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156 results on '"Dave A. Dongelmans"'

1. A quality improvement study on how a simulation model can help decision making on organization of ICU wards

Author

Danielle Sent, Delanie M. van der Meulen, Andres Alban, Stephen E. Chick, Ilse J.A. Wissink, Alexander P.J. Vlaar, and Dave A. Dongelmans

Subjects
Critical care, Computer Simulation, Organizational decision making, Quality of Healthcare, Hospital Bed Capacity, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. Methods A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. Results The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. Conclusions The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.

Published
2024
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2. Lack of association between classical HLA genes and asymptomatic SARS-CoV-2 infection

Author

Astrid Marchal, Elizabeth T. Cirulli, Iva Neveux, Evangelos Bellos, Ryan S. Thwaites, Kelly M. Schiabor Barrett, Yu Zhang, Ivana Nemes-Bokun, Mariya Kalinova, Andrew Catchpole, Stuart G. Tangye, András N. Spaan, Justin B. Lack, Jade Ghosn, Charles Burdet, Guy Gorochov, Florence Tubach, Pierre Hausfater, Clifton L. Dalgard, Shen-Ying Zhang, Qian Zhang, Christopher Chiu, Jacques Fellay, Joseph J. Grzymski, Vanessa Sancho-Shimizu, Laurent Abel, Jean-Laurent Casanova, Aurélie Cobat, Alexandre Bolze, Alessandro Aiuti, Saleh Al-Muhsen, Fahd Al-Mulla, Ali Amara, Mark S. Anderson, Evangelos Andreakos, Andrés A. Arias, Lisa M. Arkin, Hagit Baris Feldman, Paul Bastard, Alexandre Belot, Catherine M. Biggs, Dusan Bogunovic, Anastasiia Bondarenko, Alessandro Borghesi, Ahmed A. Bousfiha, Petter Brodin, Yenan Bryceson, Manish J. Butte, Giorgio Casari, John Christodoulou, Roger Colobran, Antonio Condino-Neto, Stefan N. Constantinescu, Megan A. Cooper, Murkesh Desai, Beth A. Drolet, Xavier Duval, Jamila El Baghdadi, Philippine Eloy, Sara Espinosa-Padilla, Carlos Flores, José Luis Franco, Antoine Froidure, Peter K. Gregersen, Bodo Grimbacher, Filomeen Haerynck, David Hagin, Rabih Halwani, Lennart Hammarström, James R. Heath, Elena W.Y. Hsieh, Eystein Husebye, Kohsuke Imai, Yuval Itan, Emmanuelle Jouanguy, Elżbieta Kaja, Timokratis Karamitros, Kai Kisand, Cheng-Lung Ku, Yu-Lung Lau, Yun Ling, Carrie L. Lucas, Tom Maniatis, Davood Mansouri, László Maródi, France Mentré, Isabelle Meyts, Joshua D. Milner, Kristina Mironska, Trine H. Mogensen, Tomohiro Morio, Lisa F.P. Ng, Luigi D. Notarangelo, Antonio Novelli, Giuseppe Novelli, Cliona O'Farrelly, Satoshi Okada, Keisuke Okamoto, Tayfun Ozcelik, Qiang Pan-Hammarström, Jean W. Pape, Rebeca Perez de Diego, Jordi Perez-Tur, David S. Perlin, Graziano Pesole, Anna M. Planas, Carolina Prando, Aurora Pujol, Anne Puel, Lluis Quintana-Murci, Sathishkumar Ramaswamy, Laurent Renia, Igor Resnick, Carlos Rodríguez-Gallego, Anna Sediva, Mikko R.J. Seppänen, Mohammad Shahrooei, Anna Shcherbina, Ondrej Slaby, Andrew L. Snow, Pere Soler-Palacín, Vassili Soumelis, Ivan Tancevski, Ahmad Abou Tayoun, Şehime Gülsün Temel, Christian Thorball, Pierre Tiberghien, Sophie Trouillet-Assant, Stuart E. Turvey, K. M. Furkan Uddin, Mohammed J. Uddin, Diederik van de Beek, Donald C. Vinh, Horst von Bernuth, Joost Wauters, Mayana Zatz, Pawel Zawadzki, Serge Bureau, Yannick Vacher, Anne Gysembergh-Houal, Lauren Demerville, Abla Benleulmi-Chaachoua, Sebastien Abad, Radhiya Abassi, Abdelrafie Abdellaoui, Abdelkrim Abdelmalek, Hendy Abdoul, Helene Abergel, Fariza Abeud, Sophie Abgrall, Noemie Abisror, Marylise Adechian, Nordine Aderdour, Hakeem Farid Admane, Frederic Adnet, Sara Afritt, Helene Agostini, Claire Aguilar, Sophie Agut, Tommaso Francesco Aiello, Marc Ait Kaci, Hafid Ait Oufella, Gokula Ajeenthiravasan, Virginie Alauzy, Fanny Alby-Laurent, Lucie Allard, Marie-Alexandra Alyanakian, Blanca Amador Borrero, Sabrina Amam, Lucile Amrouche, Marc Andronikof, Dany Anglicheau, Nadia Anguel, Djillali Annane, Mohammed Aounzou, Caroline Aparicio, Gladys Aratus, Jean-Benoit Arlet, Jeremy Arzoine, Elisabeth Aslangul, Mona Assefi, Adeline Aubry, Laetitia Audiffred, Etienne Audureau, Christelle Nathalie Auger, Jean-Charles Auregan, Celine Awotar, Sonia Ayllon Milla, Delphine Azan, Laurene Azemar, Billal Azzouguen, Marwa Bachir Elrufaai, Aïda Badsi, Prissile Bakouboula, Coline Balcerowiak, Fanta Balde, Elodie Baldivia, Eliane-Flore Bangamingo, Amandine Baptiste, Fanny Baran-Marszak, Caroline Barau, Nathalie Barget, Flore Baronnet, Romain Barthelemy, Jean-Luc Baudel, Camille Baudry, Elodie Baudry, Laurent Beaugerie, Adel Belamri, Nicolas Belaube, Rhida Belilita, Pierre Bellassen, Rawan Belmokhtar, Isabel Beltran, Ruben Benainous, Mourad Benallaoua, Robert Benamouzig, Amélie Benbara, Jaouad Benhida, Anis Benkhelouf, Jihene Benlagha, Chahinez Benmostafa, Skander Benothmane, Miassa Bentifraouine, Laurence Berard, Quentin Bernier, Enora Berti, Astrid Bertier, Laure Berton, Simon Bessis, Alexandra Beurton, Celine Bianco, Clara Bianquis, Frank Bidar, Philippe Blanche, Clarisse Blayau, Alexandre Bleibtreu, Emmanuelle Blin, Coralie Bloch-Queyrat, Marie-Christophe Boissier, Diane Bollens, Marion Bolzoni, Rudy pierre Bompard, Nicolas Bonnet, Justine Bonnouvrier, Shirmonecrystal Botha, Wissam Boucenna, Fatiha Bouchama, Olivier Bouchaud, Hanane Bouchghoul, Taoueslylia Boudjebla, Noel Boudjema, Catherine Bouffard, Adrien Bougle, Meriem Bouguerra, Leila Bouras, Agnes Bourcier, Anne Bourgarit Durand, Anne Bourrier, Fabrice Bouscarat, Diane Bouvry, Nesrine Bouziri, Ons Bouzrara, Sarah Bribier, Delphine Brugier, Melanie Brunel, Eida Bui, Anne Buisson, Iryna Bukreyeva, Côme Bureau, Jacques Cadranel, Johann Cailhol, Ruxandra Calin, Clara Campos Vega, Pauline Canavaggio, Marta Cancella, Delphine Cantin, Albert Cao, Lionel Carbillon, Nicolas Carlier, Clementine Cassard, Guylaine Castor, Marion Cauchy, Olivier Cha, Benjamin Chaigne, Salima Challal, Karine Champion, Patrick Chariot, Julie Chas, Simon Chauveau, Anthony Chauvin, Clement Chauvin, Nathalie Chavarot, Kamélia Chebbout, Mustapha Cherai, Ilaria Cherubini, Amelie Chevalier, Thibault Chiarabini, Thierry Chinet, Richard Chocron, Pascaline Choinier, Juliette Chommeloux, Christophe Choquet, Laure Choupeaux, Benjamin Chousterman, Dragosmarius Ciocan, Ada Clarke, Gaëlle Clavere, Florian Clavier, Karine Clement, Sebastien Clerc, Yves Cohen, Fleur Cohen, Adrien Cohen, Audrey Coilly, Hester Colboc, Pauline Colin, Magalie Collet, Chloé Comarmond, Emeline Combacon, Alain Combes, Celine Comparon, Jean-Michel Constantin, Hugues Cordel, Anne-Gael Cordier, Adrien Costantini, Nathalie Costedoat Chalumeau, Camille Couffignal, Doriane Coupeau, Alain Creange, Yannie Cuvillier Lamarre, Charlène Da Silveira, Sandrine Dautheville Guibal El Kayani, Nathalie De Castro, Yann De Rycke, Lucie Del Pozo, Quentin Delannoy, Mathieu Delay, Robin Deleris, Juliette Delforge, Laëtitia Delphine, Noemie Demare, Sophie Demeret, Alexandre Demoule, Aurore Deniau, François Depret, Sophie Derolez, Ouda Derradji, Nawal Derridj, Vincent Descamps, Lydia Deschamps, Celine Desconclois, Cyrielle Desnos, Karine Desongins, Robin Dhote, Benjamin Diallo, Morgane Didier, Myriam Diemer, Stephane Diez, Juliette Djadi-Prat, Fatima-Zohra Djamouri Monnory, Siham Djebara, Naoual Djebra, Minette Djietcheu, Hadjer Djillali, Nouara Djouadi, Severine Donneger, Catarina Dos Santos, Nathalie Dournon, Martin Dres, Laura Droctove, Marie Drogrey, Margot Dropy, Elodie Drouet, Valérie Dubosq, Evelyne Dubreucq, Estelle Dubus, Boris Duchemann, Thibault Duchenoy, Emmanuel Dudoignon, Romain Dufau, Florence Dumas, Clara Duran, Emmanuelle Duron, Antoine Durrbach, Claudine Duvivier, Nathan Ebstein, Jihane El Khalifa, Alexandre Elabbadi, Caroline Elie, Gabriel Ernotte, Anne Esling, Martin Etienne, Xavier Eyer, Muriel Sarah Fartoukh, Takoua Fayali, Marion Fermaut, Arianna Fiorentino, Souha Fliss, Marie-Céline Fournier, Benjamin Fournier, Hélène Francois, Olivia Freynet, Yvann Frigout, Isaure Fromont, Axelle Fuentes, Thomas Furet, Joris Galand, Marc Garnier, Agnes Gaubert, Stéphane Gaudry, Samuel Gaugain, Damien Gauthier, Maxime Gautier, Sophie Georgin-Lavialle, Daniela Geromin, Mohamed Ghalayini, Bijan Ghaleh, Myriam Ghezal, Aude Gibelin, Linda Gimeno, Benoit Girard, Bénédicte Giroux Leprieur, Doryan Gomes, Elisabete Gomes-Pires, Anne Gouge, Amel Gouja, Helene Goulet, Sylvain Goupil, Jeanne Goupil De Bouille, Julien Gras, Segolene Greffe, Lamiae Grimaldi, Paul Guedeney, Bertrand Guidet, Matthias Guillo, Mariechristelle Gulczynski, Tassadit Hadjam, Didier Haguenauer, Soumeya Hammal, Nadjib Hammoudi, Olivier Hanon, Anarole Harrois, Coraline Hautem, Guillaume Hekimian, Nicholas Heming, Olivier Hermine, Sylvie Ho, Marie Houllier, Benjamin Huot, Tessa Huscenot, Wafa Ibn Saied, Ghilas Ikherbane, Meriem Imarazene, Patrick Ingiliz, Lina Iratni, Stephane Jaureguiberry, Jean-Francois Jean-Marc, Deleena Jeyarajasingham, Pauline Jouany, Veronique Jouis, Clement Jourdaine, Ouifiya Kafif, Rim Kallala, Sandrine Katsahian, Lilit Kelesyan, Vixra Keo, Flora Ketz, Warda Khamis, Enfel Khelili, Mehdi Khellaf, Christy Gaëlla Kotokpo Youkou, Ilias Kounis, Gaelle Kpalma, Jessica Krause, Vincent Labbe, Karine Lacombe, Jean-Marc Lacorte, Anne Gaelle Lafont, Emmanuel Lafont, Lynda Lagha, Lionel Lamhaut, Aymeric Lancelot, Cecilia Landman, Fanny Lanternier, Cecile Larcheveque, Caroline Lascoux Combe, Ludovic Lassel, Benjamin Laverdant, Christophe Lavergne, Jean-Rémi Lavillegrand, Pompilia Lazureanu, Loïc Le Guennec, Lamia Leberre, Claire Leblanc, Marion Leboyer, Francois Lecomte, Marine Lecorre, Romain Leenhardt, Marylou Lefebvre, Bénédicte Lefebvre, Paul Legendre, Anne Leger, Laurence Legros, Justyna Legrosse, Sébastien Lehuunghia, Julien Lemarec, Jeremie Leporrier-Ext, Manon Lesein, Hubert Lesur, Vincent Levy, Albert Levy, Edwige Lopes, Amanda Lopes, Vanessa Lopez, Julien Lopinto, Olivier Lortholary, Badr Louadah, Bénédicte Loze, Marie-Laure Lucas, Axelle Lucasamichi, Liem Binh Luong, Arouna Magazimama-Ext, David Maingret, Lakhdar Mameri, Philippe Manivet, Cylia Mansouri, Estelle Marcault, Jonathan Marey, Nathalie Marin, Clémence Marois, Olivier Martin, Lou Martineau, Cannelle Martinez-Lopez, Pierre Martyniuck, Pauline Mary De Farcy, Nessrine Marzouk, Rafik Masmoudi, Alexandre Mebazaa, Frédéric Mechai, Fabio Mecozzi, Chamseddine Mediouni, Bruno Megarbane, Mohamed Meghadecha, Élodie Mejean, Arsene Mekinian, Nour Mekki Abdelhadi, Rania Mekni, Thinhinan Sabrina Meliti, Breno Melo Lima, Paris Meng, Soraya Merbah, Fadhila Messani, Yasmine Messaoudi, Baboo-Irwinsingh Mewasing, Lydia Meziane, Carole Michelot-Burger, Françoise Mignot, Fadi Hillary Minka, Makoto Miyara, Pierre Moine, Jean-Michel Molina, Anaïs Montegnies-Boulet, Alexandra Monti, Claire Montlahuc, Anne-Lise Montout, Alexandre Moores, Caroline Morbieu, Helene Mortelette, Stéphane Mouly, Rosita Muzaffar, Cherifa Iness Nacerddine, Marine Nadal, Hajer Nadif, Kladoum Nassarmadji, Pierre Natella, Sandrine Ndingamondze, Stefan Neraal, Caroline Nguyen, Bao N'Guyen, Isabelle Nion Larmurier, Luc Nlomenyengue, Nicolas Noel, Hilario Nunes, Edris Omar, Zineb Ouazene, Elise Ouedraogo, Wassila Ouelaa, Anissa Oukhedouma, Yasmina Ould Amara, Herve Oya, Johanna Oziel, Thomas Padilla, Elena Paillaud, Solenne Paiva, Beatrice Parfait, Perrine Parize, Christophe Parizot, Antoine Parrot, Arthur Pavot, Laetitia Peaudecerf, Frédéric Pene, Marion Pepin, Julie Pernet, Claire Pernin, Mylène Petit, Olivier Peyrony, Marie-Pierre Pietri, Olivia Pietri, Marc Pineton De Chambrun, Michelle Pinson, Claire Pintado, Valentine Piquard, Christine Pires, Benjamin Planquette, Sandrine Poirier, Anne-Laure Pomel, Stéphanie Pons, Diane Ponscarme, Annegaelle Pourcelot, Valérie Pourcher, Anne Pouvaret, Florian Prever, Miresta Previlon, Margot Prevost, Marie-Julie Provoost, Cyril Quemeneur, Cédric Rafat, Agathe Rami, Brigitte Ranque, Maurice Raphael, Jean Herle Raphalen, Anna Rastoin, Mathieu Raux, Amani Rebai, Michael Reby, Alexis Regent, Asma Regrag, Matthieu Resche-Rigon, Quentin Ressaire, Christian Richard, Mariecaroline Richard, Maxence Robert, Benjamin Rohaut, Camille Rolland-Debord, Jacques Ropers, Anne-Marie Roque-Afonso, Charlotte Rosso, Mélanie Rousseaux, Nabila Rousseaux, Swasti Roux, Lorène Roux, Claire Rouzaud, Antoine Rozes, Emma Rubenstein, Jean-Marc Sabate, Sheila Sabet, Sophie-Caroline Sacleux, Nathalie Saidenberg Kermanach, Faouzi Saliba, Dominique Salmon, Laurent Savale, Guillaume Savary, Rebecca Sberro, Anne Scemla, Frederic Schlemmer, Mathieu Schwartz, Saïd Sedfi, Samia Sefir-Kribel, Philippe Seksik, Pierre Sellier, Agathe Selves, Nicole Sembach, Luca Semerano, Marie-Victoire Senat, Damien Sene, Alexandra Serris, Lucile Sese, Naima Sghiouar, Johanna Sigaux, Martin Siguier, Johanne Silvain, Noémie Simon, Tabassome Simon, Lina Innes Skandri, Miassa Slimani, Aurélie Snauwaert, Harry Sokol, Heithem Soliman, Nisrine Soltani, Benjamin Soyer, Gabriel Steg, Lydia Suarez, Tali-Anne Szwebel, Kossi Taffame, Yacine Tandjaoui-Lambiotte, Claire Tantet, Mariagrazia Tateo, Igor Theodose, Pierre clement Thiebaud, Caroline Thomas, Kelly Tiercelet, Julie Tisserand, Carole Tomczak, Krystel Torelino, Fatima Touam-Ext, Lilia Toumi, Gustave Toury, Mireille Toy-Miou, Olivia Tran Dinh Thanh Lien, Alexy Trandinh, Jean-Marc Treluyer, Baptiste Trinque, Jennifer Truchot, Sarah Tubiana, Simone Tunesi, Matthieu Turpin, Agathe Turpin, Tomas Urbina, Rafael Usubillaga Narvaez, Yurdagul Uzunhan, Prabakar Vaittinadaayar, Arnaud Valent, Maelle Valentian, Nadia Valin, Hélène Vallet, Marina Vaz, Miguel-Alejandro Vazquezibarra, Benoit Vedie, Laetitia Velly, Celine Verstuyft, Cedric Viallette, Eric Vicaut, Dorothee Vignes, Damien Vimpere, Myriam Virlouvet, Guillaume Voiriot, Lena Voisot, Emmanuel Weiss, Nicolas Weiss, Anaïs Winchenne, Youri Yordanov, Lara Zafrani, Mohamad Zaidan, Wissem Zaidi, Cathia Zak, Aida Zarhrate-Ghoul, Ouassila Zatout, Suzanne Zeino, Michel Zeitouni, Naïma Zemirli, Lorene Zerah, Ounsa Zia, Marianne Ziol, Oceane Zolario, Julien Zuber, Claire Andrejak, François Angoulvant, Delphine Bachelet, Marie Bartoli, Romain Basmaci, Sylvie Behillil, Marine Beluze, Dehbia Benkerrou, Krishna Bhavsar, Lila Bouadma, Sabelline Bouchez, Maude Bouscambert, Minerva Cervantes-Gonzalez, Anissa Chair, Catherine Chirouze, Alexandra Coelho, Sandrine Couffin-Cadiergues, Eric d’Ortenzio, Marie-Pierre Debray, Laurene Deconinck, Dominique Deplanque, Diane Descamps, Mathilde Desvallée, Alpha Diallo, Alphonsine Diouf, Céline Dorival, François Dubos, Brigitte Elharrar, Vincent Enouf, Hélène Esperou, Marina Esposito-Farese, Manuel Etienne, Eglantine Ferrand Devouge, Nathalie Gault, Alexandre Gaymard, Tristan Gigante, Morgane Gilg, Jérémie Guedj, Alexandre Hoctin, Isabelle Hoffmann, Ikram Houas, Jean-Sébastien Hulot, Salma Jaafoura, Florentia Kaguelidou, Sabrina Kali, Antoine Khalil, Coralie Khan, Cédric Laouénan, Samira Laribi, Minh Le, Quentin Le Hingrat, Soizic Le Mestre, Hervé Le Nagard, François-Xavier Lescure, Sophie Letrou, Yves Levy, Bruno Lina, Guillaume Lingas, Jean-Christophe Lucet, Denis Malvy, Marina Mambert, Amina Meziane, Hugo Mouquet, Jimmy Mullaert, Nadège Neant, Duc Nguyen, Marion Noret, Saad Nseir, Aurélie Papadopoulos, Christelle Paul, Nathan Peiffer-Smadja, Thomas Perpoint, Ventzislava Petrov-Sanchez, Gilles Peytavin, Huong Pham, Olivier Picone, Oriane Puéchal, Christian Rabaud, Manuel Rosa-Calatrava, Bénédicte Rossignol, Patrick Rossignol, Carine Roy, Marion Schneider, Richa Su, Coralie Tardivon, Marie-Capucine Tellier, François Téoulé, Olivier Terrier, Jean-François Timsit, Christelle Tual, Sylvie Van Der Werf, Noémie Vanel, Aurélie Veislinger, Benoit Visseaux, Aurélie Wiedemann, Yazdan Yazdanpanah, Loubna Alavoine, Charlotte Charpentier, Aline Dechanet, Jean-Luc Ecobichon, Wahiba Frezouls, Nadhira Houhou, Jonathan Lehacaut, Pauline Manchon, Mariama Nouroudine, Caroline Quintin, Michael Thy, Sylvie van der Werf, Valérie Vignali, Abir Chahine, Nawal Waucquier, Maria-Claire Migaud, Félix Djossou, Mayka Mergeay-Fabre, Aude Lucarelli, Magalie Demar, Léa Bruneau, Patrick Gérardin, Adrien Maillot, Christine Payet, Bruno Laviolle, Fabrice Laine, Christophe Paris, Mireille Desille-Dugast, Julie Fouchard, Thierry Pistone, Pauline Perreau, Valérie Gissot, Carole L.E. Goas, Samatha Montagne, Lucie Richard, Kévin Bouiller, Maxime Desmarets, Alexandre Meunier, Marilou Bourgeon, Benjamin Lefévre, Hélène Jeulin, Karine Legrand, Sandra Lomazzi, Bernard Tardy, Amandine Gagneux-Brunon, Frédérique Bertholon, Elisabeth Botelho-Nevers, Christelle Kouakam, Leturque Nicolas, Layidé Roufai, Karine Amat, Hélène Espérou, Samia Hendou, Giuseppe Foti, Giuseppe Citerio, Ernesto Contro, Alberto Pesci, Maria Grazia Valsecchi, Marina Cazzaniga, Giacomo Bellani, Jorge Abad, Giulia Accordino, Micol Angelini, Sergio Aguilera-Albesa, Aina Aguiló-Cucurull, Esra Akyüz Özkan, Ilad Alavi Darazam, Jonathan Antonio Roblero Albisures, Juan C. Aldave, Miquel Alfonso Ramos, Taj Ali Khan, Anna Aliberti, Seyed Alireza Nadji, Gulsum Alkan, Suzan A. AlKhater, Jerome Allardet-Servent, Luis M. Allende, Rebeca Alonso-Arias, Mohammed S. Alshahrani, Laia Alsina, Zahir Amoura, Arnau Antolí, Romain Arrestier, Mélodie Aubart, Teresa Auguet, Iryna Avramenko, Gökhan Aytekin, Axelle Azot, Seiamak Bahram, Fanny Bajolle, Fausto Baldanti, Aurélie Baldolli, Maite Ballester, Benoit Barrou, Federica Barzaghi, Sabrina Basso, Gulsum Iclal Bayhan, Liliana Bezrodnik, Agurtzane Bilbao, Geraldine Blanchard-Rohner, Ignacio Blanco, Adeline Blandinières, Daniel Blázquez-Gamero, Marketa Bloomfield, Mireia Bolivar-Prados, Raphael Borie, Elisabeth Botdhlo-Nevers, Aurore Bousquet, David Boutolleau, Claire Bouvattier, Oksana Boyarchuk, Juliette Bravais, M. Luisa Briones, Marie-Eve Brunner, Raffaele Bruno, Maria Rita P. Bueno, Huda Bukhari, Jacinta Bustamante, Juan José Cáceres Agra, Ruggero Capra, Raphael Carapito, Maria Carrabba, Carlos Casasnovas, Marion Caseris, Irene Cassaniti, Martin Castelle, Francesco Castelli, Martín Castillo de Vera, Mateus V. Castro, Emilie Catherinot, Jale Bengi Celik, Alessandro Ceschi, Martin Chalumeau, Bruno Charbit, Cécile Boulanger, Père Clavé, Bonaventura Clotet, Anna Codina, Cloé Comarmond, Patrizia Comoli, Angelo G. Corsico, Taner Coşkuner, Aleksandar Cvetkovski, Cyril Cyrus, David Dalmau, François Danion, David Ross Darley, Vincent Das, Nicolas Dauby, Stéphane Dauger, Paul De Munte, Loic de Pontual, Amin Dehban, Geoffroy Delplancq, Isabelle Desguerre, Antonio Di Sabatino, Jean-Luc Diehl, Stephanie Dobbelaere, Elena Domínguez-Garrido, Clément Dubost, Olov Ekwall, Şefika Elmas Bozdemir, Marwa H. Elnagdy, Melike Emiroglu, Akifumi Endo, Emine Hafize Erdeniz, Selma Erol Aytekin, Maria Pilar Etxart Lasa, Romain Euvrard, Giovanna Fabio, Laurence Faivre, Antonin Falck, Muriel Fartoukh, Morgane Faure, Miguel Fernandez Arquero, Ricard Ferrer, Jose Ferreres, Bruno Francois, Victoria Fumadó, Kitty S.C. Fung, Francesca Fusco, Alenka Gagro, Blanca Garcia Solis, Pierre Garçon, Pascale Gaussem, Zeynep Gayretli, Juana Gil-Herrera, Laurent Gilardin, Audrey Giraud Gatineau, Mònica Girona-Alarcón, Karen Alejandra Cifuentes Godínez, Jean-Christophe Goffard, Nacho Gonzales, Luis I. Gonzalez-Granado, Rafaela González-Montelongo, Antoine Guerder, Belgin Gülhan, Victor Daniel Gumucio, Leif Gunnar Hanitsch, Jan Gunst, Marta Gut, Jérôme Hadjadj, Selda Hancerli, Tetyana Hariyan, Nevin Hatipoglu, Deniz Heppekcan, Elisa Hernandez-Brito, Po-ki Ho, María Soledad Holanda-Peña, Juan P. Horcajada, Sami Hraiech, Linda Humbert, Ivan F.N. Hung, Alejandro D. Iglesias, Antonio Íñigo-Campos, Matthieu Jamme, María Jesús Arranz, Marie-Thérèse Jimeno, Iolanda Jordan, Saliha Kanık-Yüksek, Yalcin Kara, Aydın Karahan, Adem Karbuz, Kadriye Kart Yasar, Ozgur Kasapcopur, Kenichi Kashimada, Sevgi Keles, Yasemin Kendir Demirkol, Yasutoshi Kido, Can Kizil, Ahmet Osman Kılıç, Adam Klocperk, Antonia Koutsoukou, Zbigniew J. Król, Hatem Ksouri, Paul Kuentz, Arthur M.C. Kwan, Yat Wah M. Kwan, Janette S.Y. Kwok, Jean-Christophe Lagier, David S.Y. Lam, Vicky Lampropoulou, Fleur Le Bourgeois, Yee-Sin Leo, Rafael Leon Lopez, Daniel Leung, Michael Levin, Michael Levy, Romain Lévy, Zhi Li, Daniele Lilleri, Edson Jose Adrian Bolanos Lima, Agnes Linglart, Eduardo López-Collazo, José M. Lorenzo-Salazar, Céline Louapre, Catherine Lubetzki, Kwok-Cheung Lung, Charles-Edouard Luyt, David C. Lye, Cinthia Magnone, Enrico Marchioni, Carola Marioli, Majid Marjani, Laura Marques, Jesus Marquez Pereira, Andrea Martín-Nalda, David Martínez Pueyo, Javier Martinez-Picado, Iciar Marzana, Carmen Mata-Martínez, Alexis Mathian, Larissa R.B. Matos, Gail V. Matthews, Julien Mayaux, Raquel McLaughlin-Garcia, Philippe Meersseman, Jean-Louis Mège, Armand Mekontso-Dessap, Isabelle Melki, Federica Meloni, Jean-François Meritet, Paolo Merlani, Özge Metin Akcan, Mehdi Mezidi, Isabelle Migeotte, Maude Millereux, Matthieu Million, Tristan Mirault, Clotilde Mircher, Mehdi Mirsaeidi, Yoko Mizoguchi, Bhavi P. Modi, Francesco Mojoli, Elsa Moncomble, Abián Montesdeoca Melián, Antonio Morales Martinez, Francisco Morandeira, Pierre-Emmanuel Morange, Clémence Mordacq, Guillaume Morelle, Stéphane J. Mouly, Adrián Muñoz-Barrera, Cyril Nafati, Shintaro Nagashima, Yu Nakagama, Bénédicte Neven, João Farela Neves, Yuk-Yung Ng, Hubert Nielly, Yeray Novoa Medina, Esmeralda Nuñez Cuadros, Semsi Nur Karabela, J. Gonzalo Ocejo-Vinyals, Mehdi Oualha, Amani Ouedrani, Tayfun Özçelik, Aslinur Ozkaya-Parlakay, Michele Pagani, Maria Papadaki, Philippe Parola, Tiffany Pascreau, Stéphane Paul, Estela Paz-Artal, Sigifredo Pedraza, Nancy Carolina González Pellecer, Silvia Pellegrini, Rebeca Pérez de Diego, Xosé Luis Pérez-Fernández, Aurélien Philippe, Quentin Philippot, Adrien Picod, Marc Pineton de Chambrun, Antonio Piralla, Laura Planas-Serra, Dominique Ploin, Julien Poissy, Géraldine Poncelet, Garyphallia Poulakou, Marie S. Pouletty, Persia Pourshahnazari, Jia Li Qiu-Chen, Paul Quentric, Thomas Rambaud, Didier Raoult, Violette Raoult, Anne-Sophie Rebillat, Claire Redin, Léa Resmini, Pilar Ricart, Jean-Christophe Richard, Raúl Rigo-Bonnin, Nadia Rivet, Jacques G. Rivière, Gemma Rocamora-Blanch, Mathieu P. Rodero, Carlos Rodrigo, Luis Antonio Rodriguez, Carlos Rodriguez-Gallego, Agustí Rodriguez-Palmero, Carolina Soledad Romero, Anya Rothenbuhler, Damien Roux, Nikoletta Rovina, Flore Rozenberg, Yvon Ruch, Montse Ruiz, Maria Yolanda Ruiz del Prado, Juan Carlos Ruiz-Rodriguez, Joan Sabater-Riera, Kai Saks, Maria Salagianni, Oliver Sanchez, Adrián Sánchez-Montalvá, Silvia Sánchez-Ramón, Laire Schidlowski, Agatha Schluter, Julien Schmidt, Matthieu Schmidt, Catharina Schuetz, Cyril E. Schweitzer, Francesco Scolari, Luis Seijo, Analia Gisela Seminario, Piseth Seng, Sevtap Senoglu, Mikko Seppänen, Alex Serra Llovich, Virginie Siguret, Eleni Siouti, David M. Smadja, Nikaia Smith, Ali Sobh, Xavier Solanich, Jordi Solé-Violán, Catherine Soler, Betül Sözeri, Giulia Maria Stella, Yuriy Stepanovskiy, Annabelle Stoclin, Fabio Taccone, Jean-Luc Taupin, Simon J. Tavernier, Loreto Vidaur Tello, Benjamin Terrier, Guillaume Thiery, Karolina Thorn, Caroline Thumerelle, Imran Tipu, Martin Tolstrup, Gabriele Tomasoni, Julie Toubiana, Josep Trenado Alvarez, Vasiliki Triantafyllia, Jesús Troya, Owen T.Y. Tsang, Liina Tserel, Eugene Y.K. Tso, Alessandra Tucci, Şadiye Kübra Tüter Öz, Matilde Valeria Ursini, Takanori Utsumi, Pierre Vabres, Juan Valencia-Ramos, Ana Maria Van Den Rym, Isabelle Vandernoot, Valentina Velez-Santamaria, Silvia Patricia Zuniga Veliz, Mateus C. Vidigal, Sébastien Viel, Cédric Villain, Marie E. Vilaire-Meunier, Judit Villar-García, Audrey Vincent, Dimitri Van der Linden, Alla Volokha, Fanny Vuotto, Els Wauters, Alan K.L. Wu, Tak-Chiu Wu, Aysun Yahşi, Osman Yesilbas, Mehmet Yildiz, Barnaby E. Young, Ufuk Yükselmiş, Marco Zecca, Valentina Zuccaro, Jens Van Praet, Bart N. Lambrecht, Eva Van Braeckel, Cédric Bosteels, Levi Hoste, Eric Hoste, Fré Bauters, Jozefien De Clercq, Catherine Heijmans, Hans Slabbynck, Leslie Naesens, Benoit Florkin, Mary-Anne Young, Amanda Willis, Paloma Lapuente-Suanzes, Ana de Andrés-Martín, Matilda Berkell, Valerio Carelli, Alessia Fiorentino, Surbhi Malhotra, Alessandro Mattiaccio, Tommaso Pippucci, Marco Seri, Evelina Tacconelli, Michiel van Agtmael, Anne Geke Algera, Brent Appelman, Frank van Baarle, Diane Bax, Martijn Beudel, Harm Jan Bogaard, Marije Bomers, Peter Bonta, Lieuwe Bos, Michela Botta, Justin de Brabander, Godelieve de Bree, Sanne de Bruin, David T.P. Buis, Marianna Bugiani, Esther Bulle, Osoul Chouchane, Alex Cloherty, Mirjam Dijkstra, Dave A. Dongelmans, Romein W.G. Dujardin, Paul Elbers, Lucas Fleuren, Suzanne Geerlings, Theo Geijtenbeek, Armand Girbes, Bram Goorhuis, Martin P. Grobusch, Florianne Hafkamp, Laura Hagens, Jorg Hamann, Vanessa Harris, Robert Hemke, Sabine M. Hermans, Leo Heunks, Markus Hollmann, Janneke Horn, Joppe W. Hovius, Menno D. de Jong, Rutger Koning, Endry H.T. Lim, Niels van Mourik, Jeaninne Nellen, Esther J. Nossent, Frederique Paulus, Edgar Peters, Dan A.I. Pina-Fuentes, Tom van der Poll, Bennedikt Preckel, Jan M. Prins, Jorinde Raasveld, Tom Reijnders, Maurits C.F. J. de Rotte, Michiel Schinkel, Marcus J. Schultz, Femke A.P. Schrauwen, Alex Schuurmans, Jaap Schuurmans, Kim Sigaloff, Marleen A. Slim, Patrick Smeele, Marry Smit, Cornelis S. Stijnis, Willemke Stilma, Charlotte Teunissen, Patrick Thoral, Anissa M. Tsonas, Pieter R. Tuinman, Marc van der Valk, Denise P. Veelo, Carolien Volleman, Heder de Vries, Lonneke A. Vught, Michèle van Vugt, Dorien Wouters, A.H. Zwinderman, Matthijs C. Brouwer, W. Joost Wiersinga, Alexander P.J. Vlaar, Miranda F. Tompkins, Camille Alba, Daniel N. Hupalo, John Rosenberger, Gauthaman Sukumar, Matthew D. Wilkerson, Xijun Zhang, Justin Lack, Andrew J. Oler, Kerry Dobbs, Ottavia M. Delmonte, Jeffrey J. Danielson, Andrea Biondi, Laura Rachele Bettini, Mariella D’Angiò, Ilaria Beretta, Luisa Imberti, Alessandra Sottini, Virginia Quaresima, Eugenia Quiros-Roldan, Camillo Rossi, Riccardo Castagnoli, Daniela Montagna, Amelia Licari, and Gian Luigi Marseglia

Subjects
HLA, association, asymptomatic infection, COVID-19, population stratification, Genetics, QH426-470
Abstract

Summary: Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B∗15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B∗15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the United States (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B∗15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections studied, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified.

Published
2024
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3. Characteristics and outcome of COVID-19 patients admitted to the ICU: a nationwide cohort study on the comparison between the consecutive stages of the COVID-19 pandemic in the Netherlands, an update

Author

Fabian Termorshuizen, Dave A. Dongelmans, Sylvia Brinkman, Ferishta Bakhshi-Raiez, M. Sesmu Arbous, Dylan W. de Lange, Bas C. T. van Bussel, Nicolette F. de Keizer, and the Dutch COVID-19 Research Consortium

Subjects
COVID-19, Coronavirus, Mortality, Outcome, Intensive Care, Critical Care, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background Previously, we reported a decreased mortality rate among patients with COVID-19 who were admitted at the ICU during the final upsurge of the second wave (February–June 2021) in the Netherlands. We examined whether this decrease persisted during the third wave and the phases with decreasing incidence of COVID-19 thereafter and brought up to date the information on patient characteristics. Methods Data from the National Intensive Care Evaluation (NICE)-registry of all COVID-19 patients admitted to an ICU in the Netherlands were used. Patient characteristics and rates of in-hospital mortality (the primary outcome) during the consecutive periods after the first wave (periods 2–9, May 25, 2020–January 31, 2023) were compared with those during the first wave (period 1, February–May 24, 2020). Results After adjustment for patient characteristics and ICU occupancy rate, the mortality risk during the initial upsurge of the third wave (period 6, October 5, 2021–January, 31, 2022) was similar to that of the first wave (ORadj = 1.01, 95%-CI [0.88–1.16]). The mortality rates thereafter decreased again (e.g., period 9, October 5, 2022–January, 31, 2023: ORadj = 0.52, 95%-CI [0.41–0.66]). Among the SARS-CoV-2 positive patients, there was a huge drop in the proportion of patients with COVID-19 as main reason for ICU admission: from 88.2% during the initial upsurge of the third wave to 51.7%, 37.3%, and 41.9% for the periods thereafter. Restricting the analysis to these patients did not modify the results on mortality. Conclusions The results show variation in mortality rates among critically ill COVID-19 patients across the calendar time periods that is not explained by differences in case-mix and ICU occupancy rates or by varying proportions of patients with COVID-19 as main reason for ICU admission. The consistent increase in mortality during the initial, rising phase of each separate wave might be caused by the increased virulence of the contemporary virus strain and lacking immunity to the new strain, besides unmeasured patient-, treatment- and healthcare system characteristics.

Published
2024
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4. The interaction of thrombocytopenia, hemorrhage, and platelet transfusion in venoarterial extracorporeal membrane oxygenation: a multicenter observational study

Author

Senta Jorinde Raasveld, Claudia van den Oord, Jimmy Schenk, Walter M. van den Bergh, Annemieke Oude Lansink - Hartgring, Franciska van der Velde, Jacinta J. Maas, Pablo van de Berg, Roberto Lorusso, Thijs S. R. Delnoij, Dinis Dos Reis Miranda, Erik Scholten, Fabio Silvio Taccone, Dieter F. Dauwe, Erwin De Troy, Greet Hermans, Federico Pappalardo, Evgeny Fominskiy, Višnja Ivancan, Robert Bojčić, Jesse de Metz, Bas van den Bogaard, Dirk W. Donker, Christiaan L. Meuwese, Martin De Bakker, Benjamin Reddi, José P. S. Henriques, Lars Mikael Broman, Dave A. Dongelmans, and Alexander P. J. Vlaar

Subjects
Thrombocytopenia, Platelet transfusion, Hemorrhage, Venoarterial extracorporeal membrane oxygenation, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background Thrombocytopenia, hemorrhage and platelet transfusion are common in patients supported with venoarterial extracorporeal membrane oxygenation (VA ECMO). However, current literature is limited to small single-center experiences with high degrees of heterogeneity. Therefore, we aimed to ascertain in a multicenter study the course and occurrence rate of thrombocytopenia, and to assess the association between thrombocytopenia, hemorrhage and platelet transfusion during VA ECMO. Methods This was a sub-study of a multicenter (N = 16) study on transfusion practices in patients on VA ECMO, in which a retrospective cohort (Jan-2018–Jul-2019) focusing on platelets was selected. The primary outcome was thrombocytopenia during VA ECMO, defined as mild (100–150·109/L), moderate (50–100·109/L) and severe (

Published
2023
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5. Moral distress and positive experiences of ICU staff during the COVID-19 pandemic: lessons learned

Author

Mark L. van Zuylen, Janine C. de Snoo-Trimp, Suzanne Metselaar, Dave A. Dongelmans, and Bert Molewijk

Subjects
COVID-19, Intensive care, Critical care, Multidisciplinary, Medical ethics, Moral challenges, Medical philosophy. Medical ethics, R723-726
Abstract

Abstract Background The COVID-19 pandemic causes moral challenges and moral distress for healthcare professionals and, due to an increased work load, reduces time and opportunities for clinical ethics support services. Nevertheless, healthcare professionals could also identify essential elements to maintain or change in the future, as moral distress and moral challenges can indicate opportunities to strengthen moral resilience of healthcare professionals and organisations. This study describes 1) the experienced moral distress, challenges and ethical climate concerning end-of-life care of Intensive Care Unit staff during the first wave of the COVID-19 pandemic and 2) their positive experiences and lessons learned, which function as directions for future forms of ethics support. Methods A cross-sectional survey combining quantitative and qualitative elements was sent to all healthcare professionals who worked at the Intensive Care Unit of the Amsterdam UMC - Location AMC during the first wave of the COVID-19 pandemic. The survey consisted of 36 items about moral distress (concerning quality of care and emotional stress), team cooperation, ethical climate and (ways of dealing with) end-of-life decisions, and two open questions about positive experiences and suggestions for work improvement. Results All 178 respondents (response rate: 25–32%) showed signs of moral distress, and experienced moral dilemmas in end-of-life decisions, whereas they experienced a relatively positive ethical climate. Nurses scored significantly higher than physicians on most items. Positive experiences were mostly related to ‘team cooperation’, ‘team solidarity’ and ‘work ethic’. Lessons learned were mostly related to ‘quality of care’ and ‘professional qualities’. Conclusions Despite the crisis, positive experiences related to ethical climate, team members and overall work ethic were reported by Intensive Care Unit staff and quality and organisation of care lessons were learned. Ethics support services can be tailored to reflect on morally challenging situations, restore moral resilience, create space for self-care and strengthen team spirit. This can improve healthcare professionals’ dealing of inherent moral challenges and moral distress in order to strengthen both individual and organisational moral resilience. Trial registration The trial was registered on The Netherlands Trial Register, number NL9177.

Published
2023
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6. Predicting responders to prone positioning in mechanically ventilated patients with COVID-19 using machine learning

Author

Tariq A. Dam, Luca F. Roggeveen, Fuda van Diggelen, Lucas M. Fleuren, Ameet R. Jagesar, Martijn Otten, Heder J. de Vries, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco A. A. Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Sesmu Arbous, Sebastiaan J. J. Vonk, Tomas Machado, Willem E. Herter, Harm-Jan de Grooth, Patrick J. Thoral, Armand R. J. Girbes, Mark Hoogendoorn, Paul W. G. Elbers, and The Dutch ICU Data Sharing Against COVID-19 Collaborators

Subjects
COVID-19, Mechanical ventilation, Acute respiratory distress syndrome, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, prone positioning is labor intensive and comes with potential adverse effects. Therefore, identifying which critically ill intubated COVID-19 patients will benefit may help allocate labor resources. Methods From the multi-center Dutch Data Warehouse of COVID-19 ICU patients from 25 hospitals, we selected all 3619 episodes of prone positioning in 1142 invasively mechanically ventilated patients. We excluded episodes longer than 24 h. Berlin ARDS criteria were not formally documented. We used supervised machine learning algorithms Logistic Regression, Random Forest, Naive Bayes, K-Nearest Neighbors, Support Vector Machine and Extreme Gradient Boosting on readily available and clinically relevant features to predict success of prone positioning after 4 h (window of 1 to 7 h) based on various possible outcomes. These outcomes were defined as improvements of at least 10% in PaO2/FiO2 ratio, ventilatory ratio, respiratory system compliance, or mechanical power. Separate models were created for each of these outcomes. Re-supination within 4 h after pronation was labeled as failure. We also developed models using a 20 mmHg improvement cut-off for PaO2/FiO2 ratio and using a combined outcome parameter. For all models, we evaluated feature importance expressed as contribution to predictive performance based on their relative ranking. Results The median duration of prone episodes was 17 h (11–20, median and IQR, N = 2632). Despite extensive modeling using a plethora of machine learning techniques and a large number of potentially clinically relevant features, discrimination between responders and non-responders remained poor with an area under the receiver operator characteristic curve of 0.62 for PaO2/FiO2 ratio using Logistic Regression, Random Forest and XGBoost. Feature importance was inconsistent between models for different outcomes. Notably, not even being a previous responder to prone positioning, or PEEP-levels before prone positioning, provided any meaningful contribution to predicting a successful next proning episode. Conclusions In mechanically ventilated COVID-19 patients, predicting the success of prone positioning using clinically relevant and readily available parameters from electronic health records is currently not feasible. Given the current evidence base, a liberal approach to proning in all patients with severe COVID-19 ARDS is therefore justified and in particular regardless of previous results of proning.

Published
2022
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7. Characteristics and outcome of COVID-19 patients admitted to the ICU: a nationwide cohort study on the comparison between the first and the consecutive upsurges of the second wave of the COVID-19 pandemic in the Netherlands

Author

Dave A. Dongelmans, Fabian Termorshuizen, Sylvia Brinkman, Ferishta Bakhshi-Raiez, M. Sesmu Arbous, Dylan W. de Lange, Bas C. T. van Bussel, Nicolette F. de Keizer, and the Dutch COVID-19 Research Consortium

Subjects
COVID-19, Coronavirus, Mortality, Outcome, Intensive Care, Critical Care, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background To assess trends in the quality of care for COVID-19 patients at the ICU over the course of time in the Netherlands. Methods Data from the National Intensive Care Evaluation (NICE)-registry of all COVID-19 patients admitted to an ICU in the Netherlands were used. Patient characteristics and indicators of quality of care during the first two upsurges (N = 4215: October 5, 2020–January 31, 2021) and the final upsurge of the second wave, called the ‘third wave’ (N = 4602: February 1, 2021–June 30, 2021) were compared with those during the first wave (N = 2733, February–May 24, 2020). Results During the second and third wave, there were less patients treated with mechanical ventilation (58.1 and 58.2%) and vasoactive drugs (48.0 and 44.7%) compared to the first wave (79.1% and 67.2%, respectively). The occupancy rates as fraction of occupancy in 2019 (1.68 and 1.55 vs. 1.83), the numbers of ICU relocations (23.8 and 27.6 vs. 32.3%) and the mean length of stay at the ICU (HRs of ICU discharge = 1.26 and 1.42) were lower during the second and third wave. No difference in adjusted hospital mortality between the second wave and the first wave was found, whereas the mortality during the third wave was considerably lower (OR = 0.80, 95% CI [0.71–0.90]). Conclusions These data show favorable shifts in the treatment of COVID-19 patients at the ICU over time. The adjusted mortality decreased in the third wave. The high ICU occupancy rate early in the pandemic does probably not explain the high mortality associated with COVID-19.

Published
2022
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8. Predictors for extubation failure in COVID-19 patients using a machine learning approach

Author

Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Adam Kantorik, Tom de Ruijter, Willem E. Herter, Martijn Beudel, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W. G. Elbers, and the Dutch ICU Data Sharing Against Covid-19 Collaborators

Subjects
Extubation, Prediction, Risk factors, Extubation failure, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (

Published
2021
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9. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Author

Lucas M. Fleuren, Tariq A. Dam, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Sesmu Arbous, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn-Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cina, Martijn Beudel, Willem E. Herter, Armand R. J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, and Paul W. G. Elbers

Subjects
Database, Big data, COVID-19, Data sharing, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Published
2021
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10. Risk factors for adverse outcomes during mechanical ventilation of 1152 COVID-19 patients: a multicenter machine learning study with highly granular data from the Dutch Data Warehouse

Author

Lucas M. Fleuren, Michele Tonutti, Daan P. de Bruin, Robbert C. A. Lalisang, Tariq A. Dam, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Nardo J. M. van der Meer, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Sefanja Achterberg, Harald J. Faber, A. Karakus, Menno Beukema, Robert Entjes, Paul de Jong, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Martijn Beudel, Nicolet F. de Keizer, Mark Hoogendoorn, Armand R. J. Girbes, Willem E. Herter, Paul W. G. Elbers, Patrick J. Thoral, and Dutch ICU Data Sharing Against COVID-19 Collaborators

Subjects
COVID-19, Mortality prediction, Risk factors, Machine learning, Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

Abstract Background The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential for prognostication, determining treatment intensity, and resource allocation. Previous studies have determined risk factors on admission only, and included a limited number of predictors. Therefore, using data from the highly granular and multicenter Dutch Data Warehouse, we developed machine learning models to identify risk factors for ICU mortality, ventilator-free days and ICU-free days during the course of invasive mechanical ventilation (IMV) in COVID-19 patients. Methods The DDW is a growing electronic health record database of critically ill COVID-19 patients in the Netherlands. All adult ICU patients on IMV were eligible for inclusion. Transfers, patients admitted for less than 24 h, and patients still admitted at time of data extraction were excluded. Predictors were selected based on the literature, and included medication dosage and fluid balance. Multiple algorithms were trained and validated on up to three sets of observations per patient on day 1, 7, and 14 using fivefold nested cross-validation, keeping observations from an individual patient in the same split. Results A total of 1152 patients were included in the model. XGBoost models performed best for all outcomes and were used to calculate predictor importance. Using Shapley additive explanations (SHAP), age was the most important demographic risk factor for the outcomes upon start of IMV and throughout its course. The relative probability of death across age values is visualized in Partial Dependence Plots (PDPs), with an increase starting at 54 years. Besides age, acidaemia, low P/F-ratios and high driving pressures demonstrated a higher probability of death. The PDP for driving pressure showed a relative probability increase starting at 12 cmH2O. Conclusion Age is the most important demographic risk factor of ICU mortality, ICU-free days and ventilator-free days throughout the course of invasive mechanical ventilation in critically ill COVID-19 patients. pH, P/F ratio, and driving pressure should be monitored closely over the course of mechanical ventilation as risk factors predictive of these outcomes.

Published
2021
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11. Prioritizing suicide prevention guideline recommendations in specialist mental healthcare: a Delphi study

Author

Kim Setkowski, Anton J. L. M. van Balkom, Dave A. Dongelmans, and Renske Gilissen

Subjects
Suicide prevention, Implementation, Guideline recommendations, Mental healthcare, Delphi study, Quality indicator, Psychiatry, RC435-571
Abstract

Abstract Background The Delphi technique is a proven and reliable method to create common definitions and to achieve convergence of opinion. This study aimed to prioritize suicide prevention guideline recommendations and to develop a set of quality indicators (QIs) for suicide prevention in specialist mental healthcare. Methods This study selected 12 key recommendations from the guideline to modify them into QIs. After feedback from two face-to-face workgroup sessions, 11 recommendations were rephrased and selected to serve as QIs. Next, a Delphi study with the 11 QIs was performed to achieve convergence of opinion among a panel of 90 participants (23 suicide experts, 23 members of patients’ advisory boards or experts with experiences in suicidal behavior and 44 mental healthcare professionals). The participants scored the 11 QIs on two selection criteria: relevance (it affects the number of suicides in the institution) and action orientation (institutions or professionals themselves can influence it) using a 5-point Likert scale. Also, data analysts working in mental healthcare institutions (MHIs) rated each QI on feasibility (is it feasible to monitor and extract from existing systems). Consensus was defined as 70% agreement with priority scores of four or five. Results Out of the 11 recommendations, participants prioritized five recommendations as relevant and action-oriented in optimizing the quality of care for suicide prevention: 1) screening for suicidal thoughts and behavior, 2) safety plan, 3) early follow-up on discharge, 4) continuity of care and 5) involving family or significant others. Only one of the 11 recommendations early follow-up on discharge reached consensus on all three selection criteria (relevance, action orientation, and feasibility). Conclusions The prioritization of relevant and action-oriented suicide prevention guideline recommendations is an important step towards the improvement of quality of care in specialist mental healthcare.

Published
2020
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12. Overweight and Obesity Are Associated With Acute Kidney Injury and Acute Respiratory Distress Syndrome, but Not With Increased Mortality in Hospitalized COVID-19 Patients: A Retrospective Cohort Study

Author

Jamie van Son, Sabrina M. Oussaada, Aydin Şekercan, Martijn Beudel, Dave A. Dongelmans, Sander van Assen, Ingo A. Eland, Hazra S. Moeniralam, Tom P. J. Dormans, Colin A. J. van Kalkeren, Renée A. Douma, Daisy Rusch, Suat Simsek, Limmie Liu, Ruud S. Kootte, Caroline E. Wyers, Richard G. IJzerman, Joop P. van den Bergh, Coen D. A. Stehouwer, Max Nieuwdorp, Kasper W. ter Horst, and Mireille J. Serlie

Subjects
COVID-19, obesity, overweight, complications, mortality, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

ObjectiveTo evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19.DesignRetrospective, observational cohort study.MethodsWe performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes.ResultsOut of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients.ConclusionIn this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.

Published
2021
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13. Some Patients Are More Equal Than Others: Variation in Ventilator Settings for Coronavirus Disease 2019 Acute Respiratory Distress Syndrome

Author

Tariq A. Dam, MD, Harm-Jan de Grooth, MD, PhD, Thomas Klausch, PhD, Lucas M. Fleuren, MD, Daan P. de Bruin, MSc, Robert Entjes, MD, Thijs C. D. Rettig, MD, PhD, Dave A. Dongelmans, MD, PhD, Age D. Boelens, MD, Sander Rigter, MD, Stefaan H. A. Hendriks, MD, Remko de Jong, MD, Marlijn J. A Kamps, MD, Marco Peters, MD, A. Karakus, MD, Diederik Gommers, MD, PhD, Dharmanand Ramnarain, MD, Evert-Jan Wils, MD, PhD, Sefanja Achterberg, MD, PhD, Ralph Nowitzky, MD, Walter van den Tempel, MD, Cornelis P. C. de Jager, MD, PhD, Fleur G. C. A. Nooteboom, MD, Evelien Oostdijk, MD, PhD, Peter Koetsier, MD, Alexander D. Cornet, MD, PhD, FRCP, Auke C. Reidinga, MD, Wouter de Ruijter, MD, PhD, Rob J. Bosman, MD, Tim Frenzel, MD, PhD, Louise C. Urlings-Strop, MD, PhD, Paul de Jong, MD, Ellen G. M. Smit, MD, Olaf L. Cremer, MD, PhD, D. Jannet Mehagnoul-Schipper, MD, PhD, Harald J. Faber, MD, Judith Lens, MD, Gert B. Brunnekreef, MD, Barbara Festen-Spanjer, MD, Tom Dormans, MD, PhD, Annemieke Dijkstra, MD, Bram Simons, MD, A. A. Rijkeboer, MD, Sesmu Arbous, MD, PhD, Marcel Aries, MD, PhD, Menno Beukema, MD, Daniël Pretorius, MD, Rutger van Raalte, MD, Martijn van Tellingen, MD, EDIC, Niels C. Gritters van den Oever, MD, Robbert C. A. Lalisang, MD, Michele Tonutti, MRes, Armand R. J. Girbes, MD, PhD, EDIC, Mark Hoogendoorn, PhD, Patrick J. Thoral, MD, EDIC, Paul W. G. Elbers, MD, PhD, EDIC, on behalf of the Dutch ICU Data Sharing Against COVID-19 Collaborators, Remko van den Akker, Tom A. Rijpstra, M. C. Reuland, Klaas Sierk Arnold, Arend Jan Meinders, Nicolas Schroten, Laura van Manen, Leon Montenij, Julia Koeter, J. W. Fijen, Jasper van Bommel, Roy van den Berg, Martha de Bruin, Roger van Rietschote, Ellen van Geest, Koen S. Simons, Anisa Hana, Joost Labout, Michael Kuiper, Albertus Beishuizen, Bart van de Gaauw, Roos Renckens, B. van den Bogaard, Peter Pickkers, Pim van der Heiden, Dennis Geutjes, Claudia (C. W.) van Gemeren, Emma Rademaker, Frits H. M. van Osch, Johan Lutisan, Jacomar J. M. van Koesveld, Bart P. Grady, Martijn de Kruif, Martin E. Haan, Luca Roggeveen, Dagmar M. Ouweneel, Ronald Driessen, Jan Peppink, G. J. Zijlstra, A. J. van Tienhoven, Evelien van der Heiden, Jan Jaap Spijkstra, Hans van der Spoel, Angelique de Man, Heder J. de Vries, Fuda van Diggelen, Ali el Hassouni, David Romero Guzman, Sandjai Bhulai, Sebastiaan J. J. Vonk, Mattia Fornasa, Tomas Machado, Adam Izdebski, Taco Houwert, Hidde Hovenkamp, Roberto Noorduijn Londono, Davide Quintarelli, Martijn G. Scholtemeijer, Aletta A. de Beer, Giovanni Cinà, Willem E. Herter, Michael de Neree tot Babberich, Olivier Thijssens, Lot Wagemakers, Hilde G. A. van der Pol, Tom Hendriks, Julie Berend, Virginia Ceni Silva, Robert F. J. Kullberg, Leo Heunks, Nicole Juffermans, Arjen J. C. Slooter, Martijn Beudel, and Nicolet F. de Keizer

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

OBJECTIVES:. As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with a unique opportunity as the population of coronavirus disease 2019 patients requiring invasive mechanical ventilation is relatively homogeneous compared with other ICU populations. We hypothesize that the novelty of coronavirus disease 2019 and the uncertainty over its similarity with noncoronavirus disease 2019 acute respiratory distress syndrome resulted in substantial practice variation between hospitals during the first and second waves of coronavirus disease 2019 patients. DESIGN:. Multicenter retrospective cohort study. SETTING:. Twenty-five hospitals in the Netherlands from February 2020 to July 2020, and 14 hospitals from August 2020 to December 2020. PATIENTS:. One thousand two hundred ninety-four critically ill intubated adult ICU patients with coronavirus disease 2019 were selected from the Dutch Data Warehouse. Patients intubated for less than 24 hours, transferred patients, and patients still admitted at the time of data extraction were excluded. MEASUREMENTS AND MAIN RESULTS:. We aimed to estimate between-ICU practice variation in selected ventilation parameters (positive end-expiratory pressure, Fio2, set respiratory rate, tidal volume, minute volume, and percentage of time spent in a prone position) on days 1, 2, 3, and 7 of intubation, adjusted for patient characteristics as well as severity of illness based on Pao2/Fio2 ratio, pH, ventilatory ratio, and dynamic respiratory system compliance during controlled ventilation. Using multilevel linear mixed-effects modeling, we found significant (p ≤ 0.001) variation between ICUs in all ventilation parameters on days 1, 2, 3, and 7 of intubation for both waves. CONCLUSIONS:. This is the first study to clearly demonstrate significant practice variation between ICUs related to mechanical ventilation parameters that are under direct control by intensivists. Their effect on clinical outcomes for both coronavirus disease 2019 and other critically ill mechanically ventilated patients could have widespread implications for the practice of intensive care medicine and should be investigated further by causal inference models and clinical trials.

Published
2021
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14. Facilitating action planning within audit and feedback interventions: a mixed-methods process evaluation of an action implementation toolbox in intensive care

Author

Wouter T. Gude, Marie-José Roos-Blom, Sabine N. van der Veer, Dave A. Dongelmans, Evert de Jonge, Niels Peek, and Nicolette F. de Keizer

Subjects
Intensive care, Medical audit, Feedback, Quality improvement, Quality indicators, Medicine (General), R5-920
Abstract

Abstract Background Audit and feedback (A&F) is more effective if it facilitates action planning, but little is known about how best to do this. We developed an electronic A&F intervention with an action implementation toolbox to improve pain management in intensive care units (ICUs); the toolbox contained suggested actions for improvement. A head-to-head randomised trial demonstrated that the toolbox moderately increased the intervention’s effectiveness when compared with A&F only. Objective To understand the mechanisms through which A&F with action implementation toolbox facilitates action planning by ICUs to increase A&F effectiveness. Methods We extracted all individual actions from action plans developed by ICUs that received A&F with (n = 10) and without (n = 11) toolbox for 6 months and classified them using Clinical Performance Feedback Intervention Theory. We held semi-structured interviews with participants during the trial. We compared the number and type of planned and completed actions between study groups and explored barriers and facilitators to effective action planning. Results ICUs with toolbox planned more actions directly aimed at improving practice (p = 0.037) and targeted a wider range of practice determinants compared to ICUs without toolbox. ICUs with toolbox also completed more actions during the study period, but not significantly (p = 0.142). ICUs without toolbox reported more difficulties in identifying what actions they could take. Regardless of the toolbox, all ICUs still experienced barriers relating to the feedback (low controllability, accuracy) and organisational context (competing priorities, resources, cost). Conclusions The toolbox helped health professionals to broaden their mindset about actions they could take to change clinical practice. Without the toolbox, professionals tended to focus more on feedback verification and exploring solutions without developing intentions for actual change. All feedback recipients experienced organisational barriers that inhibited eventual completion of actions. Trial registration ClinicalTrials.gov, NCT02922101. Registered on 26 September 2016.

Published
2019
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15. Clinical features and prognostic factors in Covid-19: A prospective cohort study

Author

Sanne de Bruin, Lieuwe D. Bos, Marian A. van Roon, Anita M. Tuip-de Boer, Alex R. Schuurman, Marleen J.A. Koel-Simmelinck, Harm Jan Bogaard, Pieter Roel Tuinman, Michiel A. van Agtmael, Jörg Hamann, Charlotte E. Teunissen, W. Joost Wiersinga, A.H. (Koos) Zwinderman, Matthijs C. Brouwer, Diederik van de Beek, Alexander P.J. Vlaar, Michiel van Agtmael, Anne Geke Algera, Brent Appelman, Frank van Baarle, Diane Bax, Martijn Beudel, Marije Bomers, Peter Bonta, Lieuwe Bos, Michela Botta, Justin de Brabander, Godelieve de Bree, David T.P. Buis, Marianna Bugiani, Esther Bulle, Osoul Chouchane, Alex Cloherty, Maurits C.F.J. de Rotte, Mirjam Dijkstra, Dave A. Dongelmans, Romein W.G. Dujardin, Paul Elbers, Lucas Fleuren, Suzanne Geerlings, Theo Geijtenbeek, Armand Girbes, Bram Goorhuis, Martin P. Grobusch, Florianne Hafkamp, Laura Hagens, Jorg Hamann, Vanessa Harris, Robert Hemke, Sabine M. Hermans, Leo Heunks, Markus Hollmann, Janneke Horn, Joppe W. Hovius, Menno D. de Jong, Rutger Koning, Endry H.T. Lim, Niels van Mourik, Jeannine Nellen, Esther J. Nossent, Frederique Paulus, Edgar Peters, Dan A.I. Piña-Fuentes, Tom van der Poll, Bennedikt Preckel, Jan M. Prins, Jorinde Raasveld, Tom Reijnders, Michiel Schinkel, Femke A.P. Schrauwen, Marcus J. Schultz, Alex Schuurmans, Jaap Schuurmans, Kim Sigaloff, Marleen A. Slim, Patrick Smeele, Marry Smit, Cornelis S. Stijnis, Willemke Stilma, Charlotte Teunissen, Patrick Thoral, Anissa M. Tsonas, Pieter R. Tuinman, Marc van der Valk, Denise Veelo, Carolien Volleman, Heder de Vries, Lonneke A. Vught, Michèle van Vugt, Dorien Wouters, and A.H (Koos) Zwinderman

Subjects
COVID-19, Prognosis, Biomarker, Pathway analysis, Clinical features, Medicine, Medicine (General), R5-920
Abstract

Background: Mortality rates are high among hospitalized patients with COVID-19, especially in those intubated on the ICU. Insight in pathways associated with unfavourable outcome may lead to new treatment strategies. Methods: We performed a prospective cohort study of patients with COVID-19 admitted to general ward or ICU who underwent serial blood sampling. To provide insight in the pathways involved in disease progression, associations were estimated between outcome risk and serial measurements of 64 biomarkers in potential important pathways of COVID-19 infection (inflammation, tissue damage, complement system, coagulation and fibrinolysis) using joint models combining Cox regression and linear mixed-effects models. For patients admitted to the general ward, the primary outcome was admission to the ICU or mortality (unfavourable outcome). For patients admitted to the ICU, the primary outcome was 12-week mortality. Findings: A total of 219 patients were included: 136 (62%) on the ward and 119 patients (54%) on the ICU; 36 patients (26%) were included in both cohorts because they were transferred from general ward to ICU. On the general ward, 54 of 136 patients (40%) had an unfavourable outcome and 31 (23%) patients died. On the ICU, 54 out of 119 patients (45%) died. Unfavourable outcome on the general ward was associated with changes in concentrations of IL-6, IL-8, IL-10, soluble Receptor for Advanced Glycation End Products (sRAGE), vascular cell adhesion molecule 1 (VCAM-1) and Pentraxin-3. Death on the ICU was associated with changes in IL-6, IL-8, IL-10, sRAGE, VCAM-1, Pentraxin-3, urokinase-type plasminogen activator receptor, IL-1-receptor antagonist, CD14, procalcitonin, tumor necrosis factor alfa, tissue factor, complement component 5a, Growth arrest–specific 6, angiopoietin 2, and lactoferrin. Pathway analysis showed that unfavourable outcome on the ward was mainly driven by chemotaxis and interleukin production, whereas death on ICU was associated with a variety of pathways including chemotaxis, cell-cell adhesion, innate host response mechanisms, including the complement system, viral life cycle regulation, angiogenesis, wound healing and response to corticosteroids. Interpretation: Clinical deterioration in patients with severe COVID-19 involves multiple pathways, including chemotaxis and interleukin production, but also endothelial dysfunction, the complement system, and immunothrombosis. Prognostic markers showed considerable overlap between general ward and ICU patients, but we identified distinct differences between groups that should be considered in the development and timing of interventional therapies in COVID-19. Funding: Amsterdam UMC, Amsterdam UMC Corona Fund, and Dr. C.J. Vaillant Fonds.

Published
2021
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16. RELAx – REstricted versus Liberal positive end-expiratory pressure in patients without ARDS: protocol for a randomized controlled trial

Author

Anna Geke Algera, Luigi Pisani, Dennis C. J. Bergmans, Sylvia den Boer, Corianne A. J. de Borgie, Frank H. Bosch, Karina Bruin, Thomas G. Cherpanath, Rogier M. Determann, Arjen M. Dondorp, Dave A. Dongelmans, Henrik Endeman, Jasper J. Haringman, Janneke Horn, Nicole P. Juffermans, David M. van Meenen, Nardo J. van der Meer, Maruschka P. Merkus, Hazra S. Moeniralam, Ilse Purmer, Pieter Roel Tuinman, Mathilde Slabbekoorn, Peter E. Spronk, Alexander P. J. Vlaar, Marcelo Gama de Abreu, Paolo Pelosi, Ary Serpa Neto, Marcus J. Schultz, Frederique Paulus, and for the RELAx Investigators and the PROVE Network Investigators

Subjects
Artificial ventilation, Invasive ventilation, Mechanical ventilation, Positive end-expiratory pressure, PEEP, Non-injured lungs, Medicine (General), R5-920
Abstract

Abstract Background Evidence for benefit of high positive end-expiratory pressure (PEEP) is largely lacking for invasively ventilated, critically ill patients with uninjured lungs. We hypothesize that ventilation with low PEEP is noninferior to ventilation with high PEEP with regard to the number of ventilator-free days and being alive at day 28 in this population. Methods/Design The “REstricted versus Liberal positive end-expiratory pressure in patients without ARDS” trial (RELAx) is a national, multicenter, randomized controlled, noninferiority trial in adult intensive care unit (ICU) patients with uninjured lungs who are expected not to be extubated within 24 h. RELAx will run in 13 ICUs in the Netherlands to enroll 980 patients under invasive ventilation. In all patients, low tidal volumes are used. Patients assigned to ventilation with low PEEP will receive the lowest possible PEEP between 0 and 5 cm H2O, while patients assigned to ventilation with high PEEP will receive PEEP of 8 cm H2O. The primary endpoint is the number of ventilator-free days and being alive at day 28, a composite endpoint for liberation from the ventilator and mortality until day 28, with a noninferiority margin for a difference between groups of 0.5 days. Secondary endpoints are length of stay (LOS), mortality, and occurrence of pulmonary complications, including severe hypoxemia, major atelectasis, need for rescue therapies, pneumonia, pneumothorax, and development of acute respiratory distress syndrome (ARDS). Hemodynamic support and sedation needs will be collected and compared. Discussion RELAx will be the first sufficiently sized randomized controlled trial in invasively ventilated, critically ill patients with uninjured lungs using a clinically relevant and objective endpoint to determine whether invasive, low-tidal-volume ventilation with low PEEP is noninferior to ventilation with high PEEP. Trial registration ClinicalTrials.gov, ID:NCT03167580. Registered on 23 May 2017.

Published
2018
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17. Health professionals’ perceptions about their clinical performance and the influence of audit and feedback on their intentions to improve practice: a theory-based study in Dutch intensive care units

Author

Wouter T. Gude, Marie-José Roos-Blom, Sabine N. van der Veer, Dave A. Dongelmans, Evert de Jonge, Jill J. Francis, Niels Peek, and Nicolette F. de Keizer

Subjects
Intensive care, Medical audit, Feedback, Quality improvement, Quality indicators, Medicine (General), R5-920
Abstract

Abstract Background Audit and feedback aims to guide health professionals in improving aspects of their practice that need it most. Evidence suggests that feedback fails to increase accuracy of professional perceptions about clinical performance, which likely reduces audit and feedback effectiveness. This study investigates health professionals’ perceptions about their clinical performance and the influence of feedback on their intentions to change practice. Methods We conducted an online laboratory experiment guided by Control Theory with 72 intensive care professionals from 21 units. For each of four new pain management indicators, we collected professionals’ perceptions about their clinical performance; peer performance; targets; and improvement intentions before and after receiving first-time feedback. An electronic audit and feedback dashboard provided ICU’s own performance, median and top 10% peer performance, and improvement recommendations. The experiment took place approximately 1 month before units enrolled into a cluster-randomised trial assessing the impact of adding a toolbox with suggested actions and materials to improve intensive care pain management. During the experiment, the toolbox was inaccessible; all participants accessed the same version of the dashboard. Results We analysed 288 observations. In 53.8%, intensive care professionals overestimated their clinical performance; but in only 13.5%, they underestimated it. On average, performance was overestimated by 22.9% (on a 0–100% scale). Professionals similarly overestimated peer performance, and set targets 20.3% higher than the top performance benchmarks. In 68.4% of cases, intentions to improve practice were consistent with actual gaps in performance, even before professionals had received feedback; which increased to 79.9% after receiving feedback (odds ratio, 2.41; 95% CI, 1.53 to 3.78). However, in 56.3% of cases, professionals still wanted to improve care aspects at which they were already top performers. Alternatively, in 8.3% of cases, they lacked improvement intentions because they did not consider indicators important; did not trust the data; or deemed benchmarks unrealistic. Conclusions Audit and feedback helps health professionals to work on aspects for which improvement is recommended. Given the abundance of professionals’ prior good improvement intentions, the limited effects typically found by audit and feedback studies are likely predominantly caused by barriers to translation of intentions into actual change in clinical practice. Trial registration ClinicalTrials.gov NCT02922101. Registered 26 September 2016.

Published
2018
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18. Electronic audit and feedback intervention with action implementation toolbox to improve pain management in intensive care: protocol for a laboratory experiment and cluster randomised trial

Author

Wouter T. Gude, Marie-José Roos-Blom, Sabine N. van der Veer, Evert de Jonge, Niels Peek, Dave A. Dongelmans, and Nicolette F. de Keizer

Subjects
Intensive care, Medical audit, Feedback, Quality improvement, Quality indicators, Randomised controlled trial, Medicine (General), R5-920
Abstract

Abstract Background Audit and feedback is often used as a strategy to improve quality of care, however, its effects are variable and often marginal. In order to learn how to design and deliver effective feedback, we need to understand their mechanisms of action. This theory-informed study will investigate how electronic audit and feedback affects improvement intentions (i.e. information–intention gap), and whether an action implementation toolbox with suggested actions and materials helps translating those intentions into action (i.e. intention–behaviour gap). The study will be executed in Dutch intensive care units (ICUs) and will be focused on pain management. Methods and design We will conduct a laboratory experiment with individual ICU professionals to assess the impact of feedback on their intentions to improve practice. Next, we will conduct a cluster randomised controlled trial with ICUs allocated to feedback without or feedback with action implementation toolbox group. Participants will not be told explicitly what aspect of the intervention is randomised; they will only be aware that there are two variations of providing feedback. ICUs are eligible for participation if they submit indicator data to the Dutch National Intensive Care Evaluation (NICE) quality registry and agree to allocate a quality improvement team that spends 4 h per month on the intervention. All participating ICUs will receive access to an online quality dashboard that provides two functionalities: gaining insight into clinical performance on pain management indicators and developing action plans. ICUs with access to the toolbox can develop their action plans guided by a list of potential barriers in the care process, associated suggested actions, and supporting materials to facilitate implementation of the actions. The primary outcome measure for the laboratory experiment is the proportion of improvement intentions set by participants that are consistent with recommendations based on peer comparisons; for the randomised trial it is the proportion of patient shifts during which pain has been adequately managed. We will also conduct a process evaluation to understand how the intervention is implemented and used in clinical practice, and how implementation and use affect the intervention’s impact. Discussion The results of this study will inform care providers and managers in ICU and other clinical settings how to use indicator-based performance feedback in conjunction with an action implementation toolbox to improve quality of care. Within the ICU context, this study will produce concrete and directly applicable knowledge with respect to what is or is not effective for improving pain management, and under which circumstances. The results will further guide future research that aims to understand the mechanisms behind audit and feedback and contribute to identifying the active ingredients of successful interventions. Trial registration ClinicalTrials.gov NCT02922101 . Registered 26 September 2016.

Published
2017
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23. Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges.

Author

Martijn C. Schut, Dave A. Dongelmans, Dylan W. De Lange, Sylvia Brinkman, D. P. Verbiest, L. F. te Velde, E. M. van Driel, T. Rijpstra, P. H. J. Elbers, A. P. I. Houwink, L. Georgieva, E. Verweij, R. M. de Jong, F. M. van Iersel, T. J. J. Koning, E. Rengers, N. Kusadasi, M. L. Erkamp, R. Van den Berg, C. J. M. G. Jacobs, J. L. Epker, A. A. Rijkeboer, M. T. de Bruin, P. Spronk, A. Draisma, D. J. Versluis, A. E. van den Berg, M. Vrolijk-de Mos, J. A. Lens, R. V. Pruijsten, H. Kieft, J. Rozendaal, Fleur G. C. A. Nooteboom, D. P. Boer, I. T. A. Janssen, L. van Gulik, M. P. Koetsier, V. M. Silderhuis, R. M. Schnabel, I. Drogt, Wouter de Ruijter, Robert-Jan Bosman, T. Frenzel, Louise C. Urlings-Strop, A. Dijkhuizen, I. Z. Hené, A. R. de Meijer, J. W. M. Holtkamp, N. Postma, A. J. G. H. Bindels, R. M. J. Wesselink, E. R. van Slobbe-Bijlsma, Peter H. J. van der Voort, B. J. W. Eikemans, D. Jannet Mehagnoul-Schipper, D. Gommers, J. G. Lutisan, M. Hoeksema, M. G. W. Barnas, Barbara Festen-Spanjer, M. van Lieshout, N. C. Gritters, Martijn van Tellingen, Gert B. Brunnekreef, J. Vandeputte, T. P. J. Dormans, M. E. Hoogendoorn, M. de Graaff, D. Moolenaar, Auke C. Reidinga, J. J. Spijkstra, R. de Waal, D. Ramnarain, Nicolette F. de Keizer, and Ameen Abu-Hanna

Published
2024
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28. A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patients.

Author

Adam Izdebski, Patrick J. Thoral, Robbert C. A. Lalisang, Dean M. McHugh, Robert Entjes, Nardo J. M. van der Meer, Dave A. Dongelmans, Age D. Boelens, Sander Rigter, Stefaan H. A. Hendriks, Remko de Jong, Marlijn J. A. Kamps, Marco A. A. Peters, A. Karakus, Diederik Gommers, Dharmanand Ramnarain, Evert-Jan Wils, Sefanja Achterberg, Ralph Nowitzky, Walter van den Tempel, Cornelis P. C. de Jager, Fleur G. C. A. Nooteboom, Evelien Oostdijk, Peter Koetsier, Alexander D. Cornet, Auke C. Reidinga, Wouter de Ruijter, Rob J. Bosman, Tim Frenzel, Louise C. Urlings-Strop, Paul de Jong, Ellen G. M. Smit, Olaf L. Cremer, Frits H. M. van Osch, Harald J. Faber, Judith Lens, Gert B. Brunnekreef, Barbara Festen-Spanjer, Tom Dormans, Bram Simons, A. A. Rijkeboer, Annemieke Dijkstra, M. Sesmu Arbous, Marcel Aries, Menno Beukema, Rutger van Raalte, Martijn van Tellingen, Niels C. Gritters van den Oever, Paul W. G. Elbers, and Giovanni Cinà

Published
2021

30. Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.

Author

Iacopo Vagliano, Martijn C. Schut, Ameen Abu-Hanna, Dave A. Dongelmans, Dylan W. De Lange, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Remko de Jong, Marco A. A. Peters, Marlijn J. A. Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G. C. A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G. M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P. C. de Jager, Stefaan H. A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, Attila Karakus, Robert Entjes, Paul de Jong, Thijs C. D. Rettig, Merijn C. Reuland, M. Sesmu Arbous, Lucas M. Fleuren, Tariq A. Dam, Patrick J. Thoral, Robbert C. A. Lalisang, Michele Tonutti, Daan P. de Bruin, Paul W. G. Elbers, and Nicolette F. de Keizer

Published
2022
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32. Heterogeneity in the Identification of Potential Drug-Drug Interactions in the Intensive Care Unit

Author

Tinka Bakker, Dave A. Dongelmans, Ehsan Nabovati, Saeid Eslami, Nicolette F. Keizer, Ameen Abu‐Hanna, and Joanna E. Klopotowska

Subjects
Pharmacology, drug-drug interactions, pharmacoepidemiology, Critical Care, Databases, Factual, medication safety, Hospitalization, Intensive Care Units, drug-drug interaction identification, patient safety, Humans, Drug Interactions, Pharmacology (medical), intensive care
Abstract

Patients admitted to the intensive care unit (ICU) are frequently exposed to potential drug-drug interactions (pDDIs). However, reported frequencies of pDDIs in the ICU vary widely between studies. This can be partly explained by significant variation in their methodological approach. Insight into methodological choices affecting pDDI frequency would allow for improved comparison and synthesis of reported pDDI frequencies. This study aimed to evaluate the association between methodological choices and pDDI frequency and formulate reporting recommendations for pDDI frequency studies in the ICU. The MEDLINE database was searched to identify papers reporting pDDI frequency in ICU patients. For each paper, the pDDI frequency and methodological choices such as pDDI definition and pDDI knowledge base were extracted, and the risk of bias was assessed. Each paper was categorized as reporting a low, medium, or high pDDI frequency. We sought associations between methodological choices and pDDI frequency group. Based on this comparison, reporting recommendations were formulated. Analysis of methodological choices showed significant heterogeneity between studies, and 65% of the studies had a medium to high risk of bias. High risk of bias, small sample size, and use of drug prescriptions instead of administrations were related to a higher pDDI frequency. The findings of this review may support researchers in designing a reliable methodology assessing pDDI frequency in ICU patients. The reporting recommendations may contribute to standardization, comparison, and synthesis of pDDI frequency studies, ultimately improving knowledge about pDDIs in and outside the ICU setting.

Published
2022
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33. Incorrect application of the KDIGO acute kidney injury staging criteria

Author

Izak A R Yasrebi-de Kom, Dave A Dongelmans, Ameen Abu-Hanna, Martijn C Schut, Nicolette F de Keizer, John A Kellum, Kitty J Jager, Joanna E Klopotowska, Graduate School, Medical Informatics, APH - Methodology, APH - Quality of Care, Intensive Care Medicine, APH - Aging & Later Life, APH - Digital Health, ACS - Pulmonary hypertension & thrombosis, and APH - Global Health

Subjects
KDIGO, Transplantation, acute kidney injury, Nephrology, staging error, epidemiology, urologic and male genital diseases, clinical practice guidelines
Abstract

BackgroundRecent research demonstrated substantial heterogeneity in the Kidney Disease: Improving Global Outcomes (KDIGO) acute kidney injury (AKI) diagnosis and staging criteria implementations in clinical research. Here we report an additional issue in the implementation of the criteria: the incorrect description and application of a stage 3 serum creatinine (SCr) criterion. Instead of an increase in SCr to or beyond 4.0 mg/dL, studies apparently interpreted this criterion as an increase in SCr by 4.0 mg/dL.MethodsUsing a sample of 8124 consecutive intensive care unit (ICU) admissions, we illustrate the implications of such incorrect application. The AKI stage distributions associated with the correct and incorrect stage 3 SCr criterion implementations were compared, both with and without the stage 3 renal replacement therapy (RRT) criterion. In addition, we compared chronic kidney disease presence, ICU mortality rates and hospital mortality rates associated with each of the AKI stages and the misclassified cases.ResultsWhere incorrect implementation of the SCr stage 3 criterion showed a stage 3 AKI rate of 29%, correct implementation revealed a rate of 34%, mainly due to shifts from stage 1 to stage 3. Without the stage 3 RRT criterion, the stage 3 AKI rates were 9% and 19% after incorrect and correct implementation, respectively. The ICU and hospital mortality rates in cases misclassified as stage 1 or 2 were similar to those in cases correctly classified as stage 1 instead of stage 3.ConclusionsWhile incorrect implementation of the SCr stage 3 criterion has significant consequences for AKI severity epidemiology, consequences for clinical decision making may be less severe. We urge researchers and clinicians to verify their implementation of the AKI staging criteria.

Published
2022

34. Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care

Author

Tim Frenzel, Nicolas Bennett, Tariq A Dam, Johan Mårtensson, Drago Plecko, Tom Dormans, Olaf L. Cremer, Gert B. Brunnekreef, Marco Peters, Judith Lens, Paul W. G. Elbers, Fleur G C A Nooteboom, Attila Karakus, Dharmanand Ramnarain, Sefanja Achterberg, Alexander D. Cornet, Evert-Jan Wils, Peter Koetsier, Patrick Thoral, Louise C Urlings-Strop, Robbert C. A. Lalisang, Paul de Jong, Barbara Festen-Spanjer, Stefaan H A Hendriks, Wouter de Ruijter, Daan P de Bruin, Thijs C D Rettig, Sebastiaan J J Vonk, Sander Rigter, Auke C Reidinga, Lucas M. Fleuren, Age D Boelens, Remko de Jong, Ellen G M Smit, Dave A Dongelmans, Cornelis P.C. de Jager, Harald J. Faber, Ralph Nowitzky, Walter van den Tempel, Rinaldo Bellomo, Rob J. Bosman, Martin E Haan, D Jannet Mehagnoul-Schipper, Marlijn J A Kamps, Evelien A. N. Oostdijk, Robert Entjes, Diederik Gommers, Intensive Care Medicine, AII - Infectious diseases, APH - Quality of Care, Intensive care medicine, VU University medical center, ACS - Microcirculation, ACS - Diabetes & metabolism, and Intensive Care

Subjects
Adult, Male, medicine.medical_specialty, Critical Care, medicine.medical_treatment, mechanical ventilation, COVID‐19, Intensive care, Internal medicine, medicine, Illness severity, Humans, Multicenter Studies as Topic, Hospital Mortality, corona virus, Blood urea nitrogen, Research Articles, Aged, Retrospective Studies, intensive care, Mechanical ventilation, business.industry, SARS-CoV-2, Other Research Radboud Institute for Health Sciences [Radboudumc 0], Glasgow Coma Scale, Patient Acuity, respiratory failure, COVID-19, General Medicine, Prognosis, Intensive Care Units, Observational Studies as Topic, Anesthesiology and Pain Medicine, Respiratory failure, Cohort, Observational study, business, Research Article
Abstract

Background The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. Methods This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. Results Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/−24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71–0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64–0.71], 0.61 [CI 0.58–0.66], 0.67 [CI 0.63–0.70], 0.70 [CI 0.67–0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). Conclusions Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far., Acta Anaesthesiologica Scandinavica, 66 (1), ISSN:0001-5172, ISSN:1399-6576

Published
2022
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35. Performance variability in perioperative sentinel events

Author

Iris M. Reijmerink, Kelly Bos, Ian P. Leistikow, Jop Groeneweg, Fokie Cnossen, Dave A. Dongelmans, Maarten J. van der Laan, Health Care Governance (HCG), Graduate School, Surgery, Intensive Care Medicine, AII - Infectious diseases, APH - Quality of Care, and ACS - Atherosclerosis & ischemic syndromes

Subjects
Surgery
Abstract

This study aimed to evaluate how performance variability contributes to perioperative sentinel events occurring within the Dutch healthcare system. Although performance variability was identified as a contributing factor in almost all analysis reports, it remains unrecognized by the sentinel event analysis team. Strengthening the integration of performance variability in sentinel event analyses could improve the analyses performed, and lead to more effective improvement measures specifically aimed at optimizing human performance within the healthcare system.

Published
2022
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36. Real-world Evidence of the Effects of Novel Treatments for COVID-19 on Mortality: A Nationwide Comparative Cohort Study of Hospitalized Patients in the First, Second, Third, and Fourth Waves in the Netherlands

Author

Marleen A, Slim, Brent, Appelman, Hessel, Peters-Sengers, Dave A, Dongelmans, Nicolette F, de Keizer, Rogier P, Schade, Mark G J, de Boer, Marcella C A, Müller, Alexander P J, Vlaar, W Joost, Wiersinga, Lonneke A, van Vught, N, Bokhizzou, Center of Experimental and Molecular Medicine, Graduate School, Epidemiology and Data Science, AII - Infectious diseases, AII - Inflammatory diseases, Intensive Care Medicine, APH - Quality of Care, Medical Informatics, APH - Methodology, ACS - Pulmonary hypertension & thrombosis, ACS - Microcirculation, Infectious diseases, AII - Cancer immunology, APH - Global Health, ACS - Diabetes & metabolism, APH - Personalized Medicine, Medical Microbiology and Infection Prevention, and Internal medicine

Subjects
Infectious Diseases, immunosuppressive treatments, Oncology, SARS-CoV-2, COVID-19, epidemiology, antiviral
Abstract

Background Large clinical trials on drugs for hospitalized coronavirus disease 2019 (COVID-19) patients have shown significant effects on mortality. There may be a discrepancy with the observed real-world effect. We describe the clinical characteristics and outcomes of hospitalized COVID-19 patients in the Netherlands during 4 pandemic waves and analyze the association of the newly introduced treatments with mortality, intensive care unit (ICU) admission, and discharge alive. Methods We conducted a nationwide retrospective analysis of hospitalized COVID-19 patients between February 27, 2020, and December 31, 2021. Patients were categorized into waves and into treatment groups (hydroxychloroquine, remdesivir, neutralizing severe acute respiratory syndrome coronavirus 2 monoclonal antibodies, corticosteroids, and interleukin [IL]-6 antagonists). Four types of Cox regression analyses were used: unadjusted, adjusted, propensity matched, and propensity weighted. Results Among 5643 patients from 11 hospitals, we observed a changing epidemiology during 4 pandemic waves, with a decrease in median age (67–64 years; P < .001), in in-hospital mortality on the ward (21%–15%; P < .001), and a trend in the ICU (24%–16%; P = .148). In ward patients, hydroxychloroquine was associated with increased mortality (1.54; 95% CI, 1.22–1.96), and remdesivir was associated with a higher rate of discharge alive within 29 days (1.16; 95% CI, 1.03–1.31). Corticosteroids were associated with a decrease in mortality (0.82; 95% CI, 0.69–0.96); the results of IL-6 antagonists were inconclusive. In patients directly admitted to the ICU, hydroxychloroquine, corticosteroids, and IL-6 antagonists were not associated with decreased mortality. Conclusions Both remdesivir and corticosteroids were associated with better outcomes in ward patients with COVID-19. Continuous evaluation of real-world treatment effects is needed.

Published
2022
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37. Inaccurate recording of routinely collected data items influences identification of COVID-19 patients

Author

Eva S, Klappe, Ronald, Cornet, Dave A, Dongelmans, Nicolette F, de Keizer, Medical Informatics, Graduate School, APH - Methodology, APH - Global Health, APH - Digital Health, APH - Quality of Care, and Intensive Care Medicine

Subjects
SARS-CoV-2, Real-time data extraction, Humans, COVID-19, Electronic Health Records, Health Informatics, Data accuracy, Problem list, Pandemics, Routinely collected data, Retrospective Studies, Routinely Collected Health Data
Abstract

Background: During the Coronavirus disease 2019 (COVID-19) pandemic it became apparent that it is difficult to extract standardized Electronic Health Record (EHR) data for secondary purposes like public health decision-making. Accurate recording of, for example, standardized diagnosis codes and test results is required to identify all COVID-19 patients. This study aimed to investigate if specific combinations of routinely collected data items for COVID-19 can be used to identify an accurate set of intensive care unit (ICU)-admitted COVID-19 patients. Methods: The following routinely collected EHR data items to identify COVID-19 patients were evaluated: positive reverse transcription polymerase chain reaction (RT-PCR) test results; problem list codes for COVID-19 registered by healthcare professionals and COVID-19 infection labels. COVID-19 codes registered by clinical coders retrospectively after discharge were also evaluated. A gold standard dataset was created by evaluating two datasets of suspected and confirmed COVID-19-patients admitted to the ICU at a Dutch university hospital between February 2020 and December 2020, of which one set was manually maintained by intensivists and one set was extracted from the EHR by a research data management department. Patients were labeled ‘COVID-19′ if their EHR record showed diagnosing COVID-19 during or right before an ICU-admission. Patients were labeled ‘non-COVID-19′ if the record indicated no COVID-19, exclusion or only suspicion during or right before an ICU-admission or if COVID-19 was diagnosed and cured during non-ICU episodes of the hospitalization in which an ICU-admission took place. Performance was determined for 37 queries including real-time and retrospective data items. We used the F1 score, which is the harmonic mean between precision and recall. The gold standard dataset was split into one subset including admissions between February and April and one subset including admissions between May and December to determine accuracy differences. Results: The total dataset consisted of 402 patients: 196 ‘COVID-19′ and 206 ‘non-COVID-19′ patients. F1 scores of search queries including EHR data items that can be extracted real-time ranged between 0.68 and 0.97 and for search queries including the data item that was retrospectively registered by clinical coders F1 scores ranged between 0.73 and 0.99. F1 scores showed no clear pattern in variability between the two time periods. Conclusions: Our study showed that one cannot rely on individual routinely collected data items such as coded COVID-19 on problem lists to identify all COVID-19 patients. If information is not required real-time, medical coding from clinical coders is most reliable. Researchers should be transparent about their methods used to extract data. To maximize the ability to completely identify all COVID-19 cases alerts for inconsistent data and policies for standardized data capture could enable reliable data reuse.

Published
2022

38. Comparison of patient characteristics and long-term mortality between transferred and non-transferred COVID-19 patients in Dutch intensive care units: A national cohort study

Author

Safira A, Wortel, Ferishta, Bakhshi-Raiez, Fabian, Termorshuizen, Dylan W, de Lange, Dave A, Dongelmans, Nicolette F, de Keizer, and R M J, Wesselink

Subjects
Adult, Cohort Studies, Intensive Care Units, Critical Illness, COVID-19, Humans, Hospital Mortality, Middle Aged, Respiration, Artificial, APACHE
Abstract

COVID-19 patients were often transferred to other intensive care units (ICUs) to prevent that ICUs would reach their maximum capacity. However, transferring ICU patients is not free of risk. We aim to compare the characteristics and outcomes of transferred versus non-transferred COVID-19 ICU patients in the Netherlands.We included adult COVID-19 patients admitted to Dutch ICUs between March 1, 2020 and July 1, 2021. We compared the patient characteristics and outcomes of non-transferred and transferred patients and used a Directed Acyclic Graph to identify potential confounders in the relationship between transfer and mortality. We used these confounders in a Cox regression model with left truncation at the day of transfer to analyze the effect of transfers on mortality during the 180 days after ICU admission.We included 10,209 patients: 7395 non-transferred and 2814 (27.6%) transferred patients. In both groups, the median age was 64 years. Transferred patients were mostly ventilated at ICU admission (83.7% vs. 56.2%) and included a larger proportion of low-risk patients (70.3% vs. 66.5% with mortality risk30%). After adjusting for age, APACHE IV mortality probability, BMI, mechanical ventilation, and vasoactive medication use, the hazard of mortality during the first 180 days was similar for transferred patients compared to non-transferred patients (HR [95% CI] = 0.99 [0.91-1.08]).Transferred COVID-19 patients are more often mechanically ventilated and are less severely ill compared to non-transferred patients. Furthermore, transferring critically ill COVID-19 patients in the Netherlands is not associated with mortality during the first 180 days after ICU admission.

Published
2022

39. The association between influenza infections in primary care and intensive care admissions for severe acute respiratory infection (SARI): A modelling approach

Author

Nicolette F. de Keizer, Jan van de Kassteele, Wim van der Hoek, Dylan W. de Lange, Angie Luna Pinzon, Dave A. Dongelmans, Gé Donker, Liselotte van Asten, AII - Infectious diseases, Intensive Care Medicine, Medical Informatics, APH - Methodology, APH - Quality of Care, and APH - Digital Health

Subjects
trends, Pulmonary and Respiratory Medicine, medicine.medical_specialty, Critical Care, Epidemiology, Population, Influenza epidemics, Primary care, Severity of Illness Index, law.invention, Severe acute respiratory infection, law, Intensive care, Influenza, Human, medicine, Humans, pneumonia, education, Respiratory Tract Infections, intensive care, education.field_of_study, Models, Statistical, Surveillance, regression model, Primary Health Care, seasonality, business.industry, Incidence, Incidence (epidemiology), association, Public Health, Environmental and Occupational Health, virus diseases, Original Articles, medicine.disease, Intensive care unit, Hospitalization, Intensive Care Units, Pneumonia, Infectious Diseases, SARI, Emergency medicine, Regression Analysis, Original Article, ILI, Seasons, time series, influenza, business
Abstract

Background: The burden of severe influenza virus infections is poorly known, for which surveillance of severe acute respiratory infection (SARI) is encouraged. Hospitalized SARI patients are however not always tested for influenza virus infection. Thus, to estimate the impact of influenza circulation we studied how influenza in primary care relates to intensive care unit (ICU) admissions using a modelling approach. Methods: We used time-series regression modelling to estimate a) the number of SARI admissions to ICU associated with medically attended influenza infections in primary care; b) how this varies by season; and c) the time lag between SARI and influenza time series. We analysed weekly adult ICU admissions (registry data) and adult influenza incidence (primary care surveillance data) from July 2007 through June 2016. Results: Depending on the year, 0% to 12% of annual SARI admissions were associated with influenza (0-554 in absolute numbers; population rate: 0/10 000-0.39/10 000 inhabitants), up to 27% during influenza epidemics. The average optimal fitting lag was +1 week (SARI trend preceding influenza by 1 week), varying between seasons (-1 to +4) with most seasons showing positive lags. Conclusion: Up to 12% of yearly SARI admissions to adult ICU are associated with influenza, but with large year-to-year variation and higher during influenza epidemics. In most years, SARI increases earlier than medically attended influenza infections in the general population. SARI surveillance could thus complement influenza-like illness surveillance by providing an indication of the season-specific burden of severe influenza infections and potential early warning of influenza activity and severity. (aut. ref.)

Published
2020
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40. Association between organizational characteristics and adequate pain management at the intensive care unit

Author

Willemke Stilma, Evert de Jonge, Dave A. Dongelmans, Nicolette F. de Keizer, Marie-José Roos-Blom, Jan Jaap Spijkstra, Graduate School, Medical Informatics, APH - Methodology, APH - Quality of Care, Intensive Care Medicine, APH - Digital Health, Faculteit Gezondheid, Urban Vitality, and Intensive care medicine

Subjects
Male, medicine.medical_specialty, Critical Care, Intensivist presence, Nurses, Intensivist, Pain, Nurse to patient ratio, Critical Care and Intensive Care Medicine, Logistic regression, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, Pain assessment, Physicians, Organizational characteristics, medicine, Humans, Pain Management, Health Workforce, Hospital Mortality, Aged, Bed Occupancy, Netherlands, Intensive care units, business.industry, Bed occupancy rate, Glasgow Coma Scale, 030208 emergency & critical care medicine, Middle Aged, Pain management, Respiration, Artificial, Intensive care unit, Confidence interval, Hospitalization, Logistic Models, 030228 respiratory system, Emergency medicine, Regression Analysis, Female, business
Abstract

PurposeHalf of the patients experience pain during their ICU stay which is known to influence their outcomes. Nurses and physicians encounter organizational barriers towards pain assessment and treatment. We aimed to evaluate the association between adequate pain management and nurse to patient ratio, bed occupancy rate, and fulltime presence of an intensivist.Materials and methodsWe performed unadjusted and case-mix adjusted mixed-effect logistic regression modeling on data from thirteen Dutch ICUs to investigate the association between ICU organizational characteristics and adequate pain management, i.e. patient-shift observations in which patients' pain was measured and acceptable, or unacceptable and normalized within 1 h.All ICU patients admitted between December 2017 and June 2018 were included, excluding patients who were delirious, comatose or had a Glasgow coma score < 8 at the first day of ICU admission.ResultsCase-mix adjusted nurse to patient ratios of 0.70 to 0.80 and over 0.80 were significantly associated with adequate pain management (OR [95% confidence interval] of respectively 1.14 [1.07–1.21] and 1.16 [1.08–1.24]). Bed occupancy rate and intensivist presence showed no association.ConclusionHigher nurse to patient ratios increase the percentage of patients with adequate pain management especially in medical and mechanically ventilated patients.

Published
2020
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41. Adverse drug event detection using natural language processing: A scoping review of supervised learning methods

Author

Rachel M. Murphy, Joanna E. Klopotowska, Nicolette F. de Keizer, Kitty J. Jager, Jan Hendrik Leopold, Dave A. Dongelmans, Ameen Abu-Hanna, Martijn C. Schut, Graduate School, Medical Informatics, APH - Methodology, APH - Quality of Care, APH - Digital Health, APH - Aging & Later Life, Intensive Care Medicine, AII - Infectious diseases, and Central Diagnostic Laboratory

Subjects
Pharmacovigilance, Multidisciplinary, Drug-Related Side Effects and Adverse Reactions, Humans, Electronic Health Records, Supervised Machine Learning, Natural Language Processing
Abstract

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results for the purpose of ADE detection in the context of pharmacovigilance. However, a detailed qualitative assessment and critical appraisal of NLP methods for ADE detection in the context of ADE monitoring in hospitals is lacking. Therefore, we have conducted a scoping review to close this knowledge gap, and to provide directions for future research and practice. We included articles where NLP was applied to detect ADEs in clinical narratives within electronic health records of inpatients. Quantitative and qualitative data items relating to NLP methods were extracted and critically appraised. Out of 1,065 articles screened for eligibility, 29 articles met the inclusion criteria. Most frequent tasks included named entity recognition (n = 17; 58.6%) and relation extraction/classification (n = 15; 51.7%). Clinical involvement was reported in nine studies (31%). Multiple NLP modelling approaches seem suitable, with Long Short Term Memory and Conditional Random Field methods most commonly used. Although reported overall performance of the systems was high, it provides an inflated impression given a steep drop in performance when predicting the ADE entity or ADE relation class. When annotating corpora, treating an ADE as a relation between a drug and non-drug entity seems the best practice. Future research should focus on semi-automated methods to reduce the manual annotation effort, and examine implementation of the NLP methods in practice.

Published
2022

42. Comparing continuous versus categorical measures to assess and benchmark intensive care unit performance

Author

Leonardo S.L. Bastos, Safira A. Wortel, Nicolette F. de Keizer, Ferishta Bakhshi-Raiez, Jorge I.F. Salluh, Dave A. Dongelmans, Fernando G. Zampieri, Gastón Burghi, Ameen Abu-Hanna, Silvio Hamacher, Fernando A. Bozza, Marcio Soares, Graduate School, Medical Informatics, APH - Methodology, APH - Quality of Care, APH - Digital Health, Intensive Care Medicine, and APH - Aging & Later Life

Subjects
Adult, Hospitalization, Benchmarking, Intensive Care Units, ICU benchmarking, Intensive care, Humans, Quality indicators, Hospital Mortality, Critical Care and Intensive Care Medicine, Outcome metrics, ICU efficiency, APACHE
Abstract

Purpose: To compare categorical and continuous combinations of the standardized mortality ratio (SMR) and the standardized resource use (SRU) to evaluate ICU performance. Materials and methods: We analysed data from adult patients admitted to 128 ICUs in Brazil and Uruguay (BR/UY) and 83 ICUs in The Netherlands between 2016 and 2018. SMR and SRU were calculated using SAPS-3 (BR/UY) or APACHE-IV (The Netherlands). Performance was defined as a combination of metrics. The categorical combination was the efficiency matrix, whereas the continuous combination was the average SMR and SRU (average standardized ratio, ASER). Association among metrics in each dataset was evaluated using Spearman's rho and R2. Results: We included 277,459 BR/UY and 164,399 Dutch admissions. Median [interquartile range] ASER = 0.99[0.83–1.21] in BR/UY and 0.99[0.92–1.09] in Dutch datasets. The SMR and SRU were more correlated in BR/UY ICUs than in Dutch ICUs (Spearman's Rho: 0.54vs.0.24). The highest and lowest ASER values were concentrated in the least and most efficient groups. An expert focus group listed potential advantages and limitations of both combinations. Conclusions: The categorical combination of metrics is easy to interpret but limits statistical inference for benchmarking. The continuous combination offers appropriate statistical properties for evaluating performance when metrics are positively correlated.

Published
2022

43. Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis

Author

Sander Siepel, Tariq A. Dam, Lucas M. Fleuren, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J.A Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G.C.A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G.M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P.C. de Jager, Stefaan H.A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C.D. Rettig, Sesmu Arbous, Sebastiaan J.J. Vonk, Tomas Machado, Willem E. Herter, Armand R.J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W.G. Elbers, and Frank C. Bennis

Abstract

Background: Identification of distinct clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment facilitating more personalized treatment. However, previous attempts did not take into account temporal dynamics of the disease. By including the dimension of time, we aim to gain further insights into the heterogeneity of COVID-19.Methods: We used highly granular data from 3202 adult critically ill COVID patients in the multicenter Dutch Data Warehouse that were admitted to one of 25 Dutch ICUs between February 2020 and March 2021. Parameters including demographics, clinical observations, medications, laboratory values, vital signs, and data from life support devices were selected based on relevance and availability. Twenty-one consecutive datasets were created that each covered 24 hours of ICU data for each day of ICU treatment up until day 21. After aggregation and multiple imputation of the temporal data, clinical phenotypes in each dataset were identified by performing multiple cluster analyses. Clinical phenotypes were identified by aggregating values from all patients per cluster. Both evolution of the clinical phenotypes over time and patient allocation to these clusters over time were tracked.Results: The final patient cohort consisted of 2438 critically ill COVID-19 patients with a registered ICU mortality outcome. Forty-one parameters were chosen for the cluster analysis. On admission, both a mild and a more severe clinical phenotype were found. After day 4, the severe phenotype split into an intermediate and a severe phenotype for 11 consecutive days. Heterogeneity between phenotypes appears to be strongly driven by inflammation and dead space ventilation. During the 21-day period only 8.2% and 4.6% of patients in the initial mild and severe clusters remained assigned to the same phenotype respectively. The clinical phenotype half-life was between 5 and 6 days for the mild and severe phenotypes, and about 3 days for the medium severe phenotype.Conclusions: Patients typically do not remain in the same cluster throughout intensive care treatment. This may have important implications for prognostic or predictive enrichment. Prominent dissimilarities between clinical phenotypes are predominantly driven by inflammation and dead space ventilation.

Published
2022
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44. Body Mass Index and Mortality in Coronavirus Disease 2019 and Other Diseases: A Cohort Study in 35,506 ICU Patients

Author

Dave A. Dongelmans, Matthijs Kox, Nicolette F. de Keizer, Emma J. Kooistra, Sylvia Brinkman, Peter H. J. van der Voort, Peter Pickkers, Medical Informatics, APH - Methodology, APH - Quality of Care, APH - Digital Health, Intensive Care Medicine, and Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE)

Subjects
Male, medicine.medical_specialty, Critical Illness, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], body mass index, OBESITY PARADOX, Critical Care and Intensive Care Medicine, medicine.disease_cause, All institutes and research themes of the Radboud University Medical Center, Intensive care, Internal medicine, Pneumonia, Bacterial, Medicine, Humans, Hospital Mortality, Obesity, Coronavirus, Aged, Netherlands, business.industry, Multiple Trauma, SARS-CoV-2, Bacterial pneumonia, Online Clinical Investigations, Patient Acuity, COVID-19, Length of Stay, Middle Aged, medicine.disease, mortality, COMORBIDITIES, Intensive Care Units, Respiratory failure, REGISTRY, Viral pneumonia, Cohort, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Female, business, Body mass index, Obesity paradox, severe acute respiratory syndrome coronavirus 2
Abstract

Supplemental Digital Content is available in the text., OBJECTIVES: Obesity is a risk factor for severe coronavirus disease 2019 and might play a role in its pathophysiology. It is unknown whether body mass index is related to clinical outcome following ICU admission, as observed in various other categories of critically ill patients. We investigated the relationship between body mass index and inhospital mortality in critically ill coronavirus disease 2019 patients and in cohorts of ICU patients with non-severe acute respiratory syndrome coronavirus 2 viral pneumonia, bacterial pneumonia, and multiple trauma. DESIGN: Multicenter observational cohort study. SETTING: Eighty-two Dutch ICUs participating in the Dutch National Intensive Care Evaluation quality registry. PATIENTS: Thirty-five–thousand five-hundred six critically ill patients. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patient characteristics and clinical outcomes were compared between four cohorts (coronavirus disease 2019, nonsevere acute respiratory syndrome coronavirus 2 viral pneumonia, bacterial pneumonia, and multiple trauma patients) and between body mass index categories within cohorts. Adjusted analyses of the relationship between body mass index and inhospital mortality within each cohort were performed using multivariable logistic regression. Coronavirus disease 2019 patients were more likely male, had a higher body mass index, lower Pao2/Fio2 ratio, and were more likely mechanically ventilated during the first 24 hours in the ICU compared with the other cohorts. Coronavirus disease 2019 patients had longer ICU and hospital length of stay, and higher inhospital mortality. Odds ratios for inhospital mortality for patients with body mass index greater than or equal to 35 kg/m2 compared with normal weight in the coronavirus disease 2019, nonsevere acute respiratory syndrome coronavirus 2 viral pneumonia, bacterial pneumonia, and trauma cohorts were 1.15 (0.79–1.67), 0.64 (0.43–0.95), 0.73 (0.61–0.87), and 0.81 (0.57–1.15), respectively. CONCLUSIONS: The obesity paradox, which is the inverse association between body mass index and mortality in critically ill patients, is not present in ICU patients with coronavirus disease 2019–related respiratory failure, in contrast to nonsevere acute respiratory syndrome coronavirus 2 viral and bacterial respiratory infections.

Published
2022
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45. Ventilation management and clinical outcomes in invasively ventilated patients with COVID-19 (PRoVENT-COVID): a national, multicentre, observational cohort study

Author

Michela Botta, Anissa M Tsonas, Janesh Pillay, Leonoor S Boers, Anna Geke Algera, Lieuwe D J Bos, Dave A Dongelmans, Marcus W Hollmann, Janneke Horn, Alexander P J Vlaar, Marcus J Schultz, Ary Serpa Neto, Frederique Paulus, Jesse P. van Akkeren, Cheetel K. Algoe, Rombout B. van Amstel, Onno L. Baur, Pablo van de Berg, Alida E. van den Berg, Dennis C.J.J. Bergmans, Dido I. van den Bersselaar, Freke A. Bertens, Alexander J.G.H. Bindels, Milou M. de Boer, Sylvia den Boer, Leonoor S. Boers, Margriet Bogerd, Lieuwe D.J. Bos, Jennifer S. Breel, Hendrik de Bruin, Sanne de Bruin, Caro L. Bruna, Laura A. Buiteman-Kruizinga, Olaf L. Cremer, Rogier M. Determann, Willem Dieperink, Dave A. Dongelmans, Hildegard S. Franke, Michal S. Galek-Aldridge, Mart J. de Graaff, Laura A. Hagens, Jasper J. Haringman, Sebastiaan T. van der Heide, Pim L.J. van der Heiden, Nanon F.L. Heijnen, Stephan J.P. Hiel, Lotte L. Hoeijmakers, Liselotte Hol, Markus W. Hollmann, Marga E. Hoogendoorn, Robrecht van der Horst, Evy L.K. Ie, Dimitri P. Ivanov, Nicole Juffermans, Eline Kho, Eline S. de Klerk, Ankie W.M.M. Koopman-van Gemert, Matty Koopmans, Songul Kucukcelebi, Michael A. Kuiper, Dylan W. de Lange, Niels van Mourik, Sunny G.L.H. Nijbroek, Marisa Onrust, Evelien A.N. Oostdijk, Charlotte J. Pennartz, Luigi Pisani, Ilse M. Purmer, Thijs C.D. Rettig, Jan-Paul Roozeman, Michiel T.U. Schuijt, Marcus J. Schultz, Mengalvio E. Sleeswijk, Marry R. Smit, Peter E. Spronk, Willemke Stilma, Aart C. Strang, Anissa M. Tsonas, Pieter R. Tuinman, Christel M.A. Valk, Felicia L. Veen-Schra, Lars I. Veldhuis, Patricia van Velzen, Ward H. van der Ven, Alexander P.J. Vlaar, Peter van Vliet, Peter H.J. van der Voort, Louis van Welie, Henrico J.F.T. Wesselink, Hermien H. van der Wier-Lubbers, Bas van Wijk, Tineke Winters, Wing Yi Wong, Arthur R.H. van Zanten, Intensive Care Medicine, Graduate School, AII - Inflammatory diseases, Pulmonology, ACS - Pulmonary hypertension & thrombosis, Anesthesiology, ANS - Neuroinfection & -inflammation, ANS - Neurovascular Disorders, ANS - Systems & Network Neuroscience, Nursing, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, AMS - Amsterdam Movement Sciences, AMS - Sports, AMS - Musculoskeletal Health, Orthopedic Surgery and Sports Medicine, General Paediatrics, APH - Aging & Later Life, APH - Personalized Medicine, APH - Quality of Care, APH - Global Health, ACS - Microcirculation, ACS - Heart failure & arrhythmias, ACS - Diabetes & metabolism, Critical care, Anesthesiology, Peri-operative and Emergency medicine (CAPE), Critical Care, RS: NUTRIM - R2 - Liver and digestive health, MUMC+: MA Arts Assistenten IC (9), Intensive Care, MUMC+: MA Medische Staf IC (9), Urban Vitality, Lectoraat Critical Care, Faculteit Gezondheid, Public and occupational health, Pulmonary medicine, and Intensive care medicine

Subjects
Pulmonary and Respiratory Medicine, medicine.medical_specialty, artificial, RESPIRATORY-DISTRESS-SYNDROME, netherlands, respiration, artificial, nederland, 03 medical and health sciences, 0302 clinical medicine, cohort studies, Intensive care, Heart rate, middle aged, covid-19/therapy, Medicine, EPIDEMIOLOGY, 030212 general & internal medicine, kunstmatige beademing, Tidal volume, business.industry, Retrospective cohort study, Articles, INTENSIVE-CARE UNITS, Prone position, retrospective studies, 030228 respiratory system, covid-19, Emergency medicine, Breathing, PATTERNS, treatment outcome, Observational study, ARDS, business, respiration, Cohort study
Abstract

Background: Little is known about the practice of ventilation management in patients with COVID-19. We aimed to describe the practice of ventilation management and to establish outcomes in invasively ventilated patients with COVID-19 in a single country during the first month of the outbreak. Methods: PRoVENT-COVID is a national, multicentre, retrospective observational study done at 18 intensive care units (ICUs) in the Netherlands. Consecutive patients aged at least 18 years were eligible for participation if they had received invasive ventilation for COVID-19 at a participating ICU during the first month of the national outbreak in the Netherlands. The primary outcome was a combination of ventilator variables and parameters over the first 4 calendar days of ventilation: tidal volume, positive end-expiratory pressure (PEEP), respiratory system compliance, and driving pressure. Secondary outcomes included the use of adjunctive treatments for refractory hypoxaemia and ICU complications. Patient-centred outcomes were ventilator-free days at day 28, duration of ventilation, duration of ICU and hospital stay, and mortality. PRoVENT-COVID is registered at ClinicalTrials.gov (NCT04346342). Findings: Between March 1 and April 1, 2020, 553 patients were included in the study. Median tidal volume was 6·3 mL/kg predicted bodyweight (IQR 5·7–7·1), PEEP was 14·0 cm H2O (IQR 11·0–15·0), and driving pressure was 14·0 cm H2O (11·2–16·0). Median respiratory system compliance was 31·9 mL/cm H2O (26·0–39·9). Of the adjunctive treatments for refractory hypoxaemia, prone positioning was most often used in the first 4 days of ventilation (283 [53%] of 530 patients). The median number of ventilator-free days at day 28 was 0 (IQR 0–15); 186 (35%) of 530 patients had died by day 28. Predictors of 28-day mortality were gender, age, tidal volume, respiratory system compliance, arterial pH, and heart rate on the first day of invasive ventilation. Interpretation: In patients with COVID-19 who were invasively ventilated during the first month of the outbreak in the Netherlands, lung-protective ventilation with low tidal volume and low driving pressure was broadly applied and prone positioning was often used. The applied PEEP varied widely, despite an invariably low respiratory system compliance. The findings of this national study provide a basis for new hypotheses and sample size calculations for future trials of invasive ventilation for COVID-19. These data could also help in the interpretation of findings from other studies of ventilation practice and outcomes in invasively ventilated patients with COVID-19. Funding: Amsterdam University Medical Centers, location Academic Medical Center.

Published
2021
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46. Indoleamine 2,3-dioxygenase (IDO)-1 and IDO-2 activity and severe course of COVID-19

Author

René Lutter, Dorien Wouters, A H Koos Zwinderman, Markus Hollmann, Esther J. Nossent, Jorinde Raasveld, Bram Goorhuis, Syun-Ru Yeh, Kim C. E. Sigaloff, Michiel A. van Agtmael, Lieuwe D. J. Bos, Martin P. Grobusch, Michèle van Vugt, Anissa Tsonas, Leo Heunks, Marije K. Bomers, Michela Botta, Frederique Paulus, Joppe W. Hovius, Menno D. de Jong, Suzanne Geerlings, Zachary Geeraerts, Carolien Volleman, Jaap Schuurmans, Jeannine Nellen, Dan A.I. Piña-Fuentes, Edgar Peters, Frédéric M. Vaz, Vanessa Harris, Heder de Vries, Patrick Thoral, Jörg Hamann, Anne Geke Algera, Romein W.G. Dujardin, Laura Hagens, Femke A.P. Schrauwen, Lucas Fleuren, Bennedikt Preckel, Paul Elbers, Rutger Koning, Jan M. Prins, Tom Reijnders, Marry Smit, Alex Cloherty, Justin de Brabander, Harm Jan Bogaard, Eva Roos, Alexander P.J. Vlaar, Armand Girbes, Matthijs C. Brouwer, Cornelis S. Stijnis, Tom van der Poll, Brent Appelman, Theo Geijtenbeek, Diane Bax, Florianne Hafkamp, Anissa M. Tsonas, Michiel Schinkel, Charlotte E. Teunissen, Robert Hemke, Annemiek Dijkhuis, Frank van Baarle, Alex Schuurmans, Paul van der Valk, Buis T P David, Lonneke A. Vught, Marc van der Valk, Peter Bonta, Janneke Horn, Bernadette Schurink, Maurits C.F.J. de Rotte, Sanne de Bruin, Esther Bulle, Endry H.T. Lim, Denise Veelo, Lihui Guo, Marcus J. Schultz, Marleen A. Slim, Sabine M. Hermans, Martijn Beudel, Marianna Bugiani, JanWillem Duitman, Lonneke A. van Vught, W. Joost Wiersinga, Godelieve J. de Bree, Niels van Mourik, Mirjam Dijkstra, Dave A. Dongelmans, Osoul Chouchane, Diederik van de Beek, Willemke Stilma, Pathology, Pulmonary medicine, Amsterdam Neuroscience - Neuroinfection & -inflammation, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Amsterdam Neuroscience - Complex Trait Genetics, Internal medicine, AII - Infectious diseases, Intensive care medicine, Neurology, ACS - Pulmonary hypertension & thrombosis, Laboratory Medicine, Amsterdam Cardiovascular Sciences, ACS - Diabetes & metabolism, Radiology and nuclear medicine, Anesthesiology, Medical Microbiology and Infection Prevention, AMS - Rehabilitation & Development, VU University medical center, Amsterdam Neuroscience - Neurodegeneration, Amsterdam Reproduction & Development (AR&D), Graduate School, Pulmonology, Intensive Care Medicine, ACS - Microcirculation, Vascular Medicine, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Laboratory Genetic Metabolic Diseases, Experimental Immunology, APH - Personalized Medicine, Center of Experimental and Molecular Medicine, ANS - Neurodegeneration, Laboratory for General Clinical Chemistry, Genetic Metabolic Diseases, APH - Quality of Care, Infectious diseases, APH - Global Health, Global Health, APH - Health Behaviors & Chronic Diseases, AII - Amsterdam institute for Infection and Immunity, Radiology and Nuclear Medicine, AMS - Sports, AMS - Musculoskeletal Health, APH - Methodology, ACS - Heart failure & arrhythmias, ANS - Neuroinfection & -inflammation, Nursing, APH - Digital Health, and APH - Aging & Later Life

Subjects
Adult, Programmed cell death, Cell, 3-Hydroxyanthranilic Acid, Apoptosis, Severity of Illness Index, Pathology and Forensic Medicine, chemistry.chemical_compound, Medicine, Humans, Indoleamine-Pyrrole 2,3,-Dioxygenase, Prospective Studies, Receptor, Indoleamine 2,3-dioxygenase, Lung, Kynurenine, Aged, business.industry, Myocardium, Tryptophan, Brain, COVID-19, Middle Aged, Quinolinic Acid, medicine.anatomical_structure, chemistry, Immunology, Autopsy, business, Quinolinic acid, Hormone
Abstract

COVID-19 is a pandemic with high morbidity and mortality. In an autopsy cohort of COVID-19 patients, we found extensive accumulation of the tryptophan degradation products 3-hydroxy-anthranilic acid and quinolinic acid in the lungs, heart, and brain. This was not related to the expression of the tryptophan-catabolizing indoleamine 2,3-dioxygenase (IDO)-1, but rather to that of its isoform IDO-2, which otherwise is expressed rarely. Bioavailability of tryptophan is an absolute requirement for proper cell functioning and synthesis of hormones, whereas its degradation products can cause cell death. Markers of apoptosis and severe cellular stress were associated with IDO-2 expression in large areas of lung and heart tissue, whereas affected areas in brain were more restricted. Analyses of tissue, cerebrospinal fluid, and sequential plasma samples indicate early initiation of the kynurenine/aryl-hydrocarbon receptor/IDO-2 axis as a positive feedback loop, potentially leading to severe COVID-19 pathology. © 2021 The Authors. The Journal of Pathology published by John WileySons, Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Published
2021
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47. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Author

Roberto Noorduijn-Londono, Sander Rigter, Willem E. Herter, Tomas Machado, Gert B. Brunnekreef, Thijs C. D. Rettig, Evert-Jan Wils, Remko de Jong, S Arbous, Harald J. Faber, Cornelis P.C. de Jager, Paul de Jong, Auke C Reidinga, Sebastiaan J. J. Vonk, Dave A. Dongelmans, Wouter de Ruijter, Taco Houwert, Ralph Nowitzky, Daan P de Bruin, Robert Entjes, Diederik Gommers, Dharmanand Ramnarain, Marlijn J A Kamps, Mark Hoogendoorn, Evelien A. N. Oostdijk, Martijn G. Scholtemeijer, Age D Boelens, Armand R. J. Girbes, Fleur G C A Nooteboom, Barbara Festen-Spanjer, Peter Koetsier, Giovanni Cinà, Hidde Hovenkamp, Sefanja Achterberg, Ellen G M Smit, Robbert C. A. Lalisang, D Jannet Mehagnoul-Schipper, Rob J. Bosman, Patrick Thoral, Judith Lens, Tariq A Dam, Olaf L. Cremer, Lucas M. Fleuren, Martijn Beudel, Paul W. G. Elbers, Tom Dormans, Aletta A. de Beer, Marco Peters, Alexander D. Cornet, Tim Frenzel, Louise C Urlings-Strop, Michele Tonutti, Mattia Fornasa, Walter van den Tempel, Davide Quintarelli, A Karakus, Stefaan H A Hendriks, Artificial intelligence, Network Institute, Computational Intelligence, Intensive Care, Intensive care medicine, ACS - Diabetes & metabolism, AII - Infectious diseases, ACS - Microcirculation, APH - Quality of Care, Intensive Care Medicine, AII - Inflammatory diseases, Neurology, and ANS - Neurodegeneration

Subjects
Critical Care, Critical Illness, Big data, Data validation, Critical Care and Intensive Care Medicine, computer.software_genre, Database, SDG 3 - Good Health and Well-being, Data Warehousing, Intensive care, Electronic Health Records, Humans, Medicine, Netherlands, RC86-88.9, business.industry, Research, Other Research Radboud Institute for Health Sciences [Radboudumc 0], COVID-19, Medical emergencies. Critical care. Intensive care. First aid, Missing data, Data warehouse, Hospitalization, Data sharing, Intensive Care Units, Life support, Pseudonymized, business, computer
Abstract

Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Published
2021
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48. COVID-19 vaccine effectiveness against hospitalizations and ICU admissions in the Netherlands, April- August 2021

Author

Stijn P. Andeweg, Jeanet M. Kemmeren, Jan van de Kassteele, Susan van den Hof, Nicolette F. de Keizer, Dave A. Dongelmans, Hester E. de Melker, Marjolein Kooijman, surveillance team, Brechje de Gier, Susan Hahné, Mirjam J. Knol, and Senna C.J.L. van Iersel

Subjects
Vaccination, Calendar date, Pediatrics, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Age groups, Vaccination status, business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Medicine, Rate ratio, business, Icu admission
Abstract

The objective of this study was to estimate vaccine effectiveness (VE) against COVID-19 hospitalization and ICU admission, per period according to dominating SARS-CoV-2 variant (Alpha and Delta), per vaccine and per time since vaccination. To this end, data from the national COVID-19 vaccination register was added to the national register of COVID-19 hospitalizations. For the study period 4 April – 29 August 2021, 15,571 hospitalized people with COVID-19 were included in the analysis, of whom 887 (5.7%) were fully vaccinated. Incidence rates of hospitalizations and ICU admissions per age group and vaccination status were calculated, and VE was estimated as 1-incidence rate ratio, adjusted for calendar date and age group in a negative binomial regression model. VE against hospitalization for full vaccination was 94% (95%CI 93-95%) in the Alpha period and 95% (95%CI 94-95%) in the Delta period. The VE for full vaccination against ICU admission was 93% (95%CI 87-96%) in the Alpha period and 97% (95%CI 97-98%) in the Delta period. VE was high in all age groups and did not show waning with time since vaccination up to 20 weeks after full vaccination.

Published
2021
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49. Criteria for recommendations after perioperative sentinel events

Author

Ian Leistikow, Dink A. Legemate, Maarten J. van der Laan, Dave A Dongelmans, Kelly Bos, Jop Groeneweg, Graduate School, Intensive Care Medicine, APH - Quality of Care, and Health Care Governance (HCG)

Subjects
medicine.medical_specialty, Medicine (General), Fatal outcome, Leadership and Management, media_common.quotation_subject, Patient safety, R5-920, SDG 3 - Good Health and Well-being, patient safety, Medicine, Quality (business), INCIDENTS, Original Research, media_common, business.industry, Health Policy, never events, Public Health, Environmental and Occupational Health, Guideline, Perioperative, Never events, root cause analysis, SAFETY, Family medicine, HEALTH-CARE, incident reporting, ADVERSE EVENTS, healthcare quality improvement, business, Root cause analysis, Healthcare providers
Abstract

BackgroundThe recurrence of sentinel events (SEs) is a persistent problem worldwide, despite repeated analyses and recommendations formulated to prevent recurrence. Research suggests this is partly attributable to the quality of the recommendations, and determining if a recommendation will be effective is not yet covered by an adequate guideline. Our objectives were to (1) develop and validate criteria for high-quality recommendations, and (2) evaluate recommendations using the criteria developed.Methods(1) Criteria were developed by experts using the bowtie method. Medical doctors then determined if the recommendations of Dutch in-hospital SE analysis reports met the criteria, after which interobserver variability was tested. (2) Researchers determined which recommendations of Dutch perioperative SE analysis reports produced from 2017 to 2018 met the criteria.ResultsThe criteria were: (1) a recommendation needs to be well defined and clear, (2) it needs to specifically describe the intended changes, and (3) it needs to describe how it will reduce the risk or limit the consequences of a similar SE. Validation of criteria showed substantial interobserver agreement. The SE analysis reports (n=115) contained 442 recommendations, of which 64% failed to meet all criteria, and 28% of reports did not contain a single recommendation that met the criteria.ConclusionWe developed and validated criteria for high-quality recommendations. The majority of recommendations did not meet our criteria. It was disconcerting to find that over a quarter of the investigations did not produce a single recommendation that met the criteria, not even in SEs with a fatal outcome. Healthcare providers have an obligation to prevent SEs, and certainly their recurrence. We anticipate that using these criteria to determine the potential of recommendations will aid in this endeavour.

Published
2021

50. The observed respiratory rate of ward patients in the postoperative period

Author

Farida S van Etten-Jamaludin, Ilse J A Wissink, Estaban N Jessurun, Dave A. Dongelmans, Linda M. Posthuma, Markus W. Hollmann, Maarten J. Visscher, Benedikt Preckel, Intensive Care Medicine, Graduate School, ACS - Heart failure & arrhythmias, ACS - Diabetes & metabolism, AII - Inflammatory diseases, APH - Quality of Care, Anesthesiology, ACS - Microcirculation, and APH - Global Health

Subjects
Respiratory rate, business.industry, Period (gene), Early warning score, Postoperative patients, Intensive Care Units, Anesthesiology and Pain Medicine, Respiratory Rate, Anesthesia, Systematic review, Medicine, Humans, Hospital Mortality, Postoperative Period, business, Retrospective Studies
Published
2021

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