Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19)

  1. Kurth, Florian ORCID logo
  2. Roennefarth, Maria
  3. Thibeault, Charlotte
  4. Corman, Victor M.
  5. Müller-Redetzky, Holger
  6. Mittermaier, Mirja
  7. Ruwwe-Glösenkamp, Christoph
  8. Heim, Katrin M.
  9. Krannich, Alexander
  10. Zvorc, Saskia
  11. Schmidt, Sein
  12. Kretzler, Lucie
  13. Dang-Heine, Chantip
  14. Rose, Matthias
  15. Hummel, Michael
  16. Hocke, Andreas
  17. Hübner, Ralf H.
  18. Opitz, Bastian
  19. Mall, Marcus A.
  20. Röhmel, Jobst
  21. Landmesser, Ulf
  22. Pieske, Burkert
  23. Knauss, Samuel
  24. Endres, Matthias
  25. Spranger, Joachim
  26. Mockenhaupt, Frank P.
  27. Tacke, Frank
  28. Treskatsch, Sascha
  29. Angermair, Stefan
  30. Siegmund, Britta
  31. Spies, Claudia
  32. Weber-Carstens, Steffen
  33. Eckardt, Kai-Uwe
  34. Schürmann, Dirk
  35. Uhrig, Alexander
  36. Stegemann, Miriam S.
  37. Zoller, Thomas
  38. Drosten, Christian
  39. Suttorp, Norbert
  40. Witzenrath, Martin
  41. Hippenstiel, Stefan
  42. von Kalle, Christof
  43. Sander, Leif Erik

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1000 Titel
  • Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19)
1000 Autor/in
  1. Kurth, Florian |
  2. Roennefarth, Maria |
  3. Thibeault, Charlotte |
  4. Corman, Victor M. |
  5. Müller-Redetzky, Holger |
  6. Mittermaier, Mirja |
  7. Ruwwe-Glösenkamp, Christoph |
  8. Heim, Katrin M. |
  9. Krannich, Alexander |
  10. Zvorc, Saskia |
  11. Schmidt, Sein |
  12. Kretzler, Lucie |
  13. Dang-Heine, Chantip |
  14. Rose, Matthias |
  15. Hummel, Michael |
  16. Hocke, Andreas |
  17. Hübner, Ralf H. |
  18. Opitz, Bastian |
  19. Mall, Marcus A. |
  20. Röhmel, Jobst |
  21. Landmesser, Ulf |
  22. Pieske, Burkert |
  23. Knauss, Samuel |
  24. Endres, Matthias |
  25. Spranger, Joachim |
  26. Mockenhaupt, Frank P. |
  27. Tacke, Frank |
  28. Treskatsch, Sascha |
  29. Angermair, Stefan |
  30. Siegmund, Britta |
  31. Spies, Claudia |
  32. Weber-Carstens, Steffen |
  33. Eckardt, Kai-Uwe |
  34. Schürmann, Dirk |
  35. Uhrig, Alexander |
  36. Stegemann, Miriam S. |
  37. Zoller, Thomas |
  38. Drosten, Christian |
  39. Suttorp, Norbert |
  40. Witzenrath, Martin |
  41. Hippenstiel, Stefan |
  42. von Kalle, Christof |
  43. Sander, Leif Erik |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-06-13
1000 Erschienen in
1000 Quellenangabe
  • 48(4):619-626
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s15010-020-01464-x |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293426/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Purpose!#!Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide causing a global health emergency. Pa-COVID-19 aims to provide comprehensive data on clinical course, pathophysiology, immunology and outcome of COVID-19, to identify prognostic biomarkers, clinical scores, and therapeutic targets for improved clinical management and preventive interventions.!##!Methods!#!Pa-COVID-19 is a prospective observational cohort study of patients with confirmed SARS-CoV-2 infection treated at Charité - Universitätsmedizin Berlin. We collect data on epidemiology, demography, medical history, symptoms, clinical course, and pathogen testing and treatment. Systematic, serial blood sampling will allow deep molecular and immunological phenotyping, transcriptomic profiling, and comprehensive biobanking. Longitudinal data and sample collection during hospitalization will be supplemented by long-term follow-up.!##!Results!#!Outcome measures include the WHO clinical ordinal scale on day 15 and clinical, functional, and health-related quality-of-life assessments at discharge and during follow-up. We developed a scalable dataset to (i) suit national standards of care, (ii) facilitate comprehensive data collection in medical care facilities with varying resources, and (iii) allow for rapid implementation of interventional trials based on the standardized study design and data collection. We propose this scalable protocol as blueprint for harmonized data collection and deep phenotyping in COVID-19 in Germany.!##!Conclusion!#!We established a basic platform for harmonized, scalable data collection, pathophysiological analysis, and deep phenotyping of COVID-19, which enables rapid generation of evidence for improved medical care and identification of candidate therapeutic and preventive strategies. The electronic database accredited for interventional trials allows fast trial implementation for candidate therapeutic agents.!##!Trial registration!#!Registered at the German registry for clinical studies (DRKS00021688).
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal Risk Assessment [MeSH]
lokal World Health Organization [MeSH]
lokal Risk Factors [MeSH]
lokal Clinical phenotyping
lokal Biological Specimen Banks [MeSH]
lokal COVID-19 / SARS-CoV-2
lokal Disease Management [MeSH]
lokal COVID-19 [MeSH]
lokal Infectious disease
lokal Phenotype [MeSH]
lokal Berlin/epidemiology [MeSH]
lokal Observational Studies as Topic [MeSH]
lokal Pneumonia, Viral/physiopathology [MeSH]
lokal SARS-CoV-2 [MeSH]
lokal SARS-CoV-2
lokal Humans [MeSH]
lokal Prospective Studies [MeSH]
lokal Treatment Outcome [MeSH]
lokal Coronavirus Infections/physiopathology [MeSH]
lokal COVID-19
lokal Coronavirus Infections/epidemiology [MeSH]
lokal Time Factors [MeSH]
lokal Coronavirus
lokal Pandemics [MeSH]
lokal Original Paper
lokal Betacoronavirus [MeSH]
lokal Pneumonia, Viral/epidemiology [MeSH]
lokal Patient registry
lokal Registries [MeSH]
1000 Liste der Beteiligten
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