S. Fuhrmann

Statistical biases due to anonymization evaluated in an open clinical dataset from COVID-19 patients

Marcus M. Scheunemann, Lennart M. Reinke, J. Papenbrock, 2022, Scientific data.

Die COVID-19 Pandemie als Herausforderung und Chance für Register in der Versorgungsforschung: Erfahrungen aus Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)

J. Vehreschild, S. N. D. de Miranda, A. Classen, 2021, Das Gesundheitswesen.

Die COVID-19 Pandemie als Herausforderung und Chance für Register in der Versorgungsforschung: Erfahrungen aus Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS)

J. Vehreschild, F. Prasser, S. N. D. de Miranda, 2021, Das Gesundheitswesen.

First results of the “Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS)”

J. Nattermann, U. Merle, C. Spinner, 2020, Infection.

Clinical course and predictive risk factors for fatal outcome of SARS-CoV-2 infection in patients with chronic kidney disease

R. Müller, J. Nattermann, M. Lablans, 2021, Infection.

SARS-CoV-2 infection in chronic kidney disease patients with pre-existing dialysis: description across different pandemic intervals and effect on disease course (mortality)

J. Nattermann, J. Rupp, C. Spinner, 2022, Infection.

Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning

R. König, M. Oswald, J. Nattermann, 2021, Infection.

A Comparison of Aspergillus and Mucorales PCR Testing of Different Bronchoalveolar Lavage Fluid Fractions from Patients with Suspected Invasive Pulmonary Fungal Disease

H. Einsele, J. Springer, J. Loeffler, 2017, Journal of Clinical Microbiology.