Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    In: The Lancet Rheumatology, Elsevier BV, Vol. 3, No. 10 ( 2021-10), p. e707-e714
    Type of Medium: Online Resource
    ISSN: 2665-9913
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
  • 3
    In: The Lancet Rheumatology, Elsevier BV, Vol. 4, No. 9 ( 2022-09), p. e603-e613
    Type of Medium: Online Resource
    ISSN: 2665-9913
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 4
    In: JAMA Network Open, American Medical Association (AMA), Vol. 4, No. 10 ( 2021-10-18), p. e2129639-
    Type of Medium: Online Resource
    ISSN: 2574-3805
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2021
    detail.hit.zdb_id: 2931249-8
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 5
    In: Annals of the Rheumatic Diseases, BMJ, Vol. 80, No. Suppl 1 ( 2021-06), p. 173.2-175
    Abstract: An increased risk of severe COVID-19 outcomes may be seen in patients with autoimmune diseases on moderate to high daily doses of glucocorticoids, as well as in those with comorbidities. However, specific information about COVID-19 outcomes in SLE is scarce. Objectives: To determine the characteristics associated with severe COVID-19 outcomes in a multi-national cross-sectional registry of COVID-19 patients with SLE. Methods: SLE adult patients from a physician-reported registry of the COVID-19 GRA were studied. Variables collected at COVID-19 diagnosis included age, sex, race/ethnicity, region, comorbidities, disease activity, time period of COVID-19 diagnosis, glucocorticoid (GC) dose, and immunomodulatory therapy. Immunomodulatory therapy was categorized as: antimalarials only, no SLE therapy, traditional immunosuppressive (IS) drug monotherapy, biologics/targeted synthetic IS drug monotherapy, and biologic and traditional IS drug combination therapy. We used an ordinal COVID-19 severity outcome defined as: not hospitalized/hospitalized without supplementary oxygen; hospitalized with non-invasive ventilation; hospitalized with mechanical ventilation/extracorporeal membrane oxygenation; and death. An ordinal logistic regression model was constructed to assess the association between demographic characteristics, comorbidities, medications, disease activity and COVID-19 severity. This assumed that the relationship between each pair of outcome groups is of the same direction and magnitude. Results: Of 1069 SLE patients included, 1047 (89.6%) were female, with a mean age of 44.5 (SD: 14.1) years. Patient outcomes included 815 (78.8%) not hospitalized/hospitalized without supplementary oxygen; 116 (11.2) hospitalized with non-invasive ventilation, 25 (2.4%) hospitalized with mechanical ventilation/extracorporeal membrane oxygenation and 78 (7.5%) died. In a multivariate model (n=804), increased age [OR=1.03 (1.01, 1.04)], male sex [OR =1.93 (1.21, 3.08)] , COVID-19 diagnosis between June 2020 and January 2021 (OR =1.87 (1.17, 3.00)), no IS drug use [OR =2.29 (1.34, 3.91)], chronic renal disease [OR =2.34 (1.48, 3.70)] , cardiovascular disease [OR =1.93 (1.34, 3.91)] and moderate/high disease activity [OR =2.24 (1.46, 3.43)] were associated with more severe COVID-19 outcomes. Compared with no use of GC, patients using GC had a higher odds of poor outcome: 0-5 mg/d, OR =1.98 (1.33, 2.96); 5-10 mg/d, OR =2.88 (1.27, 6.56); 〉 10 mg/d, OR =2.01 (1.26, 3.21) (Table 1). Table 1. Characteristics associated with more severe COVID-19 outcomes in SLE. (N=804) OR (95% CI ) Age, years 1.03 (1.01, 1.04) Sex, Male 1.93 (1.21, 3.08) Race/Ethnicity, Non-White vs White 1.47 (0.87, 2.50) Region Europe Ref. North America 0.67 (0.29, 1.54) South America 0.67 (0.29, 1.54) Other 1.93 (0.85, 4.39) Season, June 16th 2020-January 8th 2021 vs January-June 15th 2020 1.87 (1.17, 3.00) Glucocorticoids 0 mg/day Ref. 0-5 mg/day 1.98 (1.33, 2.96) 5-10 mg/day 2.88 (1.27, 6.56) = 〉 10 mg/day 2.01 (1.26, 3.21) Medication Category Antimalarial only Ref. No IS drugs 2.29 (1.34, 3.91) Traditional IS drugs as monotherapy 1.17 (0.77, 1.77) b/ts IS drugs as monotherapy 1.00 (0.37, 2.71) Combination of traditional and b/ts IS 1.00 (0.55, 1.82) Comorbidity Burden Number of Comorbidities (excluding renal and cardiovascular disease) 1.39 (0.97, 1.99) Chronic renal disease 2.34 (1.48, 3.70) Cardiovascular disease 1.93 (1.34, 3.91) Disease Activity, Moderate/ high vs Remission/ low 2.24 (1.46, 3.43) IS: immunosuppressive. b/ts: biologics/targeted synthetics Conclusion: Increased age, male sex, glucocorticoid use, chronic renal disease, cardiovascular disease and moderate/high disease activity at time of COVID-19 diagnosis were associated with more severe COVID-19 outcomes in SLE. Potential limitations include possible selection bias (physician reporting), the cross-sectional nature of the data, and the assumptions underlying the outcomes modelling. Acknowledgements: The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance and do not necessarily represent the views of the ACR, EULAR) the UK National Health Service, the National Institute for Health Research (NIHR), or the UK Department of Health, or any other organization. Disclosure of Interests: Manuel F. Ugarte-Gil Grant/research support from: Pfizer, Janssen, Graciela S Alarcon: None declared, Andrea Seet: None declared, Zara Izadi: None declared, Cristina Reategui Sokolova: None declared, Ann E Clarke Consultant of: AstraZeneca, BristolMyersSquibb, GlaxoSmithKline, Exagen Diagnostics, Leanna Wise: None declared, Guillermo Pons-Estel: None declared, Maria Jose Santos: None declared, Sasha Bernatsky: None declared, Lauren Mathias: None declared, Nathan Lim: None declared, Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova, Janssen, and Optum unrelated to this work., Grant/research support from: Amgen and Bristol-Myers Squibb, Zachary Wallace Consultant of: Viela Bio and MedPace, Grant/research support from: Bristol-Myers Squibb and Principia/Sanofi, Kimme Hyrich Speakers bureau: Abbvie, Grant/research support from: MS, UCB, and Pfizer, Anja Strangfeld Speakers bureau: AbbVie, MSD, Roche, BMS, Pfizer, Grant/research support from: AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis, and UCB, Laure Gossec Consultant of: Abbvie, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sanofi-Aventis, UCB, Grant/research support from: Lilly, Mylan, Pfizer, Loreto Carmona: None declared, Elsa Mateus Grant/research support from: Pfizer, Abbvie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal S.A., MSD, Celgene, Medac, Pharmakern, GAfPA, Saskia Lawson-Tovey: None declared, Laura Trupin: None declared, Stephanie Rush: None declared, Gabriela Schmajuk: None declared, Patti Katz: None declared, Lindsay Jacobsohn: None declared, Samar Al Emadi: None declared, Emily Gilbert: None declared, Ali Duarte-Garcia: None declared, Maria Valenzuela-Almada: None declared, Tiffany Hsu: None declared, Kristin D’Silva: None declared, Naomi Serling-Boyd: None declared, Philippe Dieudé Consultant of: Boerhinger Ingelheim, Bristol-Myers Squibb, Lilly, Sanofi, Pfizer, Chugai, Roche, Janssen unrelated to this work, Grant/research support from: Bristol-Myers Squibb, Chugaii, Pfizer, unrelated to this work, Elena Nikiphorou: None declared, Vanessa Kronzer: None declared, Namrata Singh: None declared, Beth Wallace: None declared, Akpabio Akpabio: None declared, Ranjeny Thomas: None declared, Suleman Bhana Consultant of: AbbVie, Horizon, Novartis, and Pfizer (all 〈 $10,000) unrelated to this work, Wendy Costello: None declared, Rebecca Grainger Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, Cornerstones, Jonathan Hausmann Consultant of: Novartis, Sobi, Biogen, all unrelated to this work ( 〈 $10,000), Jean Liew Grant/research support from: Pfizer outside the submitted work, Emily Sirotich Grant/research support from: Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer based organization whose activities are largely supported by independent grants from pharmaceutical companies, Paul Sufka: None declared, Philip Robinson Speakers bureau: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all 〈 $10,000), Consultant of: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB (all 〈 $10,000), Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all 〈 $10,000)., Consultant of: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all 〈 $10,000), Milena Gianfrancesco: None declared, Jinoos Yazdany Consultant of: Eli Lilly and AstraZeneca unrelated to this project
    Type of Medium: Online Resource
    ISSN: 0003-4967 , 1468-2060
    RVK:
    Language: English
    Publisher: BMJ
    Publication Date: 2021
    detail.hit.zdb_id: 1481557-6
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 6
    In: Annals of the Rheumatic Diseases, BMJ, Vol. 81, No. Suppl 1 ( 2022-06), p. 165-166
    Abstract: There is a paucity of data in the literature about the outcome of patients with idiopathic inflammatory myopathy (IIM) who have been infected with SARS-CoV-2. Objectives To investigate factors associated with severe COVID-19 outcomes in patients with IIM. Methods Data on demographics, number of comorbidities, region, COVID-19 time period, physician-reported disease activity, anti-rheumatic medication exposure at the clinical onset of COVID-19, and COVID-19 outcomes of IIM patients were obtained from the voluntary COVID-19 Global Rheumatology Alliance physician-reported registry of adults with rheumatic disease (from 17 March 2020 to 27 August 2021). An ordinal COVID-19 severity scale was used as primary outcome of interest, with each outcome category being mutually exclusive from the other:a) no hospitalization, b) hospitalization (and no death), or c) death. Odds ratios (OR) were estimated using multivariable ordinal logistic regression. In ordinal logistic regression, the effect size of a categorical predictor can be interpreted as the odds of being one level higher on the ordinal COVID-19 severity scale than the reference category. Results Complete hospitalization and death outcome data was available in 348 IIM cases. Mean age was 53 years, and 223 (64.1%) were female. Overall, 167/348 (48.0%) people were not hospitalized, 136/348 (39.1%) were hospitalized (and did not die), and 45/348 (12.9%) died. Older age (OR=1.59 per decade of life, 95%CI 1.32-1.93), male sex (OR=1.63, 95%CI 1.004-2.64; versus female), high disease activity (OR=4.05, 95%CI 1.29-12.76; versus remission), presence of two or more comorbidities (OR=2.39, 95%CI 1.22-4.68; versus none), prednisolone-equivalent dose 〉 7.5 mg/day (OR=2.37, 95%CI 1.27-4.44; versus no glucocorticoid intake), and exposure to rituximab (OR=2.60, 95%CI 1.23-5.47; versus csDMARDs only) were associated with worse COVID-19 outcomes (Table 1). Table 1. Multivariable logistic regression analysis of factors associated with the ordinal COVID-19 severity outcomes. AZA, azathioprine; CI, confidence interval; combo, combination; CSA, ciclosporin; CYC, cyclophosphamide; DMARD, disease-modifying anti-rheumatic drug; b/tsDMARD, biologic/targeted synthetic DMARD, csDMARD, conventional synthetic DMARD; HCQ, hydroxychloroquine; IVIg, intravenous immunoglobulin; LEF, leflunomide; MMF, mycophenolate mofetil; mono, monotherapy; MTX, methotrexate; OR, odds ratio; Ref, reference; RTX, rituximab; SSZ, sulfasalazine; TAC, tacrolimus. Variable OR (95%CI ) P-value Variable OR (95%CI ) P-value Age (per decade ) 1.59 (1.32-1.93 ) 〈 0.001 Comorbidities Male sex 1.63 (1.004-2.64 ) 0.048 None Ref NA Prednisolone-equivalent dose One 1.46 (0.79-2.72) 0.228 None Ref NA Two or more 2.39 (1.22-4.68 ) 0.011 〉 0 to 7.5mg/day 1.10 (0.57-2.11) 0.779 Physician-reported disease activity 〉 7.5mg/day 2.37 (1.27-4.44 ) 0.007 Remission Ref NA IVIg 0.41 (0.15-1.16) 0.093 Low/moderate 1.23 (0.67-2.28) 0.504 DMARDs High 4.05 (1.29-12.76 ) 0.018 csDMARD only (mono or combi - HCQ, MTX, LEF, SSZ) Ref NA Region No DMARD 1.84 (0.90-3.75) 0.094 Europe Ref NA b/tsDMARD mono or combi (except RTX) 1.60 (0.49-5.26) 0.435 North America 0.89 (0.49-1.61) 0.694 CSA/CYC/TAC mono or combi (except RTX or b/tsDMARDs) 1.55 (0.52-4.58) 0.429 Other 4.25 (2.21-8.16 ) 〈 0.001 AZA mono 1.70 (0.69-4.19) 0.249 Time period MMF mono 1.22 (0.53-2.82) 0.634 Before 15 June 2020 Ref NA AZA/MMF combi (except RTX or b/tsDMARDs) 0.71 (0.25-2.00) 0.517 16 June - 30 September 2020 0.58 (0.26-1.27) 0.171 RTX mono or combi 2.60 (1.23-5.47 ) 0.012 After 1 October 2020 0.58 (0.35-0.95 ) 0.032 Conclusion These are the first global registry data on the impact of COVID-19 on IIM patients. Older age, male gender, higher comorbidity burden, higher disease activity, higher glucocorticoid intake and rituximab exposure were associated with worse outcomes. These findings will inform risk stratification and management decisions for IIM patients. References None Disclosure of Interests Su-Ann Yeoh: None declared, Milena Gianfrancesco: None declared, Saskia Lawson-Tovey: None declared, Kimme Hyrich Speakers bureau: AbbVie unrelated to this work, Grant/research support from: Pfizer, BMS, both unrelated to this work, Anja Strangfeld Speakers bureau: AbbVie, Celltrion, MSD, Janssen, Lilly, Roche, BMS, Pfizer, all unrelated to this work, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, all unrelated to this work, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, Sandoz, all unrelated to this work, Loreto Carmona: None declared, Elsa Mateus Consultant of: Boehringer Ingelheim Portugal, not related to this work, Martin Schaefer: None declared, Christophe Richez Speakers bureau: Abbvie, Amgen, Astra Zeneca, Biogen, BMS, Celltrion, Eli Lilly, Galapagos, GSK, MSD, Novartis, and Pfizer, all unrelated to this abstract, Consultant of: Abbvie, Amgen, Astra Zeneca, Biogen, BMS, Celltrion, Eli Lilly, Galapagos, GSK, MSD, Novartis, and Pfizer, all unrelated to this abstract, Eric Hachulla Speakers bureau: Johnson & Johnson, GlaxoSmithKline, Roche-Chugai, all unrelated to this work, Consultant of: Bayer, Boehringer Ingelheim, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, all unrelated to this work, Grant/research support from: CSL Behring, GlaxoSmithKline, Johnson & Johnson, Roche-Chugai, Sanofi-Genzyme, all unrelated to this work, Marie Holmqvist: None declared, Carlo Alberto Scirè Grant/research support from: AbbVie, Lilly, both unrelated to this work, Rebecca Hasseli: None declared, Arundathi Jayatilleke: None declared, Tiffany Hsu: None declared, Kristin D’Silva: None declared, Victor Pimentel-Quiroz: None declared, Monica Vasquez del Mercado: None declared, Samuel Katsuyuki Shinjo: None declared, Edgard Reis Neto: None declared, Laurindo Rocha Jr: None declared, Ana Carolina de Oliveira e Silva Montandon Speakers bureau: GSK, not related to this work, Paula Jordan: None declared, Emily Sirotich: None declared, Jonathan Hausmann Speakers bureau: Novartis, Biogen, Pfizer, not related to this work, Consultant of: Novartis, Biogen, Pfizer, not related to this work, Jean Liew Grant/research support from: Pfizer research grant, completed in 2021, not related to this work, Lindsay Jacobsohn: None declared, Monique Gore-Massy Speakers bureau: Aurinia Pharmaceuticals, Boehringer Ingelheim, Bristol-Myers Squibb, not related to this work, Consultant of: Aurinia Pharmaceuticals, Boehringer Ingelheim, Bristol-Myers Squibb, not related to this work, Paul Sufka: None declared, Rebecca Grainger Speakers bureau: AbbVie, Janssen, Novartis, Pfizer and Cornerstones, all unrelated to this work, Consultant of: AbbVie, Novartis, both unrelated to this work, Suleman Bhana Shareholder of: Pfizer, Inc, Speakers bureau: AbbVie, Horizon, Novartis, and Pfizer, all unrelated to this work, Consultant of: AbbVie, Horizon, Novartis, and Pfizer, all unrelated to this work, Employee of: Pfizer, Inc, Zachary Wallace: None declared, Philip Robinson Speakers bureau: Abbvie, Janssen, Roche, GSK, Novartis, Lilly, UCB, all unrelated to this work, Paid instructor for: Lilly, unrelated to this work, Consultant of: GSK, Kukdong, Atom Biosciences, UCB, all unrelated to this work, Grant/research support from: Janssen, Pfizer, UCB and Novartis, all unrelated to this work, Jinoos Yazdany Consultant of: Aurinia, Astra Zeneca, Pfizer, all unrelated to this work, Grant/research support from: Astra Zeneca, Gilead, BMS Foundation, all unrelated to this work, Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this work., Consultant of: Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, all unrelated to this work.
    Type of Medium: Online Resource
    ISSN: 0003-4967 , 1468-2060
    RVK:
    Language: English
    Publisher: BMJ
    Publication Date: 2022
    detail.hit.zdb_id: 1481557-6
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 7
    In: The Lancet, Elsevier BV, Vol. 403, No. 10442 ( 2024-06), p. 2405-2415
    Type of Medium: Online Resource
    ISSN: 0140-6736
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 2067452-1
    detail.hit.zdb_id: 3306-6
    detail.hit.zdb_id: 1476593-7
    SSG: 5,21
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 8
    In: The Lancet, Elsevier BV, Vol. 403, No. 10442 ( 2024-06), p. 2416-2425
    Type of Medium: Online Resource
    ISSN: 0140-6736
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2024
    detail.hit.zdb_id: 2067452-1
    detail.hit.zdb_id: 3306-6
    detail.hit.zdb_id: 1476593-7
    SSG: 5,21
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 9
    In: Annals of the Rheumatic Diseases, BMJ, Vol. 80, No. Suppl 1 ( 2021-06), p. 175.2-176
    Abstract: Acute Respiratory Distress Syndrome (ARDS) is a life-threatening complication of COVID-19 and has been reported in approximately one-third of hospitalized patients with COVID-19 1 . Risk factors associated with the development of ARDS include older age and diabetes 2 . However, little is known about factors associated with ARDS in the setting of COVID-19, in patients with rheumatic disease or those receiving immunosuppressive medications. Prediction algorithms using traditional regression methods perform poorly with rare outcomes, often yielding high specificity but very low sensitivity. Machine learning algorithms optimized for rare events are an alternative approach with potentially improved sensitivity for rare events, such as ARDS in COVID-19 among patients with rheumatic disease. Objectives: We aimed to develop a prediction model for ARDS in people with COVID-19 and pre-existing rheumatic disease using a series of machine learning algorithms and to identify risk factors associated with ARDS in this population. Methods: We used data from the COVID-19 Global Rheumatology Alliance (GRA) Registry from March 24 to Nov 1, 2020. ARDS diagnosis was indicated by the reporting clinician. Five machine learning algorithms optimized for rare events predicted ARDS using 42 variables covering patient demographics, rheumatic disease diagnoses, medications used at the time of COVID-19 diagnosis, and comorbidities. Model performance was assessed using accuracy, area under curve, sensitivity, specificity, positive predictive value, and negative predictive value. Adjusted odds ratios corresponding to the 10 most influential predictors from the best performing model were derived using hierarchical multivariate mixed-effects logistic regression that accounted for within-country correlations. Results: A total of 5,931 COVID-19 cases from 67 countries were included in the analysis. Mean (SD) age was 54.9 (16.0) years, 4,152 (70.0%) were female, and 2,399 (40.5%) were hospitalized. ARDS was reported in 388 (6.5% of total and 15.6% of hospitalized) cases. Statistically significant differences in the risk of ARDS were observed by demographics, diagnoses, medications, and comorbidities using unadjusted univariate comparisons (data not shown). Gradient boosting machine (GBM) had the highest sensitivity (0.81) and was considered the best performing model (Table 1). Hypertension, interstitial lung disease, kidney disease, diabetes, older age, glucocorticoids, and anti-CD20 monoclonal antibodies were associated with the development of ARDS while tumor necrosis factor inhibitors were associated with a protective effect (Figure 1). Table 1. Performance of machine learning algorithms. GBM SVM GLMNET NNET RF Accuracy 0.79 0.68 0.66 0.66 0.67 AUC 0.75 0.70 0.74 0.58 0.74 Sensitivity 0.81 0.68 0.65 0.68 0.67 Specificity 0.49 0.60 0.73 0.48 0.68 PPV 0.96 0.96 0.97 0.95 0.97 NPV 0.16 0.12 0.13 0.09 0.13 GBM: Gradient Boosting Machine, SVM: Support vector machines, GLMNET: Lasso and Elastic-Net Regularized Generalized Linear Models, NNET: Neural Networks, RF: Random Forest. AUC: Area Under Curve; PPV: Positive Predictive Value; NPV: Negative Predictive Value. Conclusion: In this global cohort of patients with rheumatic disease, a machine learning model, GBM, predicted the onset of ARDS with 81% sensitivity using baseline information obtained at the time of COVID-19 diagnosis. These results identify patients who may be at higher risk of severe COVID-19 outcomes. Further studies are necessary to validate the proposed prediction model in external cohorts and to evaluate its clinical utility. Disclaimer: The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance, and do not necessarily represent the views of the ACR, NIH, (UK) NHS, NIHR, or the department of Health. References: [1]Tzotzos SJ, Fischer B, Fischer H, Zeitlinger M. 2020;24(1):516. [2]Wu C, Chen X, Cai Y, et al. JAMA Intern Med. 2020;180(7):934-943. Acknowledgements: The COVID-19 Global Rheumatology Alliance. Disclosure of Interests: Zara Izadi: None declared, Milena Gianfrancesco: None declared, Kimme Hyrich Speakers bureau: Abbvie and grant income from BMS, UCB, and Pfizer, all unrelated to this study., Anja Strangfeld Speakers bureau: AbbVie, MSD, Roche, BMS, Pfizer, outside the submitted work., Grant/research support from: A consortium of 13 companies (among them AbbVie, BMS, Celltrion, Fresenius Kabi, Lilly, Mylan, Hexal, MSD, Pfizer, Roche, Samsung, Sanofi-Aventis, and UCB) supporting the German RABBIT register., Laure Gossec Consultant of: Abbvie, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sanofi-Aventis, UCB., Grant/research support from: Lilly, Mylan, Pfizer, all unrelated to this study., Loreto Carmona Consultant of: Loreto Carmona’s institute works by contract for laboratories among other institutions, such as Abbvie Spain, Eisai, Gebro Pharma, Merck Sharp & Dohme España, S.A., Novartis, Farmaceutica, Pfizer, Roche Farma, Sanofi Aventis, Astellas Pharma, Actelion Pharmaceuticals España, Grünenthal GmbH, and UCB Pharma., Elsa Mateus Grant/research support from: LPCDR received grants from Abbvie, Novartis, Janssen-Cilag, Lilly Portugal, Sanofi, Grünenthal S.A., MSD, Celgene, Medac, Pharmakern, GAfPA and Pfizer., Saskia Lawson-Tovey: None declared, Laura Trupin: None declared, Stephanie Rush: None declared, Gabriela Schmajuk: None declared, Lindsay Jacobsohn: None declared, Patti Katz: None declared, Samar Al Emadi: None declared, Leanna Wise: None declared, Emily Gilbert: None declared, Maria Valenzuela-Almada: None declared, Ali Duarte-Garcia: None declared, Jeffrey Sparks Consultant of: Bristol-Myers Squibb, Gilead, Inova, Janssen, and Optum unrelated to this work., Grant/research support from: Amgen and Bristol-Myers Squibb., Tiffany Hsu: None declared, Kristin D’Silva: None declared, Naomi Serling-Boyd: None declared, Suleman Bhana Employee of: Suleman Bhana reports non-branded marketing campaigns for Novartis ( 〈 $10,000)., Wendy Costello: None declared, Rebecca Grainger Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, Cornerstones and travel assistance from Pfizer (all 〈 $10,000)., Jonathan Hausmann Consultant of: Novartis, unrelated to this work ( 〈 $10,000)., Jean Liew Grant/research support from: Pfizer, outside the submitted work., Emily Sirotich Grant/research support from: Emily Sirotich is a Board Member of the Canadian Arthritis Patient Alliance, a patient run, volunteer-based organization whose activities are largely supported by independent grants from pharmaceutical companies., Paul Sufka: None declared, Zachary Wallace Consultant of: Viela Bio and MedPace, outside the submitted work., Grant/research support from: Bristol-Myers Squibb and Principia/Sanofi., Pedro Machado Speakers bureau: Abbvie, BMS, Celgene, Eli Lilly, Janssen, MSD, Novartis, Pfizer, Roche and UCB, all unrelated to this study (all 〈 $10,000)., Philip Robinson Consultant of: Abbvie, Eli Lilly, Janssen, Novartis, Pfizer and UCB and travel assistance from Roche (all 〈 $10,000)., Jinoos Yazdany Consultant of: Eli Lilly and Astra Zeneca, unrelated to this project.
    Type of Medium: Online Resource
    ISSN: 0003-4967 , 1468-2060
    RVK:
    Language: English
    Publisher: BMJ
    Publication Date: 2021
    detail.hit.zdb_id: 1481557-6
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 10
    In: Radiography, Elsevier BV, Vol. 21, No. 3 ( 2015-08), p. 273-277
    Type of Medium: Online Resource
    ISSN: 1078-8174
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2015
    detail.hit.zdb_id: 2010900-3
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages