Assessment of the Coagulation Profile in Canine Multiple Myeloma: A Cohort Investigation in 234 Dogs

Hypercoagulability in canine multiple myeloma (MM) as described in humans has not been reported and prognostic factors related to hemostasis have not been investigated. Aims of this study were: to describe the haemostatic profile in dogs with MM, to detect a possible hypercoagulable state, and to assess whether coagulation parameters have prognostic value. Haemostatic alteration at the initial visit of dogs affected by MM (Group 1, n = 78) were retrieved from the electronic data- base (P.O.A. System-Plus 9.0®) of the San Marco Veterinary Clinic, between 2002–2015. Dogs with MM met the following criteria: bone marrow plasma cells ≥ 15%, osteolytic lesions, serum mono-biclonal gammopathy and extensive coagulation profile including platelet count, aPTT, PT, fibrinogen, thrombin time (TT), FPDs, D-Dimer and antithrombin (AT). Two groups of dogs individually matched for age, breed, and sex were used as controls: healthy dogs (Group 2, n = 78) and sick dogs without MM (Group 3, n = 78). In addition, the hemostatic profile between clinical bleeding (B-MM, n = 45) (e.g., gum bleeding, epistaxis) and no- clinical bleeding (NB-MM, n = 33) dogs with MM was evaluated. Kruskal-Wallis and Wilcoxon-Mann-Whitney tests were used to compare groups. Risk to death at 90 days after diagnosis within B-MM and NB-MM dogs was evaluated by Pearson's X2 test. ROC curves were used to identify the best analyte to predict death. Prothrombin time and aPTT were increased (p = 0.001) in Group 1 vs groups 2 and 3, TT was increased (p = 0.001) in Group 1 vs 3. The platelet count and AT concentration were decreased in Group 1 vs groups 2 and 3 (p = 0.001). Fibrinogen concentration was decreased in Group 1 vs 3 (p = 0.01). No differences between Groups 1 vs groups 2 and 3 for FDPs and D-dimer were observed. Platelet count and AT concentrations were decreased in B-MM vs NB-MM (p = 0.04; p = 0.026); PT and aPTT and were increased in B-MM vs NB-MM (p = 0.026; p = 0.03). No differences between B-MM and NB-MM were observed for TT, FDPs, D-Dimer. B-MM dogs showed lower mortality rate in respect to NB-MM patient (p < 0.028). The TT resulted the best haemostatic analyte in predicting death in dogs affected with MM (p < 0.04; AUC 64%; 95% CI = 0.48–0.82). Primary and secondary haemostasis are compromised in dogs with MM while tertiary haemostasis appears unaffected. The hypercoagulable state, opposite to humans, is unlikely in dogs with MM. Surprisingly, dogs with MM and clinical bleeding apparently have protective effect against death. The prediction of mortality in canine MM was related to TT

Zerovalent Fe, Co and Ni nanoparticle toxicity evaluated on SKOV-3 and U87 cell lines

ABSTRACT:We have considered nanoparticles (NPs) of Fe, Co and Ni, three transition metals sharing similar chemical properties. NP dissolution, conducted by radioactive tracer method and inductively coupled plasmamass spectrometry, indicated that NiNPs and FeNPs released in the medium a much smaller amount of ions than that released by Co NPs. The two considered methodological approaches, however, gave comparable but not identical results. All NPs are readily internalized by the cells, but their quantity inside the cells is less than 5%. Cytotoxicity and gene expression experimentswere performed on SKOV-3 and U87 cells. In both cell lines, CoNPs and NiNPs were definitely more toxic than FeNPs. Real-time polymerase chain reaction experiments aimed to evaluatemodifications of the expression of genes involved in the cellular stress response (HSP70, MT2A), or susceptible to metal exposure (SDHB1 and MLL), or involved in specific cellular processes (caspase3, IQSEC1 and VMP1), gave different response patterns in the two cell lines. HSP70, for example, was highly upregulated by CoNPs and NiNPs, but only in SKOV-3 cell lines. Overall, this work underlines the difficulties in predicting NP toxicological properties based only on their chemical characteristics. We, consequently, think that, at this stage of our knowledge, biological effects induced by metal-based NPs should be examined on a case-by-case basis following studies on different in vitro models. Moreover, with the only exception of U87 exposed to Ni, our results suggest thatmetallic NPs have caused, on gene expression, similar effects to those caused by their cor- Q2 responding ions

O desenvolvimento do protocolo de avaliação de bem-estar AWIN (Animal Welfare Indicators) para jumentos

The donkey population has increased in the last 10 years, with an estimated 50 million donkeys currently worldwide. Donkey welfare, meanwhile, is an increasing global concern that receives close public scrutiny. However, multiple challenges are surrounding how donkey welfare is assessed and recorded. The Animal Welfare Indicators (AWIN) project is the first project, funded by the European Commission, intended to improve donkey welfare by developing a scientifically sound and practical on-farm welfare assessment protocol. The present study describes the procedure for the development of the AWIN welfare assessment protocol for donkeys: 1) selection of promising welfare indicators; 2) research to cover gaps in knowledge; 3) stakeholder consultation; 4) testing the prototype protocol on-farm. The proposed two-level strategy improved on-farm feasibility, while the AWIN donkey app enables the standardized collection of data with prompt results. Although limitations are linked with a relatively small reference population, the AWIN welfare assessment protocol represents the first scientific and standardized approach to evaluate donkey welfare on-farm.Na última década, a população de jumentos vem aumentando; estima-se que existam aproximadamente 50 milhões de em todo o mundo. O bem-estar dos jumentos é uma preocupação global crescente, que recebe um escrutínio público próximo. No entanto, existem vários desafios em torno de como o bem-estar do jumento é avaliado e registrado. O projeto Indicadores de Bem-Estar Animal (AWIN) foi o primeiro projeto, financiado pela Comissão Europeia, destinado a melhorar o bem-estar dos jumentos, desenvolvendo um protocolo de avaliação do bem-estar cientificamente válido e prático na fazenda. O presente estudo descreve o procedimento para o desenvolvimento do protocolo de avaliação de bem-estar AWIN para jumentos: 1) seleção de indicadores promissores de bem-estar; 2) pesquisa para cobrir lacunas no conhecimento; 3) consulta às partes interessadas; 4) testando o protocolo do protótipo em fazendas. A estratégia proposta em dois níveis de avaliação melhorou a viabilidade na fazenda, além disso, o aplicativo AWIN donkey permite coletar dados de maneira padronizada e mostrar resultados rapidamente. Embora a limitação esteja ligada a uma população de referência relativamente pequena, o protocolo de avaliação de bem-estar do AWIN representa a primeira abordagem científica e padronizada para avaliar o bem-estar de jumentos em fazendas

Time course of risk factors associated with mortality of 1260 critically ill patients with COVID-19 admitted to 24 Italian intensive care units

Purpose: To evaluate the daily values and trends over time of relevant clinical, ventilatory and laboratory parameters during the intensive care unit (ICU) stay and their association with outcome in critically ill patients with coronavirus disease 19 (COVID-19). Methods: In this retrospective–prospective multicentric study, we enrolled COVID-19 patients admitted to Italian ICUs from February 22 to May 31, 2020. Clinical data were daily recorded. The time course of 18 clinical parameters was evaluated by a polynomial maximum likelihood multilevel linear regression model, while a full joint modeling was fit to study the association with ICU outcome. Results: 1260 consecutive critically ill patients with COVID-19 admitted in 24 ICUs were enrolled. 78% were male with a median age of 63 [55–69] years. At ICU admission, the median ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) was 122 [89–175] mmHg. 79% of patients underwent invasive mechanical ventilation. The overall mortality was 34%. Both the daily values and trends of respiratory system compliance, PaO2/FiO2, driving pressure, arterial carbon dioxide partial pressure, creatinine, C-reactive protein, ferritin, neutrophil, neutrophil–lymphocyte ratio, and platelets were associated with survival, while for lactate, pH, bilirubin, lymphocyte, and urea only the daily values were associated with survival. The trends of PaO2/FiO2, respiratory system compliance, driving pressure, creatinine, ferritin, and C-reactive protein showed a higher association with survival compared to the daily values. Conclusion: Daily values or trends over time of parameters associated with acute organ dysfunction, acid–base derangement, coagulation impairment, or systemic inflammation were associated with patient survival

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 12 488 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 ‘Precision Medicine in Chronic Inflammation’ (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.Ö. 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, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—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). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-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 ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació 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 Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). 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), ‘A way to build Europe’). 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 Acción Estratégica 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 government’s 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 Investigación (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 ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (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 Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. 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 Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. 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 Programme—Neurodegenerative 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 ‘Precision Medicine in Chronic Inflammation’ (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 Universitätsmedizin 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 ∼0.9-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 “Precision Medicine in Chronic Inflammation” (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 Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer 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 – 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 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts 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 ISCIIISubdirección General de Evaluación 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), “A way to build Europe”). 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 Julià 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 Julià was also supported the by national grant PI17/00019 from the Acción 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 Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (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 Formación en Investigación en Salud. Enrique Calderón'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. Solligård: 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 – CECAD, EXC 2030 – 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 – 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 “Precision Medicine in Chronic Inflammation” (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 Universitätsmedizin 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

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Bleeding diathesis in canine multiple myeloma and prognostic implications: A cohort study in 156 dogs

Multiple myeloma (MM) is a tumor of plasma cells representing approximately 1% of all canine tumors. Clinical evident bleeding is often referred to as the main finding. The aim of the study was to evaluate the occurrence of clinical bleedings in dogs with MM and its prognostic implications compared to a population of dogs not affected by MM. Two groups of dogs (# 78 each) individually matched for breed, age and gender were considered. Group-1 (exposed) was affected by MM and group-2 (unexposed) was affected by other diseases. They were compared for bleeding and mortality at 90 days after diagnosis (relative risk, RR; attributable risk, AR). Among group-1, bleeding patients (B) were compared with non-bleeding patients (NB) in terms of mortality at 90 days (RR, AR). Incident cases of MM were 78/57,694 (0.13%). Signs of bleeding up to 30 days before the referral presentation were found in 33 (42.3%) group-1 dogs in comparison to 6 (7.7%) group-2 dogs (RR, 5.50, CI 95% 2.55–12.3, p=0.0001; AR, 0.34, CI 95% 0.22–0.47, p=0.0001). Epistaxis was the most frequent sign of bleeding recorded. Nineteen dogs from group-1 (24.3%) and eight from group-2 (10.2%) were non-survivors (RR=2.37, CI 95% 1.14–5.06, p=0.01; AR=0.14, CI 95% 0.02–0.26, p=0.01). Among the group-1, the B dogs, 4/33 (12.1%) were non-survivors, while 15/45 NB dogs (33.3%) were non-survivors (RR=2.75, CI 95% 1.08–7.44, p=0.03; AR=0.21, CI 95% 0.20–0.38, p=0.03). Epistaxis at diagnosis was frequent in MM dogs, and signs of bleeding were associated with a more favorable 90-day prognosis

HAEMOSTATIC PROFILE IN CANINE MULTIPLE MYELOMA: A COHORT STUDY IN 210 DOGS

Human patients with MM have short survival times associated with frequent complications such as throm- bosis.1 Considering their life span, dogs with MM in comparison to humans, have a longer survival times. Hypercoagulable complications in canine MM are not known and prognostic factors linked to haemostasis have been not thoroughly investigated.2 Aim of the study: a) to describe the haemostatic profile in dogs with MM at presentation, b) to assess whether coagulation parameters have a prognostic value, and c) to detect a possible hypercoagulable state. Haemostatic abnormalities in dogs with MM (Group 1, #70) were evaluated via search of the electronic data-base (P.O.A System Plus 9.0 R ) of the San Marco Veterinary Clinic, between 2002-2015. Dogs in- cluded in Group 1 met the criteria: bone marrow plasmacytosis (plasmacells 15%), osteolytic lesions, serum mono-biclonal gammopathy. All groups had a haemostatic panel taken at presentation. Two groups of dogs matched for age, breed, and sex were enrolled as case-control: healthy dogs (Group 2,#70) and dogs affected by various diseases (Group 3,#70). The analytes investigated were: Platelet count (PLT), activated Partial Thromboplastin Time (aPTT), Prothrombin Time (PT), Fibrinogen, Thrombin Time (TT), Fibrin-Fibrinogen Degradation Products (FPDs), D-Dimer and Antithrombin (AT). In addition, within the MM-dogs the haemostatic profile between bleeding (B-MM, #42) and non-bleeding (NB-MM, #28) dogs was evaluated. Statistical differences between groups was evaluated by Kruskal-Wallis test and post-test analysis were performed by Wilcoxon-Mann-Whitney. Risk to death within B-MM and NB-MM dogs was evaluated by Pearson’s X2 test. ROC curves were used to identify the best analyte to predict death. The significance level for all statistical test was set at p<0.05. aPTT, PT and TT were significantly increased in Group 1 compared to Groups 2 and 3. PLT count and AT concentrations were significantly decreased in Group 1 compared to Group 2 and 3. Fibrinogen concentration was significantly decreased in Group 1 compare to Group 3, while no difference was present between Group 1 and 2. No difference were present between Groups 1 versus Group 2 and 3 for FDPs and D-dimer. PLT count and AT concentration were significantly decreased in B-MM compared to NB-MM; aPTT and PT were significantly increased in B-MM compared to NB-MM; finally, no differences between B-MM and NB-MM were present for TT, FDPs, D-Dimer. B-MM dogs showed lower mortality rate in respect to NB-MM patient (p<0.028). AT resulted the best haemostatic analyte in predicting death in dogs affected with MM (p<0.04; AUC 64%; 95% CI 0.50-0.78). Primary and secondary haemostasis are highly compromised in dogs affected by MM while tertiary haemostasis appears to be not altered, suggesting that a hypercoagulable state, opposite to humans, is un- likely in dogs with MM. Surprisingly, in dogs with MM bleeding seems to have a protective effect against death. The best haemostatic assay to predict the mortality in canine MM at 90 days after the diagnosis is the AT. 1) Coppola A, Tufano A, Di Capua M, et al. Bleeding and thrombosis in multiple myeloma and related plasma cell disorders. Semin Thromb Hemost, 2011;37, 929-945. 2) Matus RE, Leifer CE, MacEwen EG, et al. Prognostic factors for multiple myeloma in dog. J Am Vet Med Assoc, 1986;188, 11:1288-1292