the intervention and control group, differences in the mean reduction of body mass index (0.5 vs. 0.2; p < 0.001) and waist circumference (1.6 cm vs. 0.6 cm; p = 0.05), proportion of patients who exercise regularly and those with total cholesterol below 175 mg/dl (64.7% vs. 56.5%; p = 0.001). The reported intake of medications was high in both groups for all the drugs considered with no differences except for statins (98.1% vs. 95.9%; p = 0.029).</p> <p>Conclusions</p> <p>At least in the short term, lifestyle changes among coronary heart disease patients are achievable by intensifying the responsibility of the patient himself by means of a simple and feasible intervention.</p
Incidence of cardiovascular events after kidney transplantation and cardiovascular risk scores: study protocol
<p>Abstract</p> <p>Background</p> <p>Cardiovascular disease (CVD) is the major cause of death after renal transplantation. Not only conventional CVD risk factors, but also transplant-specific risk factors can influence the development of CVD in kidney transplant recipients.</p> <p>The main objective of this study will be to determine the incidence of post-transplant CVD after renal transplantation and related factors. A secondary objective will be to examine the ability of standard cardiovascular risk scores (Framingham, Regicor, SCORE, and DORICA) to predict post-transplantation cardiovascular events in renal transplant recipients, and to develop a new score for predicting the risk of CVD after kidney transplantation.</p> <p>Methods/Design</p> <p>Observational prospective cohort study of all kidney transplant recipients in the A Coruña Hospital (Spain) in the period 1981-2008 (2059 transplants corresponding to 1794 patients).</p> <p>The variables included will be: donor and recipient characteristics, chronic kidney disease-related risk factors, pre-transplant and post-transplant cardiovascular risk factors, routine biochemistry, and immunosuppressive, antihypertensive and lipid-lowering treatment. The events studied in the follow-up will be: patient and graft survival, acute rejection episodes and cardiovascular events (myocardial infarction, invasive coronary artery therapy, cerebral vascular events, new-onset angina, congestive heart failure, rhythm disturbances and peripheral vascular disease).</p> <p>Four cardiovascular risk scores were calculated at the time of transplantation: the Framingham score, the European Systematic Coronary Risk Evaluation (SCORE) equation, and the REGICOR (Registre Gironà del COR (Gerona Heart Registry)), and DORICA (Dyslipidemia, Obesity, and Cardiovascular Risk) functions.</p> <p>The cumulative incidence of cardiovascular events will be analyzed by competing risk survival methods. The clinical relevance of different variables will be calculated using the ARR (Absolute Risk Reduction), RRR (Relative Risk Reduction) and NNT (Number Needed to Treat).</p> <p>The ability of different cardiovascular risk scores to predict cardiovascular events will be analyzed by using the c index and the area under ROC curves. Based on the competing risks analysis, a nomogram to predict the probability of cardiovascular events after kidney transplantation will be developed.</p> <p>Discussion</p> <p>This study will make it possible to determine the post-transplant incidence of cardiovascular events in a large cohort of renal transplant recipients in Spain, to confirm the relationship between traditional and transplant-specific cardiovascular risk factors and CVD, and to develop a score to predict the risk of CVD in these patients.</p
Higher COVID-19 pneumonia risk associated with anti-IFN-α than with anti-IFN-Ï auto-Abs in children
We found that 19 (10.4%) of 183 unvaccinated children hospitalized for COVID-19 pneumonia had autoantibodies (auto-Abs) neutralizing type I IFNs (IFN-alpha 2 in 10 patients: IFN-alpha 2 only in three, IFN-alpha 2 plus IFN-omega in five, and IFN-alpha 2, IFN-omega plus IFN-beta in two; IFN-omega only in nine patients). Seven children (3.8%) had Abs neutralizing at least 10 ng/ml of one IFN, whereas the other 12 (6.6%) had Abs neutralizing only 100 pg/ml. The auto-Abs neutralized both unglycosylated and glycosylated IFNs. We also detected auto-Abs neutralizing 100 pg/ml IFN-alpha 2 in 4 of 2,267 uninfected children (0.2%) and auto-Abs neutralizing IFN-omega in 45 children (2%). The odds ratios (ORs) for life-threatening COVID-19 pneumonia were, therefore, higher for auto-Abs neutralizing IFN-alpha 2 only (OR [95% CI] = 67.6 [5.7-9,196.6]) than for auto-Abs neutralizing IFN-. only (OR [95% CI] = 2.6 [1.2-5.3]). ORs were also higher for auto-Abs neutralizing high concentrations (OR [95% CI] = 12.9 [4.6-35.9]) than for those neutralizing low concentrations (OR [95% CI] = 5.5 [3.1-9.6]) of IFN-omega and/or IFN-alpha 2
Registro Español de Trasplante Cardiaco. XXXI Informe Oficial de la AsociaciĂłn de Insuficiencia Cardiaca de la Sociedad Española de CardiologĂa
IntroducciĂłn y objetivos
Se presentan las caracterĂsticas clĂnicas y los resultados de los trasplantes cardiacos realizados en España con la actualizaciĂłn correspondiente a 2019.
MĂ©todos
Se describen las caracterĂsticas clĂnicas y los resultados de los trasplantes cardiacos realizados en 2019, asĂ como las tendencias de estos en el periodo 2010-2018.
Resultados
En 2019 se realizaron 300 trasplantes (8.794 desde 1984; 2.745 entre 2010 y 2019). Respecto a años previos, los cambios mås llamativos son el descenso hasta el 38% de los trasplantes realizados en código urgente, y la consolidación en el cambio de asistencia circulatoria pretrasplante, con la pråctica desaparición del balón de contrapulsación (0, 7%), la estabilización del uso del oxigenador extracorpóreo de membrana (9, 6%) y el aumento de los dispositivos de asistencia ventricular (29%). La supervivencia en el trienio 2016-2018 es similar a la del trienio 2013-2015 (p = 0, 34), y ambas mejores que la del trienio 2010-2012 (p = 0, 002 y p = 0, 01 respectivamente).
Conclusiones
Se mantienen estables tanto la actividad del trasplante cardiaco en España como los resultados en supervivencia en los Ășltimos 2 trienios. Hay una tendencia a realizar menos trasplantes urgentes, la mayorĂa con dispositivos de asistencia ventricular.
Introduction and objectives: The present report describes the clinical characteristics and outcomes of heart transplants in Spain and updates the data to 2019.
Methods: We describe the clinical characteristics and outcomes of heart transplants performed in Spain in 2019, as well as trends in this procedure from 2010 to 2018.
Results: In 2019, 300 transplants were performed (8794 since 1984; 2745 between 2010 and 2019). Compared with previous years, the most notable findings were the decreasing rate of urgent transplants (38%), and the consolidation of the type of circulatory support prior to transplant, with an almost complete disappearance of counterpulsation balloon (0.7%), stabilization in the use of extracorporeal membrane oxygenation (9.6%), and an increase in the use of ventricular assist devices (29.0%). Survival from 2016 to 2018 was similar to that from 2013 to 2015 (P = .34). Survival in both these periods was better than that from 2010 to 2012 (P = .002 and P = .01, respectively).
Conclusions: Heart transplant activity has remained stable during the last few years, as have outcomes (in terms of survival). There has been a trend to a lower rate of urgent transplants and to a higher use of ventricular assist devices prior to transplant
Detailed stratified GWAS analysis for severe COVID-19 in four European populations
Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12â488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence âPrecision Medicine in Chronic Inflammationâ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ă. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, âGenes, Environment and Inflammationâ. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health âCV PREVITALââstrategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project âREVEALâ; Fondazione IRCCS Caâ Granda âRicerca correnteâ, Fondazione Sviluppo Caâ Granda âLiver-BIBLEâ (PR-0391), Fondazione IRCCS Caâ Granda â5permilleâ âCOVID-19 Biobankâ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: âBio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program âDipartimenti di Eccellenza 2018â2022â. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, FundaciĂł IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by AcciĂłn de DinamizaciĂłn del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the AgĂšncia de GestiĂł dâAjuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 AcciĂłn EstratĂ©gica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-SubdirecciĂłn General de EvaluaciĂłn and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europaâ). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), âA way to build Europeâ). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the AcciĂłn EstratĂ©gica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque governmentâs Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de InvestigaciĂłn (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the âSpanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos IIIâ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos EstratĂ©gicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de FormaciĂłn en InvestigaciĂłn en Salud. Enrique CalderĂłnâs team is supported by CIBER of Epidemiology and Public Health (CIBERESP), âInstituto de Salud Carlos IIIâ. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germanyâs Excellence StrategyâCECAD, EXC 2030â390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint ProgrammeâNeurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence âPrecision Medicine in Chronic Inflammationâ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung UniversitĂ€tsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe
Detailed stratified GWAS analysis for severe COVID-19 in four European populations
Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic âŒ0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German
Federal Ministry of Education and Research (01KI20197), Andre Franke, David
Ellinghaus and Frauke Degenhardt were supported by the Deutsche
Forschungsgemeinschaft Cluster of Excellence âPrecision Medicine in Chronic
Inflammationâ (EXC2167). David Ellinghaus was supported by the German Federal
Ministry of Education and Research (BMBF) within the framework of the
Computational Life Sciences funding concept (CompLS grant 031L0165). David
Ellinghaus, Karina Banasik and SĂžren Brunak acknowledge the Novo Nordisk
Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana
Teles and Onur Ăzer were funded by the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German
Research Foundation (DFG) through the Research Training Group 1743, "Genes,
Environment and Inflammation". This project was supported by a Covid-19 grant from
the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197).
Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL â strategie di prevenzione
primaria cardiovascolare primaria nella popolazione italiana; The European Union
(EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project
LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca
corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione
IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi
was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research
(Covid-Bank). This research was partly funded by a MIUR grant to the Department of
Medical Sciences, under the program "Dipartimenti di Eccellenza 2018â2022". This
study makes use of data generated by the GCAT-Genomes for Life. Cohort study of
the Genomes of Catalonia, FundaciĂł IGTP. IGTP is part of the CERCA Program /
Generalitat de Catalunya. GCAT is supported by AcciĂłn de DinamizaciĂłn del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026);
the AgĂšncia de GestiĂł dâAjuts Universitaris i de Recerca (AGAUR) (2017-SGR 529).
Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en
Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirecciĂłn General de EvaluaciĂłn and the Fondo Europeo de Desarrollo Regional
(FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national
grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), âA way to build Europeâ).
Additional data included in this study was obtained in part by the COVICAT Study
Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19
Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio JuliĂ
and Sara Marsal were supported by the Spanish Ministry of Economy and
Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36).
Antonio JuliĂ was also supported the by national grant PI17/00019 from the AcciĂłn
Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque
Foundation for Health Innovation and Research-BIOEF. Mario CĂĄceres received
Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal
de InvestigaciĂłn (AEI, Spain) and the European Regional Development Fund
(FEDER, EU). Manuel Romero GĂłmez, Javier Ampuero Herrojo, RocĂo Gallego DurĂĄn
and Douglas Maya Miles are supported by the âSpanish Ministry of Economy,
Innovation and Competition, the Instituto de Salud Carlos IIIâ (PI19/01404,
PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian
government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed,
COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant
FI20/00215, PFIS Contratos Predoctorales de FormaciĂłn en InvestigaciĂłn en Salud.
Enrique CalderĂłn's team is supported by CIBER of Epidemiology and Public Health
(CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from
Research Council of Norway grant no 312780 during the conduct of the study. Dr.
SolligÄrd: reports grants from Research Council of Norway grant no 312769. The
BioMaterialBank Nord is supported by the German Center for Lung Research (DZL),
Airway Research Center North (ARCN). The BioMaterialBank Nord is member of
popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants
from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne
Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases,
University of Cologne, Cologne, Germany. He is supported by the German Federal
Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the
German Federal Ministry of Research and Education and is funded by the Deutsche
Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's
Excellence Strategy â CECAD, EXC 2030 â 390661388. The COMRI cohort is funded
by Technical University of Munich, Munich, Germany. Genotyping was performed by
the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM
Technology Centre, University of Helsinki. This work was supported by grants of the
Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland
and Lower Saxony. Kerstin U. Ludwig is supported by the German Research
Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the
Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported
by the Bavarian State Ministry for Science and Arts. Part of the genotyping was
supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA
BioBank, EADB) within the context of the EU Joint Programme â Neurodegenerative
Disease Research (JPND). Additional funding was derived from the German Research
Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is
supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH
state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist
Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence âPrecision
Medicine in Chronic Inflammationâ (EXC2167). Christoph Lange and Jan Heyckendorf
are supported by the German Center for Infection Research (DZIF). Thorsen Brenner,
Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung
UniversitÀtsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la
Cierva Incorporacion program, grant IJC2018-035131-I funded by
MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche
Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N
Multi-messenger Observations of a Binary Neutron Star Merger
On 2017 August 17 a binary neutron star coalescence candidate (later
designated GW170817) with merger time 12:41:04 UTC was observed through
gravitational waves by the Advanced LIGO and Advanced Virgo detectors.
The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray
burst (GRB 170817A) with a time delay of ⌠1.7 {{s}} with respect to
the merger time. From the gravitational-wave signal, the source was
initially localized to a sky region of 31 deg2 at a
luminosity distance of {40}-8+8 Mpc and with
component masses consistent with neutron stars. The component masses
were later measured to be in the range 0.86 to 2.26 {M}ÈŻ
. An extensive observing campaign was launched across the
electromagnetic spectrum leading to the discovery of a bright optical
transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC
4993 (at ⌠40 {{Mpc}}) less than 11 hours after the merger by the
One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The
optical transient was independently detected by multiple teams within an
hour. Subsequent observations targeted the object and its environment.
Early ultraviolet observations revealed a blue transient that faded
within 48 hours. Optical and infrared observations showed a redward
evolution over âŒ10 days. Following early non-detections, X-ray and
radio emission were discovered at the transientâs position ⌠9
and ⌠16 days, respectively, after the merger. Both the X-ray and
radio emission likely arise from a physical process that is distinct
from the one that generates the UV/optical/near-infrared emission. No
ultra-high-energy gamma-rays and no neutrino candidates consistent with
the source were found in follow-up searches. These observations support
the hypothesis that GW170817 was produced by the merger of two neutron
stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and
a kilonova/macronova powered by the radioactive decay of r-process
nuclei synthesized in the ejecta.</p
- âŠ