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1,622 results on '"Marx, Gernot"'

152. Inhaled Prostacyclin Improves Oxygenation in Patients with COVID-19-induced Acute Respiratory Distress Syndrome – a randomized controlled multicenter trial

Author

Haeberle, Helene A., primary, Calov, Stefanie, additional, Martus, Peter, additional, Higuita, Lina Maria Serna, additional, Koeppen, Michael, additional, Goll, Almuth, additional, Zarbock, Alexander, additional, Meersch, Melanie, additional, Weiss, Raphael, additional, Mehrländer, Martin, additional, Marx, Gernot, additional, Putensen, Christian, additional, Bakchoul, Tamam, additional, Magunia, Harry, additional, Nieswandt, Bernhard, additional, Mirakaj, Valbona, additional, and Rosenberger, Peter, additional

Published
2022
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155. Key summary of German national treatment guidance for hospitalized COVID-19 patients (Jul, 10.1007/s15010-021-01645-2, 2021)

Author

Malin, Jakob J., Spinner, Christoph D., Janssens, Uwe, Welte, Tobias, Weber-Carstens, Steffen, Schaelte, Gereon, Gastmeier, Petra, Langer, Florian, Wepler, Martin, Westhoff, Michael, Pfeifer, Michael, Rabe, Klaus F., Hoffmann, Florian, Boettiger, Bernd W., Weinmann-Menke, Julia, Kersten, Alexander, Berlit, Peter, Krawczyk, Marcin, Nehls, Wiebke, Fichtner, Falk, Laudi, Sven, Stegemann, Miriam, Skoetz, Nicole, Nothacker, Monika, Marx, Gernot, Karagiannidis, Christian, Kluge, Stefan, Malin, Jakob J., Spinner, Christoph D., Janssens, Uwe, Welte, Tobias, Weber-Carstens, Steffen, Schaelte, Gereon, Gastmeier, Petra, Langer, Florian, Wepler, Martin, Westhoff, Michael, Pfeifer, Michael, Rabe, Klaus F., Hoffmann, Florian, Boettiger, Bernd W., Weinmann-Menke, Julia, Kersten, Alexander, Berlit, Peter, Krawczyk, Marcin, Nehls, Wiebke, Fichtner, Falk, Laudi, Sven, Stegemann, Miriam, Skoetz, Nicole, Nothacker, Monika, Marx, Gernot, Karagiannidis, Christian, and Kluge, Stefan

Published
2022

156. Standardized contrast-enhanced ultrasound (CEUS) in clinical acute and emergency medicine and critical care (CEUS Acute) Consensus statement of DGIIN, DIVI, DGINA, DGAI, DGK, oGUM, SGUM and DEGUM

Author

Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Joerg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, Dietrich, Christoph F., Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Joerg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, and Dietrich, Christoph F.

Abstract

The present document describes the possible applications of contrast-enhanced ultrasound (CEUS) in emergency examinations. Guidelines on contrast medium ultrasound in acute and emergency care and intensive care medicine have not yet been published. Evidence-based CEUS guidelines were first provided by the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) and the World Federation for Ultrasound in Medicine and Biology (WFUMB). The presented recommendations describe the possible applications and protocols of CEUS in acute care.

Published
2022

157. Standardized contrast-enhanced ultrasound (CEUS) in clinical acute and emergency medicine and critical care (CEUS Acute) Consensus statement of DGIIN, DIVI, DGINA, DGAI, DGK, oGUM, SGUM and DEGUM (10.1007/s00063-021-00891-4, 2021)

Author

Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Jorg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, Dietrich, Christoph F., Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Jorg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, and Dietrich, Christoph F.

Published
2022

158. Standardized contrast-enhanced ultrasound (CEUS) in clinical acute and emergency medicine as well as critical care (CEUS Acute) Consensus statement of the DGIIN, DIVI, DGINA, DGAI, DGK, oGUM, SGUM und DEGUM

Author

Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Joerg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, Dietrich, Christoph F., Michels, Guido, Horn, Rudolf, Helfen, Andreas, Hagendorff, Andreas, Jung, Christian, Hoffmann, Beatrice, Jaspers, Natalie, Kinkel, Horst, Greim, Clemens-Alexander, Knebel, Fabian, Bauersachs, Johann, Busch, Hans-Joerg, Kiefl, Daniel, Spiel, Alexander O., Marx, Gernot, and Dietrich, Christoph F.

Published
2022

159. Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

Author

Schreibing, Felix, Hannani, Monica T., Kim, Hyojin, Nagai, James S., Ticconi, Fabio, Fewings, Eleanor, Bleckwehl, Tore, Begemann, Matthias, Torow, Natalia, Kuppe, Christoph, Kurth, Ingo, Kranz, Jennifer, Frank, Dario, Anslinger, Teresa M., Ziegler, Patrick, Kraus, Thomas, Enczmann, Jürgen, Balz, Vera, Windhofer, Frank, Balfanz, Paul, Kurts, Christian, Marx, Gernot, Marx, Nikolaus, Dreher, Michael, Schneider, Rebekka K., Saez-Rodriguez, Julio, Costa, Ivan, Hayat, Sikander, Kramann, Rafael, Schreibing, Felix, Hannani, Monica T., Kim, Hyojin, Nagai, James S., Ticconi, Fabio, Fewings, Eleanor, Bleckwehl, Tore, Begemann, Matthias, Torow, Natalia, Kuppe, Christoph, Kurth, Ingo, Kranz, Jennifer, Frank, Dario, Anslinger, Teresa M., Ziegler, Patrick, Kraus, Thomas, Enczmann, Jürgen, Balz, Vera, Windhofer, Frank, Balfanz, Paul, Kurts, Christian, Marx, Gernot, Marx, Nikolaus, Dreher, Michael, Schneider, Rebekka K., Saez-Rodriguez, Julio, Costa, Ivan, Hayat, Sikander, and Kramann, Rafael

Abstract

Introduction: SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants. Methods: We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8+ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19. Results: We observed increased CD8+ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8+ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8+ T cells revealed heterogeneity among CD16+ NK-like CD8+ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions. Discussion: We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8+ effector T cells, ultimately resulting in the appearance of NK-like CD8+ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8+ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8+ T cells in COVID-19 severity.

Published
2022

168. Inhibition of Macrophage Migration Inhibitory Factor Activity Attenuates Haemorrhagic Shock-Induced Multiple Organ Dysfunction in Rats

Author

Patel, Nikita M., primary, Yamada, Noriaki, additional, Oliveira, Filipe R. M. B., additional, Stiehler, Lara, additional, Zechendorf, Elisabeth, additional, Hinkelmann, Daniel, additional, Kraemer, Sandra, additional, Stoppe, Christian, additional, Collino, Massimo, additional, Collotta, Debora, additional, Alves, Gustavo Ferreira, additional, Ramos, Hanna Pillmann, additional, Sordi, Regina, additional, Marzi, Ingo, additional, Relja, Borna, additional, Marx, Gernot, additional, Martin, Lukas, additional, and Thiemermann, Christoph, additional

Published
2022
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170. Theranostic Trigger‐Responsive Carbon Monoxide‐Generating Microbubbles

Author

Pathak, Vertika, primary, Roemhild, Karolin, additional, Schipper, Sandra, additional, Groß‐Weege, Nicolas, additional, Nolte, Teresa, additional, Ruetten, Stephan, additional, Buhl, Eva Miriam, additional, El Shafei, Asmaa, additional, Weiler, Marek, additional, Martin, Lukas, additional, Marx, Gernot, additional, Schulz, Volkmar, additional, Kiessling, Fabian, additional, Lammers, Twan, additional, and Koczera, Patrick, additional

Published
2022
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171. An Innovative Telemedical Network to Improve Infectious Disease Management in Critically Ill Patients and Outpatients (TELnet@NRW): Stepped-Wedge Cluster Randomized Controlled Trial

Author

Marx, Gernot, primary, Greiner, Wolfgang, additional, Juhra, Christian, additional, Elkenkamp, Svenja, additional, Gensorowsky, Daniel, additional, Lemmen, Sebastian, additional, Englbrecht, Jan, additional, Dohmen, Sandra, additional, Gottschalk, Antje, additional, Haverkamp, Miriam, additional, Hempen, Annette, additional, Flügel-Bleienheuft, Christian, additional, Bause, Daniela, additional, Schulze-Steinen, Henna, additional, Rademacher, Susanne, additional, Kistermann, Jennifer, additional, Hoch, Stefan, additional, Beckmann, Hans-Juergen, additional, Lanckohr, Christian, additional, Lowitsch, Volker, additional, Peine, Arne, additional, Juzek-Kuepper, Fabian, additional, Benstoem, Carina, additional, Sperling, Kathrin, additional, and Deisz, Robert, additional

Published
2022
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175. sj-docx-1-dhj-10.1177_20552076221116772 - Supplemental material for Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients

Author

Fritsch, Sebastian J, Blankenheim, Andrea, Wahl, Alina, Hetfeld, Petra, Maassen, Oliver, Deffge, Saskia, Kunze, Julian, Rossaint, Rolf, Riedel, Morris, Marx, Gernot, and Bickenbach, Johannes

Subjects
FOS: Computer and information sciences, 200299 Cultural Studies not elsewhere classified, Science Policy, FOS: Clinical medicine, FOS: Political science, 150310 Organisation and Management Theory, Cardiology, 111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences, 110306 Endocrinology, 110308 Geriatrics and Gerontology, 99999 Engineering not elsewhere classified, FOS: Sociology, FOS: Economics and business, 111099 Nursing not elsewhere classified, FOS: Other engineering and technologies, Sociology, 111708 Health and Community Services, Anthropology, 111702 Aged Health Care, 89999 Information and Computing Sciences not elsewhere classified, FOS: Other humanities, 160512 Social Policy, 111299 Oncology and Carcinogenesis not elsewhere classified
Abstract

Supplemental material, sj-docx-1-dhj-10.1177_20552076221116772 for Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients by Sebastian J Fritsch, Andrea Blankenheim, Alina Wahl, Petra Hetfeld, Oliver Maassen, Saskia Deffge, Julian Kunze, Rolf Rossaint, Morris Riedel, Gernot Marx and Johannes Bickenbach in Digital Health

Published
2022
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176. sj-docx-2-dhj-10.1177_20552076221116772 - Supplemental material for Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients

Author

Fritsch, Sebastian J, Blankenheim, Andrea, Wahl, Alina, Hetfeld, Petra, Maassen, Oliver, Deffge, Saskia, Kunze, Julian, Rossaint, Rolf, Riedel, Morris, Marx, Gernot, and Bickenbach, Johannes

Subjects
FOS: Computer and information sciences, 200299 Cultural Studies not elsewhere classified, Science Policy, FOS: Clinical medicine, FOS: Political science, 150310 Organisation and Management Theory, Cardiology, 111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences, 110306 Endocrinology, 110308 Geriatrics and Gerontology, 99999 Engineering not elsewhere classified, FOS: Sociology, FOS: Economics and business, 111099 Nursing not elsewhere classified, FOS: Other engineering and technologies, Sociology, 111708 Health and Community Services, Anthropology, 111702 Aged Health Care, 89999 Information and Computing Sciences not elsewhere classified, FOS: Other humanities, 160512 Social Policy, 111299 Oncology and Carcinogenesis not elsewhere classified
Abstract

Supplemental material, sj-docx-2-dhj-10.1177_20552076221116772 for Attitudes and perception of artificial intelligence in healthcare: A cross-sectional survey among patients by Sebastian J Fritsch, Andrea Blankenheim, Alina Wahl, Petra Hetfeld, Oliver Maassen, Saskia Deffge, Julian Kunze, Rolf Rossaint, Morris Riedel, Gernot Marx and Johannes Bickenbach in Digital Health

Published
2022
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177. Key summary of German national treatment guidance for hospitalized COVID-19 patients

Author

Malin, Jakob J., Spinner, Christoph D., Janssens, Uwe, Welte, Tobias, Weber-Carstens, Steffen, Schälte, Gereon, Gastmeier, Petra, Langer, Florian, Wepler, Martin, Westhoff, Michael, Pfeifer, Michael, Rabe, Klaus F., Hoffmann, Florian, Böttiger, Bernd W., Weinmann-Menke, Julia, Kersten, Alexander Martin, Berlit, Peter, Krawczyk, Marcin, Nehls, Wiebke, Fichtner, Falk, Laudi, Sven, Stegemann, Miriam, Skoetz, Nicole, Nothacker, Monika, Marx, Gernot, Karagiannidis, Christian, and Kluge, Stefan

Abstract

Infection 50(1), 93-106 (2022). doi:10.1007/s15010-021-01645-2 special issue: "COVID-19 / SARS-CoV-2", Published by Springer, Berlin ; Heidelberg

Published
2022

179. Erratum to: Practice of hemodynamic monitoring and management in German, Austrian, and Swiss intensive care units: the multicenter cross-sectional ICU-CardioMan Study

Author

Funcke, Sandra, Sander, Michael, Goepfert, Matthias S., Groesdonk, Heinrich, Heringlake, Matthias, Hirsch, Jan, Kluge, Stefan, Krenn, Claus, Maggiorini, Marco, Meybohm, Patrick, Salzwedel, Cornelie, Saugel, Bernd, Wagenpfeil, Gudrun, Wagenpfeil, Stefan, Reuter, Daniel A., Albuszies, Gerd Werner, Alexi, Rudolf, Bauer, Andreas, Bergt, Stefan, Berroth, Ralph, Bloos, Frank, Bracht, Hendrick, Brass, Patrick, Breukelmann, Dirk, Brunauer, Andreas, Burghardt, Matthias, Christ, Michael, Dietrich, Beatrix, Diwok, Christian, Dohmen, Christian, Dueck, Michael, Eichler, Ingolf, Engel, Joerg, Erb, Regula, Eyer, Florian, Faltlhauser, Andreas, Feld, Florian, Fricke, Ann Kristin, Fröhmert, Bernd, Funk, Wolfgang, Genzwuerker, Harald, Giesen, Hans-Ulrich, Grafelmann, Hans-Hinrich, Grosse, Joachim, Gruss, Marco, Gussone, Christoph, Haake, Hendrik, Heim, Markus, Heinemann, Anke, Henrich, Michael, Herff, Holger, Hermanns, Guido, Hofmann-Kiefer, Klaus, Hohn, Andreas, Honig, Frauke, Huebner, Tobias, Hueppe, Tobias, Huelpuesch, Nadine, Ibba, Judith, Ibscher, Ricarda, Irlbeck, Michael, Kalbhenn, Johannes, Kapfer, Barbara, Kaufmann, Ines, Kirschning, Thomas, Kloesel, Stephan F., Kobusch, Karin, Kochanek, Matthias, Kozian, Alf, Krull, Oliver, Kuhl, Thomas, Lindau, Simone, Lorenz, Ingo, Maisch, Stefan, Marx, Gernot, Marx, Thomas, Moerer, Onnen, Moser, Benjamin, Mueller, Ulrike, Nicolas, Stefan, Ney, Ludwig, Niedeggen, Andreas, Otto, Stefan, Pilarczyk, Kevin, Popp, Matthias, Putensen, Christian, Quabach, Ralf, Ragaller, Maximilian, Ramminger, Axel, Rasche, Stefan, Rehberg, Sebastian, Reinges, Marcus H. T., Riessen, Reimer, Roehrich, Knut-Age, Roehrig, Rainer, Roesner, Jan P., Ruschulte, Heiner, Sakka, Samir G., Schellhaass, Alexander, Schewe, Jens-Christian, Schirotzek, Ingo, Schley, Jörn V., Schmitt, Alexander, Schott, Martin, Schramm, Patrick, Schroeder, Stefan, Schuette, Jan-Karl, Schuld, Alexander, Schwarzkopf, Konrad, Seiler, Julia, Selleng, Sixten, Simon, Philipp, Skitek, Kornel, Soukup, Jens, Stephan, Markus, Stetefeld, Henning, Suchodolski, Klaudiusz, Toennies, Stefan, Trummer, Georg, Wattenberg, Michael, Wirtz, Stefan P., Wrigge, Hermann, Wunder, Christian, Yildirim, Cagatay, Zacharowski, Kai, Zarbock, Alexander, Zausig, York, Zoller, Michael, and for the ICU-CardioMan Investigators

Published
2017
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180. Standardisierte Kontrastmittelsonographie (CEUS) in der klinischen Akut- und Notfallmedizin sowie Intensivmedizin (CEUS-Akut)

Author

Michels, Guido, primary, Horn, Rudolf, additional, Helfen, Andreas, additional, Hagendorff, Andreas, additional, Jung, Christian, additional, Hoffmann, Beatrice, additional, Jaspers, Natalie, additional, Kinkel, Horst, additional, Greim, Clemens-Alexander, additional, Knebel, Fabian, additional, Bauersachs, Johann, additional, Busch, Hans-Jörg, additional, Kiefl, Daniel, additional, Spiel, Alexander O., additional, Marx, Gernot, additional, and Dietrich, Christoph F., additional

Published
2022
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181. Long COVID‐19: Objectifying most self‐reported neurological symptoms

Author

Bungenberg, Julia, primary, Humkamp, Karen, additional, Hohenfeld, Christian, additional, Rust, Marcus Immanuel, additional, Ermis, Ummehan, additional, Dreher, Michael, additional, Hartmann, Niels‐Ulrik Korbinian, additional, Marx, Gernot, additional, Binkofski, Ferdinand, additional, Finke, Carsten, additional, Schulz, Jörg B., additional, Costa, Ana Sofia, additional, and Reetz, Kathrin, additional

Published
2022
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186. Sepsis

Author

Schürholz, Tobias, primary and Marx, Gernot, additional

Published
2015
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188. Volumentherapie

Author

Simon, Tim-Philipp, primary, Zacharowski, Kai, additional, and Marx, Gernot, additional

Published
2014
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191. Swarm Learning for decentralized and confidential clinical machine learning

Author

Warnat-Herresthal, Stefanie, Schultze, Hartmut, Ktena, Sofia, Franzenburg, Sören, Frick, Julia-Stefanie, Gabernet, Gisela, Gagneur, Julien, Ganzenmueller, Tina, Gauder, Marie, Geißert, Janina, Goesmann, Alexander, Göpel, Siri, Grundhoff, Adam, Tran, Florian, Grundmann, Hajo, Hain, Torsten, Hanses, Frank, Hehr, Ute, Heimbach, André, Hoeper, Marius, Horn, Friedemann, Hübschmann, Daniel, Hummel, Michael, Iftner, Thomas, Bitzer, Michael, Iftner, Angelika, Illig, Thomas, Janssen, Stefan, Kalinowski, Jörn, Kallies, René, Kehr, Birte, Keppler, Oliver T, Klein, Christoph, Knop, Michael, Kohlbacher, Oliver, Ossowski, Stephan, Köhrer, Karl, Korbel, Jan, Kremsner, Peter G, Kühnert, Denise, Landthaler, Markus, Li, Yang, Ludwig, Kerstin U, Makarewicz, Oliwia, Marz, Manja, McHardy, Alice C, Casadei, Nicolas, Mertes, Christian, Münchhoff, Maximilian, Nahnsen, Sven, Nöthen, Markus M., Ntoumi, Francine, Overmann, Jörg, Peter, Silke, Pfeffer, Klaus, Pink, Isabell, Poetsch, Anna R, Herr, Christian, Protzer, Ulrike, Pühler, Alfred, Rajewsky, Nikolaus, Ralser, Markus, Reiche, Kristin, Ripke, Stephan, da Rocha, Ulisses Nunes, Saliba, Antoine-Emmanuel, Sander, Leif Erik, Sawitzki, Birgit, Petersheim, Daniel, Scheithauer, Simone, Schiffer, Philipp, Schmid-Burgk, Jonathan, Schneider, Wulf, Schulte, Eva-Christina, Sczyrba, Alexander, Sharaf, Mariam L, Singh, Yogesh, Sonnabend, Michael, Stegle, Oliver, Behrends, Uta, Stoye, Jens, Vehreschild, Janne, Velavan, Thirumalaisamy P, Vogel, Jörg, Volland, Sonja, von Kleist, Max, Walker, Andreas, Walter, Jörn, Wieczorek, Dagmar, Winkler, Sylke, Kern, Fabian, Ziebuhr, John, Fehlmann, Tobias, Shastry, Krishnaprasad Lingadahalli, Schommers, Philipp, Lehmann, Clara, Augustin, Max, Rybniker, Jan, Altmüller, Janine, Mishra, Neha, Bernardes, Joana P, Krämer, Benjamin, Bonaguro, Lorenzo, Schulte-Schrepping, Jonas, Manamohan, Sathyanarayanan, De Domenico, Elena, Siever, Christian, Kraut, Michael, Desai, Milind, Monnet, Bruno, Saridaki, Maria, Siegel, Charles Martin, Drews, Anna, Nuesch Germano, Melanie, Theis, Heidi, Mukherjee, Saikat, Heyckendorf, Jan, Schreiber, Stefan, Kim-Hellmuth, Sarah, Study, COVID-19 Aachen, Nattermann, Jacob, Skowasch, Dirk, Kurth, Ingo, Keller, Andreas, Bals, Robert, Nürnberg, Peter, Garg, Vishesh, Rieß, Olaf, Rosenstiel, Philip, Netea, Mihai G, Theis, Fabian, Mukherjee, Sach, Backes, Michael, Aschenbrenner, Anna C, Ulas, Thomas, Initiative, Deutsche COVID-19 Omics, Breteler, Monique, Sarveswara, Ravi, Giamarellos-Bourboulis, Evangelos J, Kox, Matthijs, Becker, Matthias, Cheran, Sorin, Woodacre, Michael S, Goh, Eng Lim, Schultze, Joachim L, Balfanz, Paul, Eggermann, Thomas, Boor, Peter, Händler, Kristian, Hausmann, Ralf, Kuhn, Hannah, Isfort, Susanne, Stingl, Julia Carolin, Schmalzing, Günther, Kuhl, Christiane K, Röhrig, Rainer, Marx, Gernot, Uhlig, Stefan, Dahl, Edgar, Pickkers, Peter, Müller-Wieland, Dirk, Dreher, Michael, Marx, Nikolaus, Angelov, Angel, Bartholomäus, Alexander, Becker, Anke, Bezdan, Daniela, Blumert, Conny, Bonifacio, Ezio, Bork, Peer, Aziz, Ahmad, Boyke, Bunk, Blum, Helmut, Clavel, Thomas, Colome-Tatche, Maria, Cornberg, Markus, De La Rosa Velázquez, Inti Alberto, Diefenbach, Andreas, Dilthey, Alexander, Fischer, Nicole, Förstner, Konrad, and Stem Cell Aging Leukemia and Lymphoma (SALL)

Subjects
Lung Diseases, Male, 0301 basic medicine, Cancer Research, Computer science, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Privacy laws of the United States, Datasets as Topic, computer.software_genre, Disease Outbreaks, 0302 clinical medicine, Software, diagnosis [Leukemia], pathology [Leukemia], Leukocytes, Computational models, Use case, Confidentiality, 030212 general & internal medicine, Precision Medicine, Edge computing, Leukemia, Multidisciplinary, Swarm behaviour, diagnosis [Lung Diseases], ddc, 3. Good health, diagnosis [Tuberculosis], Female, ddc:500, Clinical Decision-Making, Predictive medicine, methods [Clinical Decision-Making], pathology [Leukocytes], Machine learning, Article, 03 medical and health sciences, methods [Precision Medicine], Blockchain, Humans, Tuberculosis, trends [Machine Learning], business.industry, COVID-19, Diagnostic markers, diagnosis [COVID-19], epidemiology [COVID-19], Precision medicine, 030104 developmental biology, Cardiovascular and Metabolic Diseases, Viral infection, Artificial intelligence, business, computer
Abstract

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine., Swarm Learning is a decentralized machine learning approach that outperforms classifiers developed at individual sites for COVID-19 and other diseases while preserving confidentiality and privacy.

Published
2021

192. Adrenomedullin als Biomarker für den Schweregrad einer aneurysmatischen Subarachnoidalblutung und delayed cerebral ischemia

Author

Veldeman, Michael, Simon, Tim Phillip, Dogan, Rabia, Weiss, Miriam, Stoppe, Christian, Marx, Gernot, Clusmann, Hans, and Schubert, Gerrit Alexander

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Objective: Adrenomedullin (ADM) is a potent vasodilator which has been identified as a promising marker of mortality and outcome in sepsis, heart failure and after major surgery. A recently developed assay specific for biologically active (bio-ADM) has not yet been assessed in patients suffering aneurysmal[for full text, please go to the a.m. URL], 72. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), Joint Meeting mit der Polnischen Gesellschaft für Neurochirurgie

Published
2021

193. Differences and Similarities Among Coronavirus Disease 2019 Patients Treated in Seven ICUs in Three Countries Within One Region

Author

Mesotten, Dieter, primary, Meijs, Daniek A. M., additional, van Bussel, Bas C. T., additional, Stessel, Björn, additional, Mehagnoul-Schipper, Jannet, additional, Hana, Anisa, additional, Scheeren, Clarissa I. E., additional, Strauch, Ulrich, additional, van de Poll, Marcel C. G., additional, Ghossein-Doha, Chahinda, additional, Buhre, Wolfgang F. F. A., additional, Bickenbach, Johannes, additional, Vander Laenen, Margot, additional, Marx, Gernot, additional, and van der Horst, Iwan C. C., additional

Published
2021
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194. An Innovative Telemedical Network to Improve Infectious Disease Management in Critically Ill Patients and Outpatients (TELnet@NRW): Stepped-Wedge Cluster Randomized Controlled Trial (Preprint)

Author

Marx, Gernot, primary, Greiner, Wolfgang, additional, Juhra, Christian, additional, Elkenkamp, Svenja, additional, Gensorowsky, Daniel, additional, Lemmen, Sebastian, additional, Englbrecht, Jan, additional, Dohmen, Sandra, additional, Gottschalk, Antje, additional, Haverkamp, Miriam, additional, Hempen, Annette, additional, Flügel-Bleienheuft, Christian, additional, Bause, Daniela, additional, Schulze-Steinen, Henna, additional, Rademacher, Susanne, additional, Kistermann, Jennifer, additional, Hoch, Stefan, additional, Beckmann, Hans-Juergen, additional, Lanckohr, Christian, additional, Lowitsch, Volker, additional, Peine, Arne, additional, Juzek-Kuepper, Fabian, additional, Benstoem, Carina, additional, Sperling, Kathrin, additional, and Deisz, Robert, additional

Published
2021
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196. Evaluation to improve the quality of medication preparation and administration in pediatric and adult intensive care units

Author

Hermanspann,Theresa, van der Linden,Eva, Schoberer,Mark, Fitzner,Christina, Orlikowsky,Thorsten, Marx,Gernot, and Eisert,Albrecht

Subjects
medication errors, health care facilities, manpower, and services, Drug, Healthcare and Patient Safety, intravenous medication, patient safety, medication safety, Original Research, quality improvement
Abstract

Theresa Hermanspann,1,2 Eva van der Linden,2 Mark Schoberer,2 Christina Fitzner,3,4 Thorsten Orlikowsky,2 Gernot Marx,5 Albrecht Eisert1,6 1Hospital Pharmacy, RWTH Aachen University Hospital, Aachen, Germany; 2Department of Pediatric and Adolescent Medicine, Section of Neonatology, RWTH Aachen University Hospital, Aachen, Germany; 3Department of Medical Statistics, Medical Faculty RWTH Aachen University, Aachen, Germany; 4Department of Anaesthesiology, RWTH Aachen University Hospital, Aachen, Germany; 5Department of Intensive Care Medicine, RWTH Aachen University Hospital, Aachen, Germany; 6Institute of Pharmacology and Toxicology, Medical Faculty RWTH Aachen University, Aachen, Germany Purpose: To determine the type, frequency, and factors associated with medication preparation and administration errors in adult intensive care units (ICUs) and neonatal ICUs (NICUs)/pediatric ICUs (PICUs).Patients and methods: We conducted a prospective direct observation study in an adult ICU and NICU/PICU in a tertiary university hospital. Between June 2012 and June 2013, a clinical pharmacist and medical student observed the nursing care staff on weekdays during the preparation and administration of intravenous drugs. We analyzed the frequency and type of preparation and administration errors and factors associated with errors.Results: Six hundred and three preparations in the adult ICU and 281 in the NICU/PICU were observed. Three hundred and eighty-five errors occurred in the adult ICU and 38 in the NICU/PICU. There were 5,040 and 2,514 error opportunities, with overall error rates of 7.6% and 1.5%, respectively. The total opportunities for error meant each single step of preparation and administration that was relevant for the drug. Most errors applied to the category “uniform mixing” (adult ICU: n=227, 59%; NICU/PICU: n=14, 37%). The multivariate logistic regression results showed a significantly different influence of the “preparation type” for the adult ICU compared with the NICU/PICU with regard to the occurrence of an error. Preparations for adult patients of the LCD type (liquid concentrate with diluent into syringe or infusion bag) were more often associated with errors than the P (powder in a glass vial that must be reconstituted and diluted if necessary), P=0.012, and LC (liquid concentrate into syringe), P=0.002 type.Conclusion: “Uniform mixing” was the most erroneous preparation step in intravenous drug preparations in two ICUs. Improvement of nurse training and the preparation of prefilled syringes in the pharmacy might reduce errors and improve the quality and safety of drug therapy. Keywords: intravenous medication, medication errors, medication safety, patient safety, quality improvement

Published
2019

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