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1. Dynamics of disease characteristics and clinical management of critically ill COVID-19 patients over the time course of the pandemic: an analysis of the prospective, international, multicentre RISC-19-ICU registry

Author

Pedro David Wendel-Garcia, André Moser, Marie-Madlen Jeitziner, Hernán Aguirre-Bermeo, Pedro Arias-Sanchez, Janina Apolo, Ferran Roche-Campo, Diego Franch-Llasat, Gian-Reto Kleger, Claudia Schrag, Urs Pietsch, Miodrag Filipovic, Sascha David, Klaus Stahl, Souad Bouaoud, Amel Ouyahia, Patricia Fodor, Pascal Locher, Martin Siegemund, Nuria Zellweger, Sara Cereghetti, Peter Schott, Gianfilippo Gangitano, Maddalena Alessandra Wu, Mario Alfaro-Farias, Gerardo Vizmanos-Lamotte, Hatem Ksouri, Nadine Gehring, Emanuele Rezoagli, Fabrizio Turrini, Herminia Lozano-Gómez, Andrea Carsetti, Raquel Rodríguez-García, Bernd Yuen, Anja Baltussen Weber, Pedro Castro, Jesus Oscar Escos-Orta, Alexander Dullenkopf, Maria C. Martín-Delgado, Theodoros Aslanidis, Marie-Helene Perez, Frank Hillgaertner, Samuele Ceruti, Marilene Franchitti Laurent, Julien Marrel, Riccardo Colombo, Marcus Laube, Alberto Fogagnolo, Michael Studhalter, Tobias Wengenmayer, Emiliano Gamberini, Christian Buerkle, Philipp K. Buehler, Stefanie Keiser, Muhammed Elhadi, Jonathan Montomoli, Philippe Guerci, Thierry Fumeaux, Reto A. Schuepbach, Stephan M. Jakob, Yok-Ai Que, Matthias Peter Hilty, and the RISC-19-ICU Investigators

Subjects
COVID-19, Pandemic, Intensive care unit, ARDS, Disease dynamics, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background It remains elusive how the characteristics, the course of disease, the clinical management and the outcomes of critically ill COVID-19 patients admitted to intensive care units (ICU) worldwide have changed over the course of the pandemic. Methods Prospective, observational registry constituted by 90 ICUs across 22 countries worldwide including patients with a laboratory-confirmed, critical presentation of COVID-19 requiring advanced organ support. Hierarchical, generalized linear mixed-effect models accounting for hospital and country variability were employed to analyse the continuous evolution of the studied variables over the pandemic. Results Four thousand forty-one patients were included from March 2020 to September 2021. Over this period, the age of the admitted patients (62 [95% CI 60–63] years vs 64 [62–66] years, p

Published
2022
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2. Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Author

Jonathan Montomoli, Luca Romeo, Sara Moccia, Michele Bernardini, Lucia Migliorelli, Daniele Berardini, Abele Donati, Andrea Carsetti, Maria Grazia Bocci, Pedro David Wendel Garcia, Thierry Fumeaux, Philippe Guerci, Reto Andreas Schüpbach, Can Ince, Emanuele Frontoni, Matthias Peter Hilty, Mario Alfaro-Farias, MD, Gerardo Vizmanos-Lamotte, MD, PhD, Thomas Tschoellitsch, MD, Jens Meier, MD, Hernán Aguirre-Bermeo, MD, PhD, Janina Apolo, BSc, Alberto Martínez, MD, Geoffrey Jurkolow, MD, Gauthier Delahaye, MD, Emmanuel Novy, MD, Marie-Reine Losser, MD, PhD, Tobias Wengenmayer, MD, Jonathan Rilinger, MD, Dawid L. Staudacher, MD, Sascha David, MD, Tobias Welte, MD, Klaus Stahl, MD, “Agios Pavlos”, Theodoros Aslanidis, MD, PhD, Anita Korsos, MD, Barna Babik, MD, PhD, Reza Nikandish, MD, Emanuele Rezoagli, MD, PhD, Matteo Giacomini, MD, Alice Nova, MD, Alberto Fogagnolo, MD, Savino Spadaro, MD, PhD, Roberto Ceriani, MD, Martina Murrone, MD, Maddalena A. Wu, MD, Chiara Cogliati, MD, Riccardo Colombo, MD, Emanuele Catena, MD, Fabrizio Turrini, MD, MSc, Maria Sole Simonini, MD, Silvia Fabbri, MD, Antonella Potalivo, MD, Francesca Facondini, MD, Gianfilippo Gangitano, MD, Tiziana Perin, MD, Maria Grazia Bocci, MD, Massimo Antonelli, MD, Diederik Gommers, MD, PhD, Raquel Rodríguez-García, MD, Jorge Gámez-Zapata, MD, Xiana Taboada-Fraga, MD, Pedro Castro, MD, Adrian Tellez, MD, Arantxa Lander-Azcona, MD, Jesús Escós-Orta, MD, Maria C. Martín-Delgado, MD, Angela Algaba-Calderon, MD, Diego Franch-Llasat, MD, Ferran Roche-Campo, MD, PhD, Herminia Lozano-Gómez, MD, Begoña Zalba-Etayo, MD, PhD, Marc P. Michot, MD, Alexander Klarer, Rolf Ensner, MD, Peter Schott, MD, Severin Urech, MD, Nuria Zellweger, Lukas Merki, MD, Adriana Lambert, MD, Marcus Laube, MD, Marie M. Jeitziner, RN, PhD, Beatrice Jenni-Moser, RN, MSc, Jan Wiegand, MD, Bernd Yuen, MD, Barbara Lienhardt-Nobbe, Andrea Westphalen, MD, Petra Salomon, MD, Iris Drvaric, MD, Frank Hillgaertner, MD, Marianne Sieber, Alexander Dullenkopf, MD, Lina Petersen, MD, Ivan Chau, MD, Hatem Ksouri, MD, PhD, Govind Oliver Sridharan, MD, Sara Cereghetti, MD, Filippo Boroli, MD, Jerome Pugin, MD, PhD, Serge Grazioli, MD, Peter C. Rimensberger, MD, Christian Bürkle, MD, Julien Marrel, MD, Mirko Brenni, MD, Isabelle Fleisch, MD, Jerome Lavanchy, MD, Marie-Helene Perez, MD, Anne-Sylvie Ramelet, MD, Anja Baltussen Weber, MD, Peter Gerecke, MD, Andreas Christ, MD, Samuele Ceruti, MD, Andrea Glotta, MD, Katharina Marquardt, MD, Karim Shaikh, MD, Tobias Hübner, MD, Thomas Neff, MD, Hermann Redecker, MD, Mallory Moret-Bochatay, MD, FriederikeMeyer zu Bentrup, MD, MBA, Michael Studhalter, MD, Michael Stephan, MD, Jan Brem, MD, Nadine Gehring, MD, Daniela Selz, MD, Didier Naon, MD, Gian-Reto Kleger, MD, Urs Pietsch, MD, Miodrag Filipovic, MD, Anette Ristic, MD, Michael Sepulcri, MD, Antje Heise, MD, Marilene Franchitti Laurent, MD, Jean-Christophe Laurent, MD, Pedro D. Wendel Garcia, MSc, Reto Schuepbach, MD, Dorothea Heuberger, PhD, Philipp Bühler, MD, Silvio Brugger, MD, PhD, Patricia Fodor, MD, Pascal Locher, MD, Giovanni Camen, MD, Tomislav Gaspert, MD, Marija Jovic, MD, Christoph Haberthuer, MD, Roger F. Lussman, MD, and Elif Colak, MD

Subjects
Machine learning, Extreme gradient boosting (XGBoost), COVID-19, Multiple organ failure, Clinical decision support system (CDSS), Organ dysfunction score, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs. 0.69, P

Published
2021
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3. Multilocular Hepatic Abscess Formation and Sepsis due to Yersinia enterocolitica in a Patient with Hereditary Hemochromatosis and Type 2 Diabetes Mellitus

Author

Matthias Sauter, Stephan R. Vavricka, Pascal Locher, Benjamin Preiswerk, Dominik Weishaupt, Christoph A. Meier, and Benjamin Misselwitz

Subjects
Hepatic abscess, Yersinia enterocolitica, Sepsis, Hemochromatosis, Iron overload, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Infection with Yersinia enterocolitica (YE) typically presents with mild gastroenteritis without systemic infection. However, systemic YE infection has been described in states of iron overload. We present the case of a patient with sepsis with hepatic abscesses due to YE infection. Workup revealed a past diagnosis of diabetes mellitus and hemochromatosis which had been untreated for the previous 5 years due to patient refusal. This case highlights risk factors for systemic infection with YE. A high degree of suspicion for YE infection is warranted in patients with iron overload, diabetes mellitus, or immunosuppression.

Published
2017
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4. Ein saurer Entzug

Author

Niklas Stauffer and Pascal Locher

Subjects
General Medicine
Published
2023

5. Machine learning using the Extreme Gradient Boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Author

Marie M. Jeitziner, Iris Drvaric, Jan Wiegand, Abele Donati, Janina Apolo, Emanuele Rezoagli, Jesús Escós-Orta, Herminia Lozano-Gómez, Mirko Brenni, Giovanni Camen, Frank Hillgaertner, Sara Moccia, Antje Heise, Alexander Dullenkopf, Michael Stephan, Can Ince, Marcus Laube, Julien Marrel, Michele Bernardini, Barbara Lienhardt-Nobbe, Hernán Aguirre-Bermeo, Alberto Fogagnolo, Dorothea M. Heuberger, Severin Urech, Reto A. Schuepbach, Andrea Glotta, Samuele Ceruti, Isabelle Fleisch, Marc P. Michot, Alice Nova, Matthias P. Hilty, Tomislav Gaspert, Gianfilippo Gangitano, Savino Spadaro, Ivan Chau, Daniele Berardini, Tiziana Perin, Andrea Westphalen, Marie-Reine Losser, Hatem Ksouri, Marie-Hélène Perez, Theodoros Aslanidis, Christoph Haberthuer, Gerardo Vizmanos-Lamotte, Jorge Gámez-Zapata, Filippo Boroli, Adriana Lambert, Serge Grazioli, Petra Salomon, Christian Bürkle, Didier Naon, Philipp Bühler, Dawid L. Staudacher, Miodrag Filipovic, Hermann Redecker, Mario Alfaro-Farias, Massimo Antonelli, Rolf Ensner, Jerome Lavanchy, Lukas Merki, Roberto Ceriani, Anette Ristic, Chiara Cogliati, Reto Andreas Schüpbach, Daniela Selz, Begoña Zalba-Etayo, Anne-Sylvie Ramelet, Thierry Fumeaux, Andrea Carsetti, Peter Gerecke, Riccardo Colombo, Marilene Franchitti Laurent, Fabrizio Turrini, Tobias Wengenmayer, Tobias Welte, Philippe Guerci, Antonella Potalivo, Lucia Migliorelli, Barna Babik, Reza Nikandish, Pedro D. Wendel Garcia, Alberto Martínez, Maria Sole Simonini, Diederik Gommers, Xiana Taboada-Fraga, Jerome Pugin, Peter C. Rimensberger, Angela Algaba-Calderon, FriederikeMeyer zu Bentrup, Agios Pavlos, Thomas Tschoellitsch, Marianne Sieber, Karim Shaikh, Nuria Zellweger, Silvio Brugger, Geoffrey Jurkolow, Anja Baltussen Weber, Maria C. Martín-Delgado, Anita Korsós, Gian-Reto Kleger, Alexander Klarer, Emmanuel Novy, Diego Franch-Llasat, Adrian Tellez, Peter Schott, Jonathan Rilinger, Andreas Christ, Bernd Yuen, Jean-Christophe Laurent, Nadine Gehring, Pedro Castro, Sascha David, Francesca Facondini, Arantxa Lander-Azcona, Maria Grazia Bocci, Maddalena Alessandra Wu, Mallory Moret-Bochatay, Sara Cereghetti, Urs Pietsch, Martina Murrone, Gauthier Delahaye, Luca Romeo, Pascal Locher, Pedro David Wendel Garcia, Michael Sepulcri, Marija Jovic, Katharina Marquardt, Emanuele Frontoni, Patricia Fodor, Emanuele Catena, Tobias Hübner, Thomas Neff, Roger F. Lussman, Matteo Giacomini, Govind Oliver Sridharan, Beatrice Jenni-Moser, Jan Brem, Michael Studhalter, Elif Colak, Raquel Rodríguez-García, Silvia Fabbri, Jens Meier, Lina Petersen, Jonathan Montomoli, Ferran Roche-Campo, Klaus Stahl, Montomoli, J, Romeo, L, Moccia, S, Bernardini, M, Migliorelli, L, Berardini, D, Donati, A, Carsetti, A, Bocci, M, Wendel Garcia, P, Fumeaux, T, Guerci, P, Schupbach, R, Ince, C, Frontoni, E, Hilty, M, Alfaro-Farias, M, Vizmanos-Lamotte, G, Tschoellitsch, T, Meier, J, Aguirre-Bermeo, H, Apolo, J, Martinez, A, Jurkolow, G, Delahaye, G, Novy, E, Losser, M, Wengenmayer, T, Rilinger, J, Staudacher, D, David, S, Welte, T, Stahl, K, Pavlos, A, Aslanidis, T, Korsos, A, Babik, B, Nikandish, R, Rezoagli, E, Giacomini, M, Nova, A, Fogagnolo, A, Spadaro, S, Ceriani, R, Murrone, M, Wu, M, Cogliati, C, Colombo, R, Catena, E, Turrini, F, Simonini, M, Fabbri, S, Potalivo, A, Facondini, F, Gangitano, G, Perin, T, Grazia Bocci, M, Antonelli, M, Gommers, D, Rodriguez-Garcia, R, Gamez-Zapata, J, Taboada-Fraga, X, Castro, P, Tellez, A, Lander-Azcona, A, Escos-Orta, J, Martin-Delgado, M, Algaba-Calderon, A, Franch-Llasat, D, Roche-Campo, F, Lozano-Gomez, H, Zalba-Etayo, B, Michot, M, Klarer, A, Ensner, R, Schott, P, Urech, S, Zellweger, N, Merki, L, Lambert, A, Laube, M, Jeitziner, M, Jenni-Moser, B, Wiegand, J, Yuen, B, Lienhardt-Nobbe, B, Westphalen, A, Salomon, P, Drvaric, I, Hillgaertner, F, Sieber, M, Dullenkopf, A, Petersen, L, Chau, I, Ksouri, H, Sridharan, G, Cereghetti, S, Boroli, F, Pugin, J, Grazioli, S, Rimensberger, P, Burkle, C, Marrel, J, Brenni, M, Fleisch, I, Lavanchy, J, Perez, M, Ramelet, A, Weber, A, Gerecke, P, Christ, A, Ceruti, S, Glotta, A, Marquardt, K, Shaikh, K, Hubner, T, Neff, T, Redecker, H, Moret-Bochatay, M, Bentrup, F, Studhalter, M, Stephan, M, Brem, J, Gehring, N, Selz, D, Naon, D, Kleger, G, Pietsch, U, Filipovic, M, Ristic, A, Sepulcri, M, Heise, A, Franchitti Laurent, M, Laurent, J, Schuepbach, R, Heuberger, D, Buhler, P, Brugger, S, Fodor, P, Locher, P, Camen, G, Gaspert, T, Jovic, M, Haberthuer, C, Lussman, R, Colak, E, Biomedical Engineering and Physics, ACS - Microcirculation, Translational Physiology, ACS - Atherosclerosis & ischemic syndromes, Graduate School, AII - Infectious diseases, and University of Zurich

Subjects
610 Medicine & health, Organ dysfunction score, Machine learning, computer.software_genre, Logistic regression, Clinical decision support system, law.invention, law, Medicine, Clinical decision support system (CDSS), Receiver operating characteristic, RC86-88.9, business.industry, Clinical decision support systems, COVID-19, Medical emergencies. Critical care. Intensive care. First aid, Extreme Gradient Boosting (XGBoost), Intensive care unit, Multiple organ failure, Cohort, Population study, SOFA score, Original Article, Artificial intelligence, 10023 Institute of Intensive Care Medicine, business, Algorithm, computer, Predictive modelling
Abstract

Background : Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods : We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results : The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model {0.86 vs. 0.69, P

Published
2021

6. Prognostic factors associated with mortality risk and disease progression in 639 critically ill patients with COVID-19 in Europe: Initial report of the international RISC-19-ICU prospective observational cohort

Author

Pedro David Wendel Garcia, Thierry Fumeaux, Philippe Guerci, Dorothea Monika Heuberger, Jonathan Montomoli, Ferran Roche-Campo, Reto Andreas Schuepbach, Matthias Peter Hilty, Mario Alfaro Farias, Antoni Margarit, Gerardo Vizmanos-Lamotte, Thomas Tschoellitsch, Jens Meier, Francesco S. Cardona, Josef Skola, Lenka Horakova, Hernan Aguirre-Bermeo, Janina Apolo, Emmanuel Novy, Marie-Reine Losser, Geoffrey Jurkolow, Gauthier Delahaye, Sascha David, Tobias Welte, Tobias Wengenmayer, Dawid L. Staudacher, Theodoros Aslanidis, Barna Babik, Anita Korsos, Janos Gal, Hermann Csaba, Abele Donati, Andrea Carsetti, Fabrizio Turrini, Maria Sole Simonini, Roberto Ceriani, Martina Murrone, Emanuele Rezoagli, Giovanni Vitale, Alberto Fogagnolo, Savino Spadaro, Maddalena Alessandra Wu, Chiara Cogliati, Riccardo Colombo, Emanuele Catena, Francesca Facondini, Antonella Potalivo, Gianfilippo Gangitano, Tiziana Perin, Maria Grazia Bocci, Massimo Antonelli, Diederik Gommers, Can Ince, Eric Mayor-Vázquez, Maria Cruz, Martin Delgado, Raquel Rodriguez Garcia, Jorge Gamez Zapata, Begoña Zalba-Etayo, Herminia Lozano-Gomez, Pedro Castro, Adrian Tellez, Adriana Jacas, Guido Muñoz, Rut Andrea, Jose Ortiz, Eduard Quintana, Irene Rovira, Enric Reverter, Javier Fernandez, Miquel Ferrer, Joan R. Badia, Arantxa Lander Azcona, Jesus Escos Orta, Philipp Bühler, Silvio Brugger, Daniel Hofmaenner, Simone Unseld, Frank Ruschitzka, Mallory Moret-Bochatay, Bernd Yuen, Thomas Hillermann, Hatem Ksouri, Govind Oliver Sridharan, Anette Ristic, Michael Sepulcri, Miodrag Filipovic, Urs Pietsch, Petra Salomon, Iris Drvaric, Peter Schott, Severin Urech, Adriana Lambert, Lukas Merki, Marcus Laube, Frank Hillgaertner, Marianne Sieber, Alexander Dullenkopf, Lina Petersen, Serge Grazioli, Peter C. Rimensberger, Isabelle Fleisch, Jerome Lavanchy, Katharina Marquardt, Karim Shaikh, Hermann Redecker, Michael Stephan, Jan Brem, Bjarte Rogdo, Andre Birkenmaier, Friederike Meyer zu Bentrup, Patricia Fodor, Pascal Locher, Giovanni Camen, Martin Siegemund, Nuria Zellweger, Marie-Madlen Jeitziner, Beatrice Jenni-Moser, Christian Bürkle, Gian-Reto Kleger, Marilene Franchitti Laurent, Jean-Christophe Laurent, Tomislav Gaspert, Marija Jovic, Michael Studhalter, Christoph Haberthuer, Roger F. Lussman, Daniela Selz, Didier Naon, Romano Mauri, Samuele Ceruti, Julien Marrel, Mirko Brenni, Rolf Ensner, Nadine Gehring, Antje Heise, Tobias Huebner, Thomas A. Neff, Sara Cereghetti, Filippo Boroli, Jerome Pugin, Nandor Marczin, Joyce Wong, University of Zurich, Wendel Garcia, Pedro David, RISC-19 ICU investigators, Graduate School, Translational Physiology, ACS - Atherosclerosis & ischemic syndromes, ACS - Microcirculation, Intensive Care, Grazioli, Serge, and Rimensberger, Peter

Subjects
medicine.medical_specialty, ARDS, medicine.medical_treatment, 610 Medicine & health, Disease, 2700 General Medicine, 01 natural sciences, Article, NO, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, Internal medicine, Medicine, 030212 general & internal medicine, 0101 mathematics, Disease burden, Mechanical ventilation, lcsh:R5-920, Public health, ddc:618, Acute respiratory distress syndrome, Pandemic, business.industry, Incidence (epidemiology), 010102 general mathematics, COVID-19, General Medicine, medicine.disease, Intensive care unit, Coronavirus, Cohort, Absolute neutrophil count, 10209 Clinic for Cardiology, 10023 Institute of Intensive Care Medicine, lcsh:Medicine (General), business
Abstract

Background Coronavirus disease 2019 (COVID-19) is associated with a high disease burden with 10% of confirmed cases progressing towards critical illness. Nevertheless, the disease course and predictors of mortality in critically ill patients are poorly understood. Methods Following the critical developments in ICUs in regions experiencing early inception of the pandemic, the European-based, international RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry was created to provide near real-time assessment of patients developing critical illness due to COVID-19. Findings As of April 22, 2020, 639 critically ill patients with confirmed SARS-CoV-2 infection were included in the RISC-19-ICU registry. Of these, 398 had deceased or been discharged from the ICU. ICU-mortality was 24%, median length of stay 12 (IQR, 5-21) days. ARDS was diagnosed in 74%, with a minimum P/F-ratio of 110 (IQR, 80-148). Prone positioning, ECCO2R, or ECMO were applied in 57%. Off-label therapies were prescribed in 265 (67%) patients, and 89% of all bloodstream infections were observed in this subgroup (n = 66; RR=3·2, 95% CI [1·7-6·0]). While PCT and IL-6 levels remained similar in ICU survivors and non-survivors throughout the ICU stay (p = 0·35, 0·34), CRP, creatinine, troponin, d-dimer, lactate, neutrophil count, P/F-ratio diverged within the first seven days (p

Published
2020

7. Multilocular Hepatic Abscess Formation and Sepsis due to Yersinia enterocolitica in a Patient with Hereditary Hemochromatosis and Type 2 Diabetes Mellitus

Author

Pascal Locher, Stephan R. Vavricka, Matthias Sauter, Benjamin Misselwitz, Benjamin Preiswerk, Dominik Weishaupt, and Christoph A. Meier

Subjects
0301 basic medicine, Pathology, medicine.medical_specialty, medicine.medical_treatment, Single Case, Hepatic abscess, Gastroenterology, Sepsis, 03 medical and health sciences, Internal medicine, Diabetes mellitus, medicine, Iron overload, lcsh:RC799-869, Yersinia enterocolitica, Hemochromatosis, biology, business.industry, Type 2 Diabetes Mellitus, Immunosuppression, medicine.disease, biology.organism_classification, 030104 developmental biology, Hereditary hemochromatosis, lcsh:Diseases of the digestive system. Gastroenterology, business
Abstract

Infection with Yersinia enterocolitica (YE) typically presents with mild gastroenteritis without systemic infection. However, systemic YE infection has been described in states of iron overload. We present the case of a patient with sepsis with hepatic abscesses due to YE infection. Workup revealed a past diagnosis of diabetes mellitus and hemochromatosis which had been untreated for the previous 5 years due to patient refusal. This case highlights risk factors for systemic infection with YE. A high degree of suspicion for YE infection is warranted in patients with iron overload, diabetes mellitus, or immunosuppression.

Published
2017

8. Progressive multi-focal leukoencephalopathy as a rare lethal complication in untreated sarcoidosis

Author

Huldrych F. Günthard, Pascal Locher, Jonas Zeitz, Sabine K Hohlfeld, Esther B. Bachli, University of Zurich, and Bachli, Esther

Subjects
Adult, Lung Diseases, Male, Pathology, medicine.medical_specialty, Neurology, Sarcoidosis, Opportunistic infection, JC virus, Mirtazapine, 610 Medicine & health, Mianserin, 2700 General Medicine, medicine.disease_cause, Virus, Article, Leukoencephalopathy, 10234 Clinic for Infectious Diseases, Fatal Outcome, medicine, Demyelinating disease, Humans, Adrenergic alpha-Antagonists, business.industry, Leukoencephalopathy, Progressive Multifocal, General Medicine, medicine.disease, Dermatology, JC Virus, Radiography, DNA, Viral, business, Complication
Abstract

Progressive multi-focal leukoencephalopathy (PML) is a demyelinating disease of the central nervous system caused by reactivation of John Cunningham virus. It is an opportunistic infection affecting patients who are severely immunocompromised due to an underlying disease or secondary to immunosuppressive therapy. To date, no effective antiviral therapy has been established, though several substances are being investigated. The authors present the case of a 39-year-old previously healthy patient who was diagnosed with PML and sarcoidosis stage III without having received prior immunosuppressive treatment. The patient did not respond to treatment with mirtazapine, which has been used empirically, and deceased shortly after diagnosis.

Published
2012

9. Association of intraoperative transfusion of blood products with mortality in lung transplant recipients

Author

Pascal Locher, Silvia R Cottini, Reto A. Schuepbach, Paul A Stehberger, Urs Wenger, Denise Weber, Mario Fasshauer, Markus Béchir, and University of Zurich

Subjects
medicine.medical_specialty, Lung, business.industry, medicine.medical_treatment, Research, Transfusion, 610 Medicine & health, Human physiology, medicine.anatomical_structure, Lung transplantation, Postoperative mortality, ICU complications, Medicine, Mortality, 10023 Institute of Intensive Care Medicine, business, Intensive care medicine
Abstract

Background The impact of intraoperative transfusion on postoperative mortality in lung transplant recipients is still elusive. Methods Univariate and multivariate analysis were performed to investigate the influence of red blood cells (RBCs) and fresh frozen plasma (FFP) on mortality in 134 consecutive lung transplants recipients from September 2003 until December 2008. Results Intraoperative transfusion of RBCs and FFP was associated with a significant increase in mortality with odds ratios (ORs) of 1.10 (1.03 to 1.16, P = 0.02) and 1.09 (1.02 to 1.15, P = 0.03), respectively. For more than four intraoperatively transfused RBCs multivariate analysis showed a hazard ratio for mortality of 3.8 (1.40 to 10.31, P = 0.003). Furthermore, non-survivors showed a significant increase in renal replacement therapy (RRT) (36.6% versus 6.9%, P P P = 0.0019), sepsis (24.2% versus 4.0%, P = 0.0004), multiple organ dysfunction syndrome (MODS) (26.9% versus 3.1%, P P = 0.0004), retransplantation (12.1% versus 6.9%, P = 0.039) and readmission to the ICU (33.3% versus 12.8%, P = 0.024). Conclusions Intraoperative transfusion is associated with a strong negative influence on outcome in lung transplant recipients.

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