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1. Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort

Author

Wendel Garcia P. D., Aguirre-Bermeo H., Buehler P. K., Alfaro-Farias M., Yuen B., David S., Tschoellitsch T., Wengenmayer T., Korsos A., Fogagnolo A., Kleger G. -R., Wu M. A., Colombo R., Turrini F., Potalivo A., Rezoagli E., Rodriguez-Garcia R., Castro P., Lander-Azcona A., Martin-Delgado M. C., Lozano-Gomez H., Ensner R., Michot M. P., Gehring N., Schott P., Siegemund M., Merki L., Wiegand J., Jeitziner M. M., Laube M., Salomon P., Hillgaertner F., Dullenkopf A., Ksouri H., Cereghetti S., Grazioli S., Burkle C., Marrel J., Fleisch I., Perez M. -H., Baltussen Weber A., Ceruti S., Marquardt K., Hubner T., Redecker H., Studhalter M., Stephan M., Selz D., Pietsch U., Ristic A., Heise A., Meyer zu Bentrup F., Franchitti Laurent M., Fodor P., Gaspert T., Haberthuer C., Colak E., Heuberger D. M., Fumeaux T., Montomoli J., Guerci P., Schuepbach R. A., Hilty M. P., Roche-Campo F., Algaba-Calderon A., Apolo J., Aslanidis T., Babik B., Boroli F., Brem J., Brenni M., Brugger S. D., Camen G., Catena E., Ceriani R., Chau I., Christ A., Cogliati C., Concha P., Delahaye G., Drvaric I., Escos-Orta J., Fabbri S., Facondini F., Filipovic M., Gamez-Zapata J., Gerecke P., Gommers D., Hillermann T., Ince C., Jenni-Moser B., Jovic M., Jurkolow G., Klarer A., Lambert A., Laurent J. -C., Lavanchy J., Lienhardt-Nobbe B., Locher P., Losser M. -R., Lussman R. F., Magliocca A., Margarit A., Martinez A., Mauri R., Mayor-Vazquez E., Meier J., Moret-Bochatay M., Murrone M., Naon D., Neff T., Novy E., Petersen L., Pugin J., Ramelet A. -S., Rilinger J., Rimensberger P. C., Sepulcri M., Shaikh K., Sieber M., Simonini M. S., Spadaro S., Sridharan G. O., Stahl K., Staudacher D. L., Taboada-Fraga X., Tellez A., Urech S., Vitale G., Vizmanos-Lamotte G., Welte T., Zalba-Etayo B., Zellweger N., Graduate School, ACS - Atherosclerosis & ischemic syndromes, ACS - Microcirculation, AII - Inflammatory diseases, RISC-19-ICU Investigators, Wendel Garcia, P.D., Aguirre-Bermeo, H., Buehler, P.K., Alfaro-Farias, M., Yuen, B., David, S., Tschoellitsch, T., Wengenmayer, T., Korsos, A., Fogagnolo, A., Kleger, G.R., Wu, M.A., Colombo, R., Turrini, F., Potalivo, A., Rezoagli, E., Rodríguez-García, R., Castro, P., Lander-Azcona, A., Martín-Delgado, M.C., Lozano-Gómez, H., Ensner, R., Michot, M.P., Gehring, N., Schott, P., Siegemund, M., Merki, L., Wiegand, J., Jeitziner, M.M., Laube, M., Salomon, P., Hillgaertner, F., Dullenkopf, A., Ksouri, H., Cereghetti, S., Grazioli, S., Bürkle, C., Marrel, J., Fleisch, I., Perez, M.H., Baltussen Weber, A., Ceruti, S., Marquardt, K., Hübner, T., Redecker, H., Studhalter, M., Stephan, M., Selz, D., Pietsch, U., Ristic, A., Heise, A., Meyer Zu Bentrup, F., Franchitti Laurent, M., Fodor, P., Gaspert, T., Haberthuer, C., Colak, E., Heuberger, D.M., Fumeaux, T., Montomoli, J., Guerci, P., Schuepbach, R.A., Hilty, M.P., Roche-Campo, F., Algaba-Calderon, A., Apolo, J., Aslanidis, T., Babik, B., Boroli, F., Brem, J., Brenni, M., Brugger, S.D., Camen, G., Catena, E., Ceriani, R., Chau, I., Christ, A., Cogliati, C., Concha, P., Delahaye, G., Drvaric, I., Escós-Orta, J., Fabbri, S., Facondini, F., Filipovic, M., Gámez-Zapata, J., Gerecke, P., Gommers, D., Hillermann, T., Ince, C., Jenni-Moser, B., Jovic, M., Jurkolow, G., Klarer, A., Lambert, A., Laurent, J.C., Lavanchy, J., Lienhardt-Nobbe, B., Locher, P., Losser, M.R., Lussman, R.F., Magliocca, A., Margarit, A., Martínez, A., Mauri, R., Mayor-Vázquez, E., Meier, J., Moret-Bochatay, M., Murrone, M., Naon, D., Neff, T., Novy, E., Petersen, L., Pugin, J., Ramelet, A.S., Rilinger, J., Rimensberger, P.C., Sepulcri, M., Shaikh, K., Sieber, M., Simonini, M.S., Spadaro, S., Sridharan, G.O., Stahl, K., Staudacher, D.L., Taboada-Fraga, X., Tellez, A., Urech, S., Vitale, G., Vizmanos-Lamotte, G., Welte, T., Zalba-Etayo, B., Zellweger, N., Wendel Garcia, P, Aguirre-Bermeo, H, Buehler, P, Alfaro-Farias, M, Yuen, B, David, S, Tschoellitsch, T, Wengenmayer, T, Korsos, A, Fogagnolo, A, Kleger, G, Wu, M, Colombo, R, Turrini, F, Potalivo, A, Rezoagli, E, Rodriguez-Garcia, R, Castro, P, Lander-Azcona, A, Martin-Delgado, M, Lozano-Gomez, H, Ensner, R, Michot, M, Gehring, N, Schott, P, Siegemund, M, Merki, L, Wiegand, J, Jeitziner, M, Laube, M, Salomon, P, Hillgaertner, F, Dullenkopf, A, Ksouri, H, Cereghetti, S, Grazioli, S, Burkle, C, Marrel, J, Fleisch, I, Perez, M, Baltussen Weber, A, Ceruti, S, Marquardt, K, Hubner, T, Redecker, H, Studhalter, M, Stephan, M, Selz, D, Pietsch, U, Ristic, A, Heise, A, Meyer zu Bentrup, F, Franchitti Laurent, M, Fodor, P, Gaspert, T, Haberthuer, C, Colak, E, Heuberger, D, Fumeaux, T, Montomoli, J, Guerci, P, Schuepbach, R, Hilty, M, Roche-Campo, F, Algaba-Calderon, A, Apolo, J, Aslanidis, T, Babik, B, Boroli, F, Brem, J, Brenni, M, Brugger, S, Camen, G, Catena, E, Ceriani, R, Chau, I, Christ, A, Cogliati, C, Concha, P, Delahaye, G, Drvaric, I, Escos-Orta, J, Fabbri, S, Facondini, F, Filipovic, M, Gamez-Zapata, J, Gerecke, P, Gommers, D, Hillermann, T, Ince, C, Jenni-Moser, B, Jovic, M, Jurkolow, G, Klarer, A, Lambert, A, Laurent, J, Lavanchy, J, Lienhardt-Nobbe, B, Locher, P, Losser, M, Lussman, R, Magliocca, A, Margarit, A, Martinez, A, Mauri, R, Mayor-Vazquez, E, Meier, J, Moret-Bochatay, M, Murrone, M, Naon, D, Neff, T, Novy, E, Petersen, L, Pugin, J, Ramelet, A, Rilinger, J, Rimensberger, P, Sepulcri, M, Shaikh, K, Sieber, M, Simonini, M, Spadaro, S, Sridharan, G, Stahl, K, Staudacher, D, Taboada-Fraga, X, Tellez, A, Urech, S, Vitale, G, Vizmanos-Lamotte, G, Welte, T, Zalba-Etayo, B, Zellweger, N, and Intensive Care

Subjects
Male, ARDS, Time Factors, medicine.medical_treatment, Old age, Critical Care and Intensive Care Medicine, law.invention, 0302 clinical medicine, law, Oxygen therapy, Noninvasive mechanical ventilation, Intubation, 030212 general & internal medicine, Hospital Mortality, Prospective Studies, Registries, Prospective cohort study, 610 Medicine & health, Unitats de cures intensives, Intensive care units, Medical emergencies. Critical care. Intensive care. First aid, Middle Aged, Intensive care unit, Intensive Care Units, Treatment Outcome, Vellesa, High flow oxygen therapy, Disease Progression, Female, Standard oxygen therapy, medicine.medical_specialty, Respiratory Therapy, Critical Illness, NO, 03 medical and health sciences, Intensive care, medicine, Humans, Invasive mechanical ventilation, Critically ill, Patient self-inflicted lung injury, Aged, Retrospective Studies, Mechanical ventilation, COVID-19/mortality, COVID-19/therapy, Critical Illness/mortality, Critical Illness/therapy, Respiratory Therapy/methods, Respiratory Therapy/statistics & numerical data, COVID-19, Respiratory support, business.industry, RC86-88.9, Research, Retrospective cohort study, medicine.disease, Malalts en estat crític, 030228 respiratory system, Emergency medicine, business
Abstract

Background Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates. Methods Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups. Results Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016). Conclusion In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk.

Published
2021

2. 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, Saba, Al-Ameri, Wendel-Garcia, P, Moser, A, Jeitziner, M, Aguirre-Bermeo, H, Arias-Sanchez, P, Apolo, J, Roche-Campo, F, Franch-Llasat, D, Kleger, G, Schrag, C, Pietsch, U, Filipovic, M, David, S, Stahl, K, Bouaoud, S, Ouyahia, A, Fodor, P, Locher, P, Siegemund, M, Zellweger, N, Cereghetti, S, Schott, P, Gangitano, G, Wu, M, Alfaro-Farias, M, Vizmanos-Lamotte, G, Ksouri, H, Gehring, N, Rezoagli, E, Turrini, F, Lozano-Gomez, H, Carsetti, A, Rodriguez-Garcia, R, Yuen, B, Weber, A, Castro, P, Escos-Orta, J, Dullenkopf, A, Martin-Delgado, M, Aslanidis, T, Perez, M, Hillgaertner, F, Ceruti, S, Franchitti Laurent, M, Marrel, J, Colombo, R, Laube, M, Fogagnolo, A, Studhalter, M, Wengenmayer, T, Gamberini, E, Buerkle, C, Buehler, P, Keiser, S, Elhadi, M, Montomoli, J, Guerci, P, Fumeaux, T, Schuepbach, R, Jakob, S, Que, Y, Hilty, M, Graduate School, Translational Physiology, ACS - Atherosclerosis & ischemic syndromes, ACS - Microcirculation, and AII - Inflammatory diseases

Subjects
Disease dynamic, Disease dynamics, Pandemic, Critical Illness, COVID-19, 610 Medicine & health, Middle Aged, Critical Care and Intensive Care Medicine, Intensive Care Units, Humans, Female, ARDS, Intensive care unit, Prospective Studies, Registries, Pandemics
Abstract

BackgroundIt 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.MethodsProspective, 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.ResultsFour 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 p p p 2/FiO2at admission was lower (132 [123–141] mmHg vs 101 [91–113] mmHg,p p = 0.05). The number of patients treated with steroids and tocilizumab increased, while the use of therapeutic anticoagulation presented an inverse U-shaped behaviour over the course of the pandemic. The proportion of patients treated with high-flow oxygen (5 [4–7]% vs 20 [14–29],p p p p p ConclusionCharacteristics and disease course of critically ill COVID-19 patients have continuously evolved, concomitant to the clinical management, throughout the pandemic leading to a younger, less severely ill ICU population with distinctly different clinical, pulmonary and inflammatory presentations than at the onset of the pandemic.

Published
2022

3. 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

4. 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

Wendel-Garcia PD, Moser A, Jeitziner MM, Aguirre-Bermeo H, Arias-Sanchez P, Apolo J, Roche-Campo F, Franch-Llasat D, Kleger GR, Schrag C, Pietsch U, Filipovic M, David S, Stahl K, Bouaoud S, Ouyahia A, Fodor P, Locher P, Siegemund M, Zellweger N, Cereghetti S, Schott P, Gangitano G, Wu MA, Alfaro-Farias M, Vizmanos-Lamotte G, Ksouri H, Gehring N, Rezoagli E, Turrini F, Lozano-Gómez H, Carsetti A, Rodríguez-García R, Yuen B, Weber AB, Castro P, Escos-Orta JO, Dullenkopf A, Martín-Delgado MC, Aslanidis T, Perez MH, Hillgaertner F, Ceruti S, Franchitti Laurent M, Marrel J, Colombo R, Laube M, Fogagnolo A, Studhalter M, Wengenmayer T, Gamberini E, Buerkle C, Buehler PK, Keiser S, Elhadi M, Montomoli J, Guerci P, Fumeaux T, Schuepbach RA, Jakob SM, Que YA, and Hilty MP

Subjects
Critical Illness epidemiology, Critical Illness therapy, Female, Humans, Intensive Care Units, Middle Aged, Prospective Studies, Registries, COVID-19 therapy, Pandemics
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 < 0.001) and the severity of organ dysfunction at ICU admission decreased (Sequential Organ Failure Assessment 8.2 [7.6-9.0] vs 5.8 [5.3-6.4], p < 0.001) and increased, while more female patients (26 [23-29]% vs 41 [35-48]%, p < 0.001) were admitted. The time span between symptom onset and hospitalization as well as ICU admission became longer later in the pandemic (6.7 [6.2-7.2| days vs 9.7 [8.9-10.5] days, p < 0.001). The PaO 2 /FiO 2 at admission was lower (132 [123-141] mmHg vs 101 [91-113] mmHg, p < 0.001) but showed faster improvements over the initial 5 days of ICU stay in late 2021 compared to early 2020 (34 [20-48] mmHg vs 70 [41-100] mmHg, p = 0.05). The number of patients treated with steroids and tocilizumab increased, while the use of therapeutic anticoagulation presented an inverse U-shaped behaviour over the course of the pandemic. The proportion of patients treated with high-flow oxygen (5 [4-7]% vs 20 [14-29], p < 0.001) and non-invasive mechanical ventilation (14 [11-18]% vs 24 [17-33]%, p < 0.001) throughout the pandemic increased concomitant to a decrease in invasive mechanical ventilation (82 [76-86]% vs 74 [64-82]%, p < 0.001). The ICU mortality (23 [19-26]% vs 17 [12-25]%, p < 0.001) and length of stay (14 [13-16] days vs 11 [10-13] days, p < 0.001) decreased over 19 months of the pandemic., Conclusion: Characteristics and disease course of critically ill COVID-19 patients have continuously evolved, concomitant to the clinical management, throughout the pandemic leading to a younger, less severely ill ICU population with distinctly different clinical, pulmonary and inflammatory presentations than at the onset of the pandemic., (© 2022. The Author(s).)

Published
2022
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5. Implications of early respiratory support strategies on disease progression in critical COVID-19: a matched subanalysis of the prospective RISC-19-ICU cohort.

Author

Wendel Garcia PD, Aguirre-Bermeo H, Buehler PK, Alfaro-Farias M, Yuen B, David S, Tschoellitsch T, Wengenmayer T, Korsos A, Fogagnolo A, Kleger GR, Wu MA, Colombo R, Turrini F, Potalivo A, Rezoagli E, Rodríguez-García R, Castro P, Lander-Azcona A, Martín-Delgado MC, Lozano-Gómez H, Ensner R, Michot MP, Gehring N, Schott P, Siegemund M, Merki L, Wiegand J, Jeitziner MM, Laube M, Salomon P, Hillgaertner F, Dullenkopf A, Ksouri H, Cereghetti S, Grazioli S, Bürkle C, Marrel J, Fleisch I, Perez MH, Baltussen Weber A, Ceruti S, Marquardt K, Hübner T, Redecker H, Studhalter M, Stephan M, Selz D, Pietsch U, Ristic A, Heise A, Meyer Zu Bentrup F, Franchitti Laurent M, Fodor P, Gaspert T, Haberthuer C, Colak E, Heuberger DM, Fumeaux T, Montomoli J, Guerci P, Schuepbach RA, Hilty MP, and Roche-Campo F

Subjects
Aged, COVID-19 mortality, Critical Illness mortality, Disease Progression, Female, Hospital Mortality, Humans, Intensive Care Units, Male, Middle Aged, Prospective Studies, Registries, Retrospective Studies, Time Factors, Treatment Outcome, COVID-19 therapy, Critical Illness therapy, Respiratory Therapy methods, Respiratory Therapy statistics & numerical data
Abstract

Background: Uncertainty about the optimal respiratory support strategies in critically ill COVID-19 patients is widespread. While the risks and benefits of noninvasive techniques versus early invasive mechanical ventilation (IMV) are intensely debated, actual evidence is lacking. We sought to assess the risks and benefits of different respiratory support strategies, employed in intensive care units during the first months of the COVID-19 pandemic on intubation and intensive care unit (ICU) mortality rates., Methods: Subanalysis of a prospective, multinational registry of critically ill COVID-19 patients. Patients were subclassified into standard oxygen therapy ≥10 L/min (SOT), high-flow oxygen therapy (HFNC), noninvasive positive-pressure ventilation (NIV), and early IMV, according to the respiratory support strategy employed at the day of admission to ICU. Propensity score matching was performed to ensure comparability between groups., Results: Initially, 1421 patients were assessed for possible study inclusion. Of these, 351 patients (85 SOT, 87 HFNC, 87 NIV, and 92 IMV) remained eligible for full analysis after propensity score matching. 55% of patients initially receiving noninvasive respiratory support required IMV. The intubation rate was lower in patients initially ventilated with HFNC and NIV compared to those who received SOT (SOT: 64%, HFNC: 52%, NIV: 49%, p = 0.025). Compared to the other respiratory support strategies, NIV was associated with a higher overall ICU mortality (SOT: 18%, HFNC: 20%, NIV: 37%, IMV: 25%, p = 0.016)., Conclusion: In this cohort of critically ill patients with COVID-19, a trial of HFNC appeared to be the most balanced initial respiratory support strategy, given the reduced intubation rate and comparable ICU mortality rate. Nonetheless, considering the uncertainty and stress associated with the COVID-19 pandemic, SOT and early IMV represented safe initial respiratory support strategies. The presented findings, in agreement with classic ARDS literature, suggest that NIV should be avoided whenever possible due to the elevated ICU mortality risk.

Published
2021
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