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1. People in intensive care with COVID-19: demographic and clinical features during the first, second, and third pandemic waves in Australia.

Author

Begum H, Neto AS, Alliegro P, Broadley T, Trapani T, Campbell LT, Cheng AC, Cheung W, Cooper DJ, Erickson SJ, French CJ, Litton E, McAllister R, Nichol A, Palermo A, Plummer MP, Rotherham H, Ramanan M, Reddi B, Reynolds C, Webb SA, Udy AA, and Burrell A

Subjects
Australia epidemiology, Critical Care, Hospital Mortality, Humans, Intensive Care Units, Male, Middle Aged, COVID-19 epidemiology, COVID-19 therapy, Pandemics
Abstract

Objective: To compare the demographic and clinical features, management, and outcomes for patients admitted with COVID-19 to intensive care units (ICUs) during the first, second, and third waves of the pandemic in Australia., Design, Setting, and Participants: People aged 16 years or more admitted with polymerase chain reaction-confirmed COVID-19 to the 78 Australian ICUs participating in the Short Period Incidence Study of Severe Acute Respiratory Infection (SPRINT-SARI) Australia project during the first (27 February - 30 June 2020), second (1 July 2020 - 25 June 2021), and third COVID-19 waves (26 June - 1 November 2021)., Main Outcome Measures: Primary outcome: in-hospital mortality., Secondary Outcomes: ICU mortality; ICU and hospital lengths of stay; supportive and disease-specific therapies., Results: 2493 people (1535 men, 62%) were admitted to 59 ICUs: 214 during the first (9%), 296 during the second (12%), and 1983 during the third wave (80%). The median age was 64 (IQR, 54-72) years during the first wave, 58 (IQR, 49-68) years during the second, and 54 (IQR, 41-65) years during the third. The proportion without co-existing illnesses was largest during the third wave (41%; first wave, 32%; second wave, 29%). The proportion of ICU beds occupied by patients with COVID-19 was 2.8% (95% CI, 2.7-2.9%) during the first, 4.6% (95% CI, 4.3-5.1%) during the second, and 19.1% (95% CI, 17.9-20.2%) during the third wave. Non-invasive (42% v 15%) and prone ventilation strategies (63% v 15%) were used more frequently during the third wave than during the first two waves. Thirty patients (14%) died in hospital during the first wave, 35 (12%) during the second, and 281 (17%) during the third. After adjusting for age, illness severity, and other covariates, the risk of in-hospital mortality was similar for the first and second waves, but 9.60 (95% CI, 3.52-16.7) percentage points higher during the third than the first wave., Conclusion: The demographic characteristics of patients in intensive care with COVID-19 and the treatments they received during the third pandemic wave differed from those of the first two waves. Adjusted in-hospital mortality was highest during the third wave., (© 2022 The Authors. Medical Journal of Australia published by John Wiley & Sons Australia, Ltd on behalf of AMPCo Pty Ltd.)

Published
2022
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2. Outcomes for patients with COVID-19 admitted to Australian intensive care units during the first four months of the pandemic.

Author

Burrell AJ, Pellegrini B, Salimi F, Begum H, Broadley T, Campbell LT, Cheng AC, Cheung W, Cooper DJ, Earnest A, Erickson SJ, French CJ, Kaldor JM, Litton E, Murthy S, McAllister RE, Nichol AD, Palermo A, Plummer MP, Ramanan M, Reddi BA, Reynolds C, Trapani T, Webb SA, and Udy AA

Subjects
APACHE, Aged, Australia epidemiology, COVID-19 therapy, Comorbidity, Female, Humans, Male, Middle Aged, Prospective Studies, Respiration, Artificial, Survival Analysis, COVID-19 mortality, Hospital Mortality, Intensive Care Units statistics & numerical data, Length of Stay statistics & numerical data, Pandemics
Abstract

Objectives: To describe the characteristics and outcomes of patients with COVID-19 admitted to intensive care units (ICUs) during the initial months of the pandemic in Australia., Design, Setting: Prospective, observational cohort study in 77 ICUs across Australia., Participants: Patients admitted to participating ICUs with laboratory-confirmed COVID-19 during 27 February - 30 June 2020., Main Outcome Measures: ICU mortality and resource use (ICU length of stay, peak bed occupancy)., Results: The median age of the 204 patients with COVID-19 admitted to intensive care was 63.5 years (IQR, 53-72 years); 140 were men (69%). The most frequent comorbid conditions were obesity (40% of patients), diabetes (28%), hypertension treated with angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (24%), and chronic cardiac disease (20%); 73 patients (36%) reported no comorbidity. The most frequent source of infection was overseas travel (114 patients, 56%). Median peak ICU bed occupancy was 14% (IQR, 9-16%). Invasive ventilation was provided for 119 patients (58%). Median length of ICU stay was greater for invasively ventilated patients than for non-ventilated patients (16 days; IQR, 9-28 days v 3 days; IQR, 2-5 days), as was ICU mortality (26 deaths, 22%; 95% CI, 15-31% v four deaths, 5%; 95% CI, 1-12%). Higher Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores on ICU day 1 (adjusted hazard ratio [aHR], 1.15; 95% CI, 1.09-1.21) and chronic cardiac disease (aHR, 3.38; 95% CI, 1.46-7.83) were each associated with higher ICU mortality., Conclusion: Until the end of June 2020, mortality among patients with COVID-19 who required invasive ventilation in Australian ICUs was lower and their ICU stay longer than reported overseas. Our findings highlight the importance of ensuring adequate local ICU capacity, particularly as the pandemic has not yet ended., (© 2020 AMPCo Pty Ltd.)

Published
2021
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3. Quantitative fit testing with limited supplies of respirator masks in hospital personnel during the COVID-19 pandemic.

Author

Cameron S, Cheung W, Cronin N, Griffiths K, Hunt R, Innes L, Kol M, Lawrence A, Shah A, Skylas K, and Wagh A

Subjects
Adult, Betacoronavirus, COVID-19, Female, Humans, Male, Masks statistics & numerical data, Middle Aged, SARS-CoV-2, Coronavirus Infections prevention & control, Guidelines as Topic, Masks standards, Masks supply & distribution, Occupational Exposure statistics & numerical data, Pandemics prevention & control, Personnel, Hospital statistics & numerical data, Pneumonia, Viral prevention & control
Published
2020
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4. A cross-sectional survey of Australian and New Zealand public opinion on methods totriage intensive care patients in an influenza pandemic.

Author

Cheung W, Myburgh J, McGuinness S, Chalmers D, Parke R, Blyth F, Seppelt I, Parr M, Hooker C, Blackwell N, DeMonte S, Gandhi K, Kol M, Kerridge I, Nair P, Saunders NM, Saxena MK, Thanakrishnan G, and Naganathan V

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Australia, Critical Care, Cross-Sectional Studies, Female, Humans, Intensive Care Units, Male, Middle Aged, New Zealand, Surveys and Questionnaires, Young Adult, Attitude to Health, Critical Illness, Influenza, Human epidemiology, Pandemics, Public Opinion, Triage
Abstract

Background and Objective: An influenza pandemic has the potential to overwhelm intensive care resources, but the views of the general public on how resources should be allocated in such a scenario were unknown. We aimed to determine Australian and New Zealand public opinion on how intensive care unit beds should be allocated during an influenza pandemic., Design, Setting, and Participants: A postal questionnaire was sent to 4000 randomly selected registered voters; 2000 people each from the Australian Electoral Commission and New Zealand Electoral Commission rolls., Main Outcome Measure: The respondents' preferred method to triage ICU patients in an influenza pandemic. Respondents chose from six methods: use a "first in, first served" approach; allow a senior doctor to decide; use pre-determined health department criteria; use random selection; use the patient's ability to pay; use the importance of the patient to decide. Respondents also rated each of the triage methods for fairness., Results: Australian respondents preferred that patients be triaged to the ICU either by a senior doctor (43.2%) or by pre-determined health department criteria (38.7%). New Zealand respondents preferred that triage be performed by a senior doctor (45.9%). Respondents from both countries perceived triage by a senior doctor and by pre-determined health department criteria to be fair, and the other four methods of triage to be unfair., Conclusion: In an influenza pandemic, when ICU resources would be overwhelmed, survey respondents preferred that ICU triage be performed by a senior doctor, but also perceived the use of pre-determined triage criteria to be fair.

Published
2017

5. Development and evaluation of an influenza pandemic intensive care unit triage protocol.

Author

Cheung W, Myburgh J, Seppelt IM, Parr MJ, Blackwell N, Demonte S, Gandhi K, Hoyling L, Nair P, Passer M, Reynolds C, Saunders NM, Saxena MK, and Thanakrishnan G

Subjects
Clinical Protocols, Humans, Influenza, Human mortality, Intensive Care Units, New South Wales, Ontario, Influenza, Human epidemiology, Pandemics, Triage
Abstract

Objectives: To develop an influenza pandemic ICU triage (iPIT) protocol that excludes patients with the highest and lowest predicted mortality rates, and to determine the increase in ICU bed availability that would result., Design and Setting: Post-hoc analysis of a study evaluating two triage protocols, designed to determine which patients should be excluded from access to ICU resources during an influenza pandemic. ICU mortality rates were determined for the individual triage criteria in the protocols and included criteria based on the Sequential Organ Failure Assessment (SOFA) score. Criteria resulting in mortality rates outside the 25th and 75th percentiles were used as exclusion criteria in a new iPIT-1 protocol. The SOFA threshold component was modified further and reported as iPIT-2 and iPIT-3., Main Outcome Measure: Increase in ICU bed availability., Results: The 25th and 75th percentiles for ICU mortality were 8.3% and 35.2%, respectively. Applying the iPIT-1 protocol resulted in an increase in ICU bed availability at admission of 71.7% ± 0.6%. Decreasing the lower SOFA score exclusion criteria to ≤6 (iPIT-2) and ≤4 (iPIT-3) resulted in an increase in ICU bed availability at admission of 66.9% ± 0.6% and 59.4 ± 0.7%, respectively (P < 0.001)., Conclusion: The iPIT protocol excludes patients with the lowest and highest ICU mortality, and provides increases in ICU bed availability. Adjusting the lower SOFA score exclusion limit provides a method of escalation or de- escalation to cope with demand.

Published
2012

6. A multicentre evaluation of two intensive care unit triage protocols for use in an influenza pandemic.

Author

Cheung WK, Myburgh J, Seppelt IM, Parr MJ, Blackwell N, Demonte S, Gandhi K, Hoyling L, Nair P, Passer M, Reynolds C, Saunders NM, Saxena MK, and Thanakrishnan G

Subjects
Australia epidemiology, Clinical Protocols, Female, Humans, In Vitro Techniques, Influenza, Human epidemiology, Intensive Care Units supply & distribution, Middle Aged, Prospective Studies, Influenza, Human therapy, Intensive Care Units organization & administration, Pandemics, Triage methods
Abstract

Objective: To determine the increase in intensive care unit (ICU) bed availability that would result from the use of the New South Wales and Ontario Health Plan for an Influenza Pandemic (OHPIP) triage protocols., Design, Setting and Patients: Prospective evaluation study conducted in eight Australian, adult, general ICUs, between September 2009 and May 2010. All patients who were admitted to the ICU, excluding those who had elective surgery, were prospectively evaluated using the two triage protocols, simulating a pandemic situation. Both protocols were originally developed to determine which patients should be excluded from accessing ICU resources during an influenza pandemic., Main Outcome Measure: Increase in ICU bed availability., Results: At admission, the increases in ICU bed availability using Tiers 1, 2 and 3 of the NSW triage protocol were 3.5%, 14.7% and 22.7%, respectively, and 52.8% using the OHPIP triage protocol (P < 0.001). Re-evaluation of patients at 12 hours after admission using Tiers 1, 2 and 3 of the NSW triage protocol incrementally increased ICU bed availability by 19.2%, 16.1% and 14.1%, respectively (P < 0.001). The maximal cumulative increases in ICU bed availability using Tiers 1, 2 and 3 of the NSW triage protocol were 23.7%, 31.6% and 37.5%, respectively, at 72 hours (P < 0.001), and 65.0% using the OHPIP triage protocol, at 120 hours (P < 0.001)., Conclusion: Both triage protocols resulted in increases in ICU bed availability, but the OHPIP protocol provided the greatest increase overall. With the NSW triage protocol, ICU bed availability increased as the protocol was escalated.

Published
2012
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7. Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19:The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial

Author

Angus, Derek C, Derde, Lennie, Al-Beidh, Farah, Annane, Djillali, Arabi, Yaseen, Beane, Abigail, van Bentum-Puijk, Wilma, Berry, Lindsay, Bhimani, Zahra, Bonten, Marc, Bradbury, Charlotte, Brunkhorst, Frank, Buxton, Meredith, Buzgau, Adrian, Cheng, Allen C, de Jong, Menno, Detry, Michelle, Estcourt, Lise, Fitzgerald, Mark, Goossens, Herman, Green, Cameron, Haniffa, Rashan, Higgins, Alisa M, Horvat, Christopher, Hullegie, Sebastiaan J, Kruger, Peter, Lamontagne, Francois, Lawler, Patrick R, Linstrum, Kelsey, Litton, Edward, Lorenzi, Elizabeth, Marshall, John, McAuley, Daniel, McGlothin, Anna, McGuinness, Shay, McVerry, Bryan, Montgomery, Stephanie, Mouncey, Paul, Murthy, Srinivas, Nichol, Alistair, Parke, Rachael, Parker, Jane, Rowan, Kathryn, Sanil, Ashish, Santos, Marlene, Saunders, Christina, Seymour, Christopher, Turner, Anne, van de Veerdonk, Frank, Venkatesh, Balasubramanian, Zarychanski, Ryan, Berry, Scott, Lewis, Roger J, McArthur, Colin, Webb, Steven A, Gordon, Anthony C, Writing Committee for the REMAP-CAP Investigators, Angus, Derek, Cheng, Allen, De Jong, Menno, Gordon, Anthony, Lawler, Patrick, Webb, Steve, Campbell, Lewis, Forbes, Andrew, Gattas, David, Heritier, Stephane, Higgins, Lisa, Peake, Sandra, Presneill, Jeffrey, Seppelt, Ian, Trapani, Tony, Young, Paul, Bagshaw, Sean, Daneman, Nick, Ferguson, Niall, Misak, Cheryl, Hullegie, Sebastiaan, Pletz, Mathias, Rohde, Gernot, Rowan, Kathy, Alexander, Brian, Basile, Kim, Girard, Timothy, Huang, David, Vates, Jennifer, Beasley, Richard, Fowler, Robert, McGloughlin, Steve, Morpeth, Susan, Paterson, David, Venkatesh, Bala, Uyeki, Tim, Baillie, Kenneth, Duffy, Eamon, Fowler, Rob, Hills, Thomas, Orr, Katrina, Patanwala, Asad, Tong, Steve, Netea, Mihai, Bihari, Shilesh, Carrier, Marc, Fergusson, Dean, Goligher, Ewan, Haidar, Ghady, Hunt, Beverley, Kumar, Anand, Laffan, Mike, Lawless, Patrick, Lother, Sylvain, McCallum, Peter, Middeldopr, Saskia, McQuilten, Zoe, Neal, Matthew, Pasi, John, Schutgens, Roger, Stanworth, Simon, Turgeon, Alexis, Weissman, Alexandra, Adhikari, Neill, Anstey, Matthew, Brant, Emily, de Man, Angelique, Lamonagne, Francois, Masse, Marie-Helene, Udy, Andrew, Arnold, Donald, Begin, Phillipe, Charlewood, Richard, Chasse, Michael, Coyne, Mark, Cooper, Jamie, Daly, James, Gosbell, Iain, Harvala-Simmonds, Heli, Hills, Tom, MacLennan, Sheila, Menon, David, McDyer, John, Pridee, Nicole, Roberts, David, Shankar-Hari, Manu, Thomas, Helen, Tinmouth, Alan, Triulzi, Darrell, Walsh, Tim, Wood, Erica, Calfee, Carolyn, O’Kane, Cecilia, Shyamsundar, Murali, Sinha, Pratik, Thompson, Taylor, Young, Ian, Bihari, Shailesh, Hodgson, Carol, Laffey, John, McAuley, Danny, Orford, Neil, Neto, Ary, Lewis, Roger, McGlothlin, Anna, Miller, Eliza, Singh, Vanessa, Zammit, Claire, van Bentum Puijk, Wilma, Bouwman, Wietske, Mangindaan, Yara, Parker, Lorraine, Peters, Svenja, Rietveld, Ilse, Raymakers, Kik, Ganpat, Radhika, Brillinger, Nicole, Markgraf, Rene, Ainscough, Kate, Brickell, Kathy, Anjum, Aisha, Lane, Janis-Best, Richards-Belle, Alvin, Saull, Michelle, Wiley, Daisy, Bion, Julian, Connor, Jason, Gates, Simon, Manax, Victoria, van der Poll, Tom, Reynolds, John, van Beurden, Marloes, Effelaar, Evelien, Schotsman, Joost, Boyd, Craig, Harland, Cain, Shearer, Audrey, Wren, Jess, Clermont, Giles, Garrard, William, Kalchthaler, Kyle, King, Andrew, Ricketts, Daniel, Malakoutis, Salim, Marroquin, Oscar, Music, Edvin, Quinn, Kevin, Cate, Heidi, Pearson, Karen, Collins, Joanne, Hanson, Jane, Williams, Penny, Jackson, Shane, Asghar, Adeeba, Dyas, Sarah, Sutu, Mihaela, Murphy, Sheenagh, Williamson, Dawn, Mguni, Nhlanhla, Potter, Alison, Porter, David, Goodwin, Jayne, Rook, Clare, Harrison, Susie, Williams, Hannah, Campbell, Hilary, Lomme, Kaatje, Williamson, James, Sheffield, Jonathan, van’t Hoff, Willian, McCracken, Phobe, Young, Meredith, Board, Jasmin, Mart, Emma, Knott, Cameron, Smith, Julie, Boschert, Catherine, Affleck, Julia, Ramanan, Mahesh, D’Souza, Ramsy, Pateman, Kelsey, Shakih, Arif, Cheung, Winston, Kol, Mark, Wong, Helen, Shah, Asim, Wagh, Atul, Simpson, Joanne, Duke, Graeme, Chan, Peter, Cartner, Brittney, Hunter, Stephanie, Laver, Russell, Shrestha, Tapaswi, Regli, Adrian, Pellicano, Annamaria, McCullough, James, Tallott, Mandy, Kumar, Nikhil, Panwar, Rakshit, Brinkerhoff, Gail, Koppen, Cassandra, Cazzola, Federica, Brain, Matthew, Mineall, Sarah, Fischer, Roy, Biradar, Vishwanath, Soar, Natalie, White, Hayden, Estensen, Kristen, Morrison, Lynette, Smith, Joanne, Cooper, Melanie, Health, Monash, Shehabi, Yahya, Al-Bassam, Wisam, Hulley, Amanda, Whitehead, Christina, Lowrey, Julie, Gresha, Rebecca, Walsham, James, Meyer, Jason, Harward, Meg, Venz, Ellen, Williams, Patricia, Kurenda, Catherine, Smith, Kirsy, Smith, Margaret, Garcia, Rebecca, Barge, Deborah, Byrne, Deborah, Byrne, Kathleen, Driscoll, Alana, Fortune, Louise, Janin, Pierre, Yarad, Elizabeth, Hammond, Naomi, Bass, Frances, Ashelford, Angela, Waterson, Sharon, Wedd, Steve, McNamara, Robert, Buhr, Heidi, Coles, Jennifer, Schweikert, Sacha, Wibrow, Bradley, Rauniyar, Rashmi, Myers, Erina, Fysh, Ed, Dawda, Ashlish, Mevavala, Bhaumik, Litton, Ed, Ferrier, Janet, Nair, Priya, Buscher, Hergen, Reynolds, Claire, Santamaria, John, Barbazza, Leanne, Homes, Jennifer, Smith, Roger, Murray, Lauren, Brailsford, Jane, Forbes, Loretta, Maguire, Teena, Mariappa, Vasanth, Smith, Judith, Simpson, Scott, Maiden, Matthew, Bone, Allsion, Horton, Michelle, Salerno, Tania, Sterba, Martin, Geng, Wenli, Depuydt, Pieter, De Waele, Jan, De Bus, Liesbet, Fierens, Jan, Bracke, Stephanie, Reeve, Brenda, Dechert, William, Chassé, Michaël, Carrier, François Martin, Boumahni, Dounia, Benettaib, Fatna, Ghamraoui, Ali, Bellemare, David, Cloutier, Ève, Francoeur, Charles, Lamontagne, François, D’Aragon, Frédérick, Carbonneau, Elaine, Leblond, Julie, Vazquez-Grande, Gloria, Marten, Nicole, Wilson, Maggie, Albert, Martin, Serri, Karim, Cavayas, Alexandros, Duplaix, Mathilde, Williams, Virginie, Rochwerg, Bram, Karachi, Tim, Oczkowski, Simon, Centofanti, John, Millen, Tina, Duan, Erick, Tsang, Jennifer, Patterson, Lisa, English, Shane, Watpool, Irene, Porteous, Rebecca, Miezitis, Sydney, McIntyre, Lauralyn, Brochard, Laurent, Burns, Karen, Sandhu, Gyan, Khalid, Imrana, Binnie, Alexandra, Powell, Elizabeth, McMillan, Alexandra, Luk, Tracy, Aref, Noah, Andric, Zdravko, Cviljevic, Sabina, Đimoti, Renata, Zapalac, Marija, Mirković, Gordan, Baršić, Bruno, Kutleša, Marko, Kotarski, Viktor, Vujaklija Brajković, Ana, Babel, Jakša, Sever, Helena, Dragija, Lidija, Kušan, Ira, Vaara, Suvi, Pettilä, Leena, Heinonen, Jonna, Kuitunen, Anne, Karlsson, Sari, Vahtera, Annukka, Kiiski, Heikki, Ristimäki, Sanna, Azaiz, Amine, Charron, Cyril, Godement, Mathieu, Geri, Guillaume, Vieillard-Baron, Antoine, Pourcine, Franck, Monchi, Mehran, Luis, David, Mercier, Romain, Sagnier, Anne, Verrier, Nathalie, Caplin, Cecile, Siami, Shidasp, Aparicio, Christelle, Vautier, Sarah, Jeblaoui, Asma, Fartoukh, Muriel, Courtin, Laura, Labbe, Vincent, Leparco, Cécile, Muller, Grégoire, Nay, Mai-Anh, Kamel, Toufik, Benzekri, Dalila, Jacquier, Sophie, Mercier, Emmanuelle, Chartier, Delphine, Salmon, Charlotte, Dequin, PierreFrançois, Schneider, Francis, Morel, Guillaume, L’Hotellier, Sylvie, Badie, Julio, Berdaguer, Fernando Daniel, Malfroy, Sylvain, Mezher, Chaouki, Bourgoin, Charlotte, Megarbane, Bruno, Voicu, Sebastian, Deye, Nicolas, Malissin, Isabelle, Sutterlin, Laetitia, Guitton, Christophe, Darreau, Cédric, Landais, Mickaël, Chudeau, Nicolas, Robert, Alain, Moine, Pierre, Heming, Nicholas, Maxime, Virginie, Bossard, Isabelle, Nicholier, Tiphaine Barbarin, Colin, Gwenhael, Zinzoni, Vanessa, Maquigneau, Natacham, Finn, André, Kreß, Gabriele, Hoff, Uwe, Friedrich Hinrichs, Carl, Nee, Jens, Hagel, Stefan, Ankert, Juliane, Kolanos, Steffi, Bloos, Frank, Petros, Sirak, Pasieka, Bastian, Kunz, Kevin, Appelt, Peter, Schütze, Bianka, Kluge, Stefan, Nierhaus, Axel, Jarczak, Dominik, Roedl, Kevin, Weismann, Dirk, Frey, Anna, Klinikum Neukölln, Vivantes, Reill, Lorenz, Distler, Michael, Maselli, Astrid, Bélteczki, János, Magyar, István, Fazekas, Ágnes, Kovács, Sándor, Szőke, Viktória, Szigligeti, Gábor, Leszkoven, János, Collins, Daniel, Breen, Patrick, Frohlich, Stephen, Whelan, Ruth, McNicholas, Bairbre, Scully, Michael, Casey, Siobhan, Kernan, Maeve, Doran, Peter, O’Dywer, Michael, Smyth, Michelle, Hayes, Leanne, Hoiting, Oscar, Peters, Marco, Rengers, Els, Evers, Mirjam, Prinssen, Anton, Bosch Ziekenhuis, Jeroen, Simons, Koen, Rozendaal, Wim, Polderman, F, de Jager, P, Moviat, M, Paling, A, Salet, A, Rademaker, Emma, Peters, Anna Linda, de Jonge, E, Wigbers, J, Guilder, E, Butler, M, Cowdrey, Keri-Anne, Newby, Lynette, Chen, Yan, Simmonds, Catherine, McConnochie, Rachael, Ritzema Carter, Jay, Henderson, Seton, Van Der Heyden, Kym, Mehrtens, Jan, Williams, Tony, Kazemi, Alex, Song, Rima, Lai, Vivian, Girijadevi, Dinu, Everitt, Robert, Russell, Robert, Hacking, Danielle, Buehner, Ulrike, Williams, Erin, Browne, Troy, Grimwade, Kate, Goodson, Jennifer, Keet, Owen, Callender, Owen, Martynoga, Robert, Trask, Kara, Butler, Amelia, Schischka, Livia, Young, Chelsea, Lesona, Eden, Olatunji, Shaanti, Robertson, Yvonne, José, Nuno, Amaro dos Santos Catorze, Teodoro, de Lima Pereira, Tiago Nuno Alfaro, Neves Pessoa, Lucilia Maria, Castro Ferreira, Ricardo Manuel, Pereira Sousa Bastos, Joana Margarida, Aysel Florescu, Simin, Stanciu, Delia, Zaharia, Miahela Florentina, Kosa, Alma Gabriela, Codreanu, Daniel, Marabi, Yaseen, Al Qasim, Eman, Moneer Hagazy, Mohamned, Al Swaidan, Lolowa, Arishi, Hatim, Muñoz-Bermúdez, Rosana, Marin-Corral, Judith, Salazar Degracia, Anna, Parrilla Gómez, Francisco, Mateo López, Maria Isabel, Rodriguez Fernandez, Jorge, Cárcel Fernández, Sheila, Carmona Flores, Rosario, León López, Rafael, de la Fuente Martos, Carmen, Allan, Angela, Polgarova, Petra, Farahi, Neda, McWilliam, Stephen, Hawcutt, Daniel, Rad, Laura, O’Malley, Laura, Whitbread, Jennifer, Kelsall, Olivia, Wild, Laura, Thrush, Jessica, Wood, Hannah, Austin, Karen, Donnelly, Adrian, Kelly, Martin, O’Kane, Sinéad, McClintock, Declan, Warnock, Majella, Johnston, Paul, Gallagher, Linda Jude, Mc Goldrick, Clare, Mc Master, Moyra, Strzelecka, Anna, Jha, Rajeev, Kalogirou, Michael, Ellis, Christine, Krishnamurthy, Vinodh, Deelchand, Vashish, Silversides, Jon, McGuigan, Peter, Ward, Kathryn, O’Neill, Aisling, Finn, Stephanie, Phillips, Barbara, Mullan, Dee, Oritz-Ruiz de Gordoa, Laura, Thomas, Matthew, Sweet, Katie, Grimmer, Lisa, Johnson, Rebekah, Pinnell, Jez, Robinson, Matt, Gledhill, Lisa, Wood, Tracy, Morgan, Matt, Cole, Jade, Hill, Helen, Davies, Michelle, Antcliffe, David, Templeton, Maie, Rojo, Roceld, Coghlan, Phoebe, Smee, Joanna, Mackay, Euan, Cort, Jon, Whileman, Amanda, Spencer, Thomas, Spittle, Nick, Kasipandian, Vidya, Patel, Amit, Allibone, Suzanne, Genetu, Roman Mary, Ramali, Mohamed, Ghosh, Alison, Bamford, Peter, London, Emily, Cawley, Kathryn, Faulkner, Maria, Jeffrey, Helen, Smith, Tim, Brewer, Chris, Gregory, Jane, Limb, James, Cowton, Amanda, O’Brien, Julie, Nikitas, Nikitas, Wells, Colin, Lankester, Liana, Pulletz, Mark, Birch, Jenny, Wiseman, Sophie, Horton, Sarah, Alegria, Ana, Turki, Salah, Elsefi, Tarek, Crisp, Nikki, Allen, Louise, McCullagh, Iain, Robinson, Philip, Hays, Carole, Babio-Galan, Maite, Stevenson, Hannah, Khare, Divya, Pinder, Meredith, Selvamoni, Selvin, Gopinath, Amitha, Pugh, Richard, Menzies, Daniel, Mackay, Callum, Allan, Elizabeth, Davies, Gwyneth, Puxty, Kathryn, McCue, Claire, Cathcart, Susanne, Hickey, Naomi, Ireland, Jane, Yusuff, Hakeem, Isgro, Graziella, Brightling, Chris, Bourne, Michelle, Craner, Michelle, Watters, Malcolm, Prout, Rachel, Davies, Louisa, Pegler, Suzannah, Kyeremeh, Lynsey, Arbane, Gill, Wilson, Karen, Gomm, Linda, Francia, Federica, Brett, Stephen, Sousa Arias, Sonia, Elin Hall, Rebecca, Budd, Joanna, Small, Charlotte, Birch, Janine, Collins, Emma, Henning, Jeremy, Bonner, Stephen, Hugill, Keith, Cirstea, Emanuel, Wilkinson, Dean, Karlikowski, Michal, Sutherland, Helen, Wilhelmsen, Elva, Woods, Jane, North, Julie, Sundaran, Dhinesh, Hollos, Laszlo, Coburn, Susan, Walsh, Joanne, Turns, Margaret, Hopkins, Phil, Smith, John, Noble, Harriet, Depante, Maria Theresa, Clarey, Emma, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Huckle, Abby, Hall, Andrew, Cooke, Jill, Gardiner-Hill, Caroline, Maloney, Carolyn, Qureshi, Hafiz, Flint, Neil, Nicholson, Sarah, Southin, Sara, Nicholson, Andrew, Borgatta, Barbara, Turner-Bone, Ian, Reddy, Amie, Wilding, Laura, Chamara Warnapura, Loku, Agno Sathianathan, Ronan, Golden, David, Hart, Ciaran, Jones, Jo, Bannard-Smith, Jonathan, Henry, Joanne, Birchall, Katie, Pomeroy, Fiona, Quayle, Rachael, Makowski, Arystarch, Misztal, Beata, Ahmed, Iram, KyereDiabour, Thyra, Naiker, Kevin, Stewart, Richard, Mwaura, Esther, Mew, Louise, Wren, Lynn, Willams, Felicity, Innes, Richard, Doble, Patricia, Hutter, Joanne, Shovelton, Charmaine, Plumb, Benjamin, Szakmany, Tamas, Hamlyn, Vincent, Hawkins, Nancy, Lewis, Sarah, Dell, Amanda, Gopal, Shameer, Ganguly, Saibal, Smallwood, Andrew, Harris, Nichola, Metherell, Stella, Lazaro, Juan Martin, Newman, Tabitha, Fletcher, Simon, Nortje, Jurgens, Fottrell-Gould, Deirdre, Randell, Georgina, Zaman, Mohsin, Elmahi, Einas, Jones, Andrea, Hall, Kathryn, Mills, Gary, Ryalls, Kim, Bowler, Helen, Sall, Jas, Bourne, Richard, Borrill, Zoe, Duncan, Tracey, Lamb, Thomas, Shaw, Joanne, Fox, Claire, Moreno Cuesta, Jeronimo, Xavier, Kugan, Purohit, Dharam, Elhassan, Munzir, Bakthavatsalam, Dhanalakshmi, Rowland, Matthew, Hutton, Paula, Bashyal, Archana, Davidson, Neil, Hird, Clare, Chhablani, Manish, Phalod, Gunjan, Kirkby, Amy, Archer, Simon, Netherton, Kimberley, Reschreiter, Henrik, Camsooksai, Julie, Patch, Sarah, Jenkins, Sarah, Pogson, David, Rose, Steve, Daly, Zoe, Brimfield, Lutece, Claridge, Helen, Parekh, Dhruv, Bergin, Colin, Bates, Michelle, Dasgin, Joanne, McGhee, Christopher, Sim, Malcolm, Hay, Sophie Kennedy, Henderson, Steven, Phull, Mandeep-Kaur, Zaidi, Abbas, Pogreban, Tatiana, Rosaroso, Lace Paulyn, Harvey, Daniel, Lowe, Benjamin, Meredith, Megan, Ryan, Lucy, Hormis, Anil, Walker, Rachel, Collier, Dawn, Kimpton, Sarah, Oakley, Susan, Rooney, Kevin, Rodden, Natalie, Hughes, Emma, Thomson, Nicola, McGlynn, Deborah, Walden, Andrew, Jacques, Nicola, Coles, Holly, Tilney, Emma, Vowell, Emma, Schuster-Bruce, Martin, Pitts, Sally, Miln, Rebecca, Purandare, Laura, Vamplew, Luke, Spivey, Michael, Bean, Sarah, Burt, Karen, Moore, Lorraine, Day, Christopher, Gibson, Charly, Gordon, Elizabeth, Zitter, Letizia, Keenan, Samantha, Baker, Evelyn, Cherian, Shiney, Cutler, Sean, Roynon-Reed, Anna, Harrington, Kate, Raithatha, Ajay, Bauchmuller, Kris, Ahmad, Norfaizan, Grecu, Irina, Trodd, Dawn, Martin, Jane, Wrey Brown, Caroline, Arias, Ana-Marie, Craven, Thomas, Hope, David, Singleton, Jo, Clark, Sarah, Rae, Nicola, Welters, Ingeborg, Hamilton, David Oliver, Williams, Karen, Waugh, Victoria, Shaw, David, Puthucheary, Zudin, Martin, Timothy, Santos, Filipa, Uddin, Ruzena, Somerville, Alastair, Tatham, Kate Colette, Jhanji, Shaman, Black, Ethel, Dela Rosa, Arnold, Howle, Ryan, Tully, Redmond, Drummond, Andrew, Dearden, Joy, Philbin, Jennifer, Munt, Sheila, Vuylsteke, Alain, Chan, Charles, Victor, Saji, Matsa, Ramprasad, Gellamucho, Minerva, Creagh-Brown, Ben, Tooley, Joe, Montague, Laura, De Beaux, Fiona, Bullman, Laetitia, Kersiake, Ian, Demetriou, Carrie, Mitchard, Sarah, Ramos, Lidia, White, Katie, Donnison, Phil, Johns, Maggie, Casey, Ruth, Mattocks, Lehentha, Salisbury, Sarah, Dark, Paul, Claxton, Andrew, McLachlan, Danielle, Slevin, Kathryn, Lee, Stephanie, Hulme, Jonathan, Joseph, Sibet, Kinney, Fiona, Senya, Ho Jan, Oborska, Aneta, Kayani, Abdul, Hadebe, Bernard, Orath Prabakaran, Rajalakshmi, Nichols, Lesley, Thomas, Matt, Worner, Ruth, Faulkner, Beverley, Gendall, Emma, Hayes, Kati, Hamilton-Davies, Colin, Chan, Carmen, Mfuko, Celina, Abbass, Hakam, Mandadapu, Vineela, Leaver, Susannah, Forton, Daniel, Patel, Kamal, Paramasivam, Elankumaran, Powell, Matthew, Gould, Richard, Wilby, Elizabeth, Howcroft, Clare, Banach, Dorota, Fernández de Pinedo Artaraz, Ziortza, Cabreros, Leilani, White, Ian, Croft, Maria, Holland, Nicky, Pereira, Rita, Zaki, Ahmed, Johnson, David, Jackson, Matthew, Garrard, Hywel, Juhaz, Vera, Roy, Alistair, Rostron, Anthony, Woods, Lindsey, Cornell, Sarah, Pillai, Suresh, Harford, Rachel, Rees, Tabitha, Ivatt, Helen, Sundara Raman, Ajay, Davey, Miriam, Lee, Kelvin, Barber, Russell, Chablani, Manish, Brohi, Farooq, Jagannathan, Vijay, Clark, Michele, Purvis, Sarah, Wetherill, Bill, Dushianthan, Ahilanandan, Cusack, Rebecca, de Courcy-Golder, Kim, Smith, Simon, Jackson, Susan, Attwood, Ben, Parsons, Penny, Page, Valerie, Zhao, Xiao Bei, Oza, Deepali, Rhodes, Jonathan, Anderson, Tom, Morris, Sheila, Xia Le Tai, Charlotte, Thomas, Amy, Keen, Alexandra, Digby, Stephen, Cowley, Nicholas, Southern, David, Reddy, Harsha, Campbell, Andy, Watkins, Claire, Smuts, Sara, Touma, Omar, Barnes, Nicky, Alexander, Peter, Felton, Tim, Ferguson, Susan, Sellers, Katharine, Bradley-Potts, Joanne, Yates, David, Birkinshaw, Isobel, Kell, Kay, Marshall, Nicola, Carr-Knott, Lisa, Writing Committee for the REMAP-CAP Investigators, Menon, David [0000-0002-3228-9692], Apollo - University of Cambridge Repository, Medical Microbiology and Infection Prevention, and AII - Infectious diseases

Subjects
Male, Hydrocortisone, Anti-Inflammatory Agents, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], 01 natural sciences, law.invention, 0302 clinical medicine, Randomized controlled trial, law, Adrenal Cortex Hormones, Clinical endpoint, Medicine, 030212 general & internal medicine, Hydrocortisone/administration & dosage, Original Investigation, 2. Zero hunger, Mortality rate, Shock, Covid19, General Medicine, Middle Aged, Intensive care unit, 3. Good health, Intensive Care Units, Treatment Outcome, Early Termination of Clinical Trials, Corticosteroid, Female, Coronavirus Infections, medicine.drug, Adult, medicine.medical_specialty, Respiration, Artificial/statistics & numerical data, medicine.drug_class, Anti-Inflammatory Agents/administration & dosage, Pneumonia, Viral, UNCOVER, Adrenal Cortex Hormones/therapeutic use, 03 medical and health sciences, Betacoronavirus, All institutes and research themes of the Radboud University Medical Center, Internal medicine, Humans, 0101 mathematics, Adverse effect, Pandemics, business.industry, SARS-CoV-2, 010102 general mathematics, COVID-19, Odds ratio, Coronavirus Infections/drug therapy, Pneumonia, Viral/drug therapy, Respiration, Artificial, COVID-19 Drug Treatment, Shock/drug therapy, Human medicine, business
Abstract

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited.Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19.Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020.Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108).Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%).Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively.Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions.Trial Registration: ClinicalTrials.gov Identifier: NCT02735707.

Published
2020

8. Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial

Author

Angus, Derek C, Derde, Lennie, Al-Beidh, Farah, Annane, Djillali, Arabi, Yaseen, Beane, Abigail, Van Bentum-Puijk, Wilma, Berry, Lindsay, Bhimani, Zahra, Bonten, Marc, Bradbury, Charlotte, Brunkhorst, Frank, Buxton, Meredith, Buzgau, Adrian, Cheng, Allen C, De Jong, Menno, Detry, Michelle, Estcourt, Lise, Fitzgerald, Mark, Goossens, Herman, Green, Cameron, Haniffa, Rashan, Higgins, Alisa M, Horvat, Christopher, Hullegie, Sebastiaan J, Kruger, Peter, Lamontagne, Francois, Lawler, Patrick R, Linstrum, Kelsey, Litton, Edward, Lorenzi, Elizabeth, Marshall, John, McAuley, Daniel, McGlothin, Anna, McGuinness, Shay, McVerry, Bryan, Montgomery, Stephanie, Mouncey, Paul, Murthy, Srinivas, Nichol, Alistair, Parke, Rachael, Parker, Jane, Rowan, Kathryn, Sanil, Ashish, Santos, Marlene, Saunders, Christina, Seymour, Christopher, Turner, Anne, Van De Veerdonk, Frank, Venkatesh, Balasubramanian, Zarychanski, Ryan, Berry, Scott, Lewis, Roger J, McArthur, Colin, Webb, Steven A, Gordon, Anthony C, Writing Committee For The REMAP-CAP Investigators, Angus, Derek, Cheng, Allen, Gordon, Anthony, Lawler, Patrick, Webb, Steve, Campbell, Lewis, Forbes, Andrew, Gattas, David, Heritier, Stephane, Higgins, Lisa, Peake, Sandra, Presneill, Jeffrey, Seppelt, Ian, Trapani, Tony, Young, Paul, Bagshaw, Sean, Daneman, Nick, Ferguson, Niall, Misak, Cheryl, Hullegie, Sebastiaan, Pletz, Mathias, Rohde, Gernot, Rowan, Kathy, Alexander, Brian, Basile, Kim, Girard, Timothy, Huang, David, Vates, Jennifer, Beasley, Richard, Fowler, Robert, McGloughlin, Steve, Morpeth, Susan, Paterson, David, Venkatesh, Bala, Uyeki, Tim, Baillie, Kenneth, Duffy, Eamon, Fowler, Rob, Hills, Thomas, Orr, Katrina, Patanwala, Asad, Tong, Steve, Netea, Mihai, Bihari, Shilesh, Carrier, Marc, Fergusson, Dean, Goligher, Ewan, Haidar, Ghady, Hunt, Beverley, Kumar, Anand, Laffan, Mike, Lawless, Patrick, Lother, Sylvain, McCallum, Peter, Middeldopr, Saskia, McQuilten, Zoe, Neal, Matthew, Pasi, John, Schutgens, Roger, Stanworth, Simon, Turgeon, Alexis, Weissman, Alexandra, Adhikari, Neill, Anstey, Matthew, Brant, Emily, De Man, Angelique, Lamonagne, Francois, Masse, Marie-Helene, Udy, Andrew, Arnold, Donald, Begin, Phillipe, Charlewood, Richard, Chasse, Michael, Coyne, Mark, Cooper, Jamie, Daly, James, Gosbell, Iain, Harvala-Simmonds, Heli, Hills, Tom, MacLennan, Sheila, Menon, David, McDyer, John, Pridee, Nicole, Roberts, David, Shankar-Hari, Manu, Thomas, Helen, Tinmouth, Alan, Triulzi, Darrell, Walsh, Tim, Wood, Erica, Calfee, Carolyn, O’Kane, Cecilia, Shyamsundar, Murali, Sinha, Pratik, Thompson, Taylor, Young, Ian, Bihari, Shailesh, Hodgson, Carol, Laffey, John, McAuley, Danny, Orford, Neil, Neto, Ary, Lewis, Roger, McGlothlin, Anna, Miller, Eliza, Singh, Vanessa, Zammit, Claire, Van Bentum Puijk, Wilma, Bouwman, Wietske, Mangindaan, Yara, Parker, Lorraine, Peters, Svenja, Rietveld, Ilse, Raymakers, Kik, Ganpat, Radhika, Brillinger, Nicole, Markgraf, Rene, Ainscough, Kate, Brickell, Kathy, Anjum, Aisha, Lane, Janis-Best, Richards-Belle, Alvin, Saull, Michelle, Wiley, Daisy, Bion, Julian, Connor, Jason, Gates, Simon, Manax, Victoria, Van Der Poll, Tom, Reynolds, John, Van Beurden, Marloes, Effelaar, Evelien, Schotsman, Joost, Boyd, Craig, Harland, Cain, Shearer, Audrey, Wren, Jess, Clermont, Giles, Garrard, William, Kalchthaler, Kyle, King, Andrew, Ricketts, Daniel, Malakoutis, Salim, Marroquin, Oscar, Music, Edvin, Quinn, Kevin, Cate, Heidi, Pearson, Karen, Collins, Joanne, Hanson, Jane, Williams, Penny, Jackson, Shane, Asghar, Adeeba, Dyas, Sarah, Sutu, Mihaela, Murphy, Sheenagh, Williamson, Dawn, Mguni, Nhlanhla, Potter, Alison, Porter, David, Goodwin, Jayne, Rook, Clare, Harrison, Susie, Williams, Hannah, Campbell, Hilary, Lomme, Kaatje, Williamson, James, Sheffield, Jonathan, Van’t Hoff, Willian, McCracken, Phobe, Young, Meredith, Board, Jasmin, Mart, Emma, Knott, Cameron, Smith, Julie, Boschert, Catherine, Affleck, Julia, Ramanan, Mahesh, D’Souza, Ramsy, Pateman, Kelsey, Shakih, Arif, Cheung, Winston, Kol, Mark, Wong, Helen, Shah, Asim, Wagh, Atul, Simpson, Joanne, Duke, Graeme, Chan, Peter, Cartner, Brittney, Hunter, Stephanie, Laver, Russell, Shrestha, Tapaswi, Regli, Adrian, Pellicano, Annamaria, McCullough, James, Tallott, Mandy, Kumar, Nikhil, Panwar, Rakshit, Brinkerhoff, Gail, Koppen, Cassandra, Cazzola, Federica, Brain, Matthew, Mineall, Sarah, Fischer, Roy, Biradar, Vishwanath, Soar, Natalie, White, Hayden, Estensen, Kristen, Morrison, Lynette, Smith, Joanne, Cooper, Melanie, Health, Monash, Shehabi, Yahya, Al-Bassam, Wisam, Hulley, Amanda, Whitehead, Christina, Lowrey, Julie, Gresha, Rebecca, Walsham, James, Meyer, Jason, Harward, Meg, Venz, Ellen, Williams, Patricia, Kurenda, Catherine, Smith, Kirsy, Smith, Margaret, Garcia, Rebecca, Barge, Deborah, Byrne, Deborah, Byrne, Kathleen, Driscoll, Alana, Fortune, Louise, Janin, Pierre, Yarad, Elizabeth, Hammond, Naomi, Bass, Frances, Ashelford, Angela, Waterson, Sharon, Wedd, Steve, McNamara, Robert, Buhr, Heidi, Coles, Jennifer, Schweikert, Sacha, Wibrow, Bradley, Rauniyar, Rashmi, Myers, Erina, Fysh, Ed, Dawda, Ashlish, Mevavala, Bhaumik, Litton, Ed, Ferrier, Janet, Nair, Priya, Buscher, Hergen, Reynolds, Claire, Santamaria, John, Barbazza, Leanne, Homes, Jennifer, Smith, Roger, Murray, Lauren, Brailsford, Jane, Forbes, Loretta, Maguire, Teena, Mariappa, Vasanth, Smith, Judith, Simpson, Scott, Maiden, Matthew, Bone, Allsion, Horton, Michelle, Salerno, Tania, Sterba, Martin, Geng, Wenli, Depuydt, Pieter, De Waele, Jan, De Bus, Liesbet, Fierens, Jan, Bracke, Stephanie, Reeve, Brenda, Dechert, William, Chassé, Michaël, Carrier, François Martin, Boumahni, Dounia, Benettaib, Fatna, Ghamraoui, Ali, Bellemare, David, Cloutier, Ève, Francoeur, Charles, Lamontagne, François, D’Aragon, Frédérick, Carbonneau, Elaine, Leblond, Julie, Vazquez-Grande, Gloria, Marten, Nicole, Wilson, Maggie, Albert, Martin, Serri, Karim, Cavayas, Alexandros, Duplaix, Mathilde, Williams, Virginie, Rochwerg, Bram, Karachi, Tim, Oczkowski, Simon, Centofanti, John, Millen, Tina, Duan, Erick, Tsang, Jennifer, Patterson, Lisa, English, Shane, Watpool, Irene, Porteous, Rebecca, Miezitis, Sydney, McIntyre, Lauralyn, Brochard, Laurent, Burns, Karen, Sandhu, Gyan, Khalid, Imrana, Binnie, Alexandra, Powell, Elizabeth, McMillan, Alexandra, Luk, Tracy, Aref, Noah, Andric, Zdravko, Cviljevic, Sabina, Đimoti, Renata, Zapalac, Marija, Mirković, Gordan, Baršić, Bruno, Kutleša, Marko, Kotarski, Viktor, Vujaklija Brajković, Ana, Babel, Jakša, Sever, Helena, Dragija, Lidija, Kušan, Ira, Vaara, Suvi, Pettilä, Leena, Heinonen, Jonna, Kuitunen, Anne, Karlsson, Sari, Vahtera, Annukka, Kiiski, Heikki, Ristimäki, Sanna, Azaiz, Amine, Charron, Cyril, Godement, Mathieu, Geri, Guillaume, Vieillard-Baron, Antoine, Pourcine, Franck, Monchi, Mehran, Luis, David, Mercier, Romain, Sagnier, Anne, Verrier, Nathalie, Caplin, Cecile, Siami, Shidasp, Aparicio, Christelle, Vautier, Sarah, Jeblaoui, Asma, Fartoukh, Muriel, Courtin, Laura, Labbe, Vincent, Leparco, Cécile, Muller, Grégoire, Nay, Mai-Anh, Kamel, Toufik, Benzekri, Dalila, Jacquier, Sophie, Mercier, Emmanuelle, Chartier, Delphine, Salmon, Charlotte, Dequin, PierreFrançois, Schneider, Francis, Morel, Guillaume, L’Hotellier, Sylvie, Badie, Julio, Berdaguer, Fernando Daniel, Malfroy, Sylvain, Mezher, Chaouki, Bourgoin, Charlotte, Megarbane, Bruno, Voicu, Sebastian, Deye, Nicolas, Malissin, Isabelle, Sutterlin, Laetitia, Guitton, Christophe, Darreau, Cédric, Landais, Mickaël, Chudeau, Nicolas, Robert, Alain, Moine, Pierre, Heming, Nicholas, Maxime, Virginie, Bossard, Isabelle, Nicholier, Tiphaine Barbarin, Colin, Gwenhael, Zinzoni, Vanessa, Maquigneau, Natacham, Finn, André, Kreß, Gabriele, Hoff, Uwe, Friedrich Hinrichs, Carl, Nee, Jens, Hagel, Stefan, Ankert, Juliane, Kolanos, Steffi, Bloos, Frank, Petros, Sirak, Pasieka, Bastian, Kunz, Kevin, Appelt, Peter, Schütze, Bianka, Kluge, Stefan, Nierhaus, Axel, Jarczak, Dominik, Roedl, Kevin, Weismann, Dirk, Frey, Anna, Klinikum Neukölln, Vivantes, Reill, Lorenz, Distler, Michael, Maselli, Astrid, Bélteczki, János, Magyar, István, Fazekas, Ágnes, Kovács, Sándor, Szőke, Viktória, Szigligeti, Gábor, Leszkoven, János, Collins, Daniel, Breen, Patrick, Frohlich, Stephen, Whelan, Ruth, McNicholas, Bairbre, Scully, Michael, Casey, Siobhan, Kernan, Maeve, Doran, Peter, O’Dywer, Michael, Smyth, Michelle, Hayes, Leanne, Hoiting, Oscar, Peters, Marco, Rengers, Els, Evers, Mirjam, Prinssen, Anton, Bosch Ziekenhuis, Jeroen, Simons, Koen, Rozendaal, Wim, Polderman, F, De Jager, P, Moviat, M, Paling, A, Salet, A, Rademaker, Emma, Peters, Anna Linda, De Jonge, E, Wigbers, J, Guilder, E, Butler, M, Cowdrey, Keri-Anne, Newby, Lynette, Chen, Yan, Simmonds, Catherine, McConnochie, Rachael, Ritzema Carter, Jay, Henderson, Seton, Van Der Heyden, Kym, Mehrtens, Jan, Williams, Tony, Kazemi, Alex, Song, Rima, Lai, Vivian, Girijadevi, Dinu, Everitt, Robert, Russell, Robert, Hacking, Danielle, Buehner, Ulrike, Williams, Erin, Browne, Troy, Grimwade, Kate, Goodson, Jennifer, Keet, Owen, Callender, Owen, Martynoga, Robert, Trask, Kara, Butler, Amelia, Schischka, Livia, Young, Chelsea, Lesona, Eden, Olatunji, Shaanti, Robertson, Yvonne, José, Nuno, Amaro Dos Santos Catorze, Teodoro, De Lima Pereira, Tiago Nuno Alfaro, Neves Pessoa, Lucilia Maria, Castro Ferreira, Ricardo Manuel, Pereira Sousa Bastos, Joana Margarida, Aysel Florescu, Simin, Stanciu, Delia, Zaharia, Miahela Florentina, Kosa, Alma Gabriela, Codreanu, Daniel, Marabi, Yaseen, Al Qasim, Eman, Moneer Hagazy, Mohamned, Al Swaidan, Lolowa, Arishi, Hatim, Muñoz-Bermúdez, Rosana, Marin-Corral, Judith, Salazar Degracia, Anna, Parrilla Gómez, Francisco, Mateo López, Maria Isabel, Rodriguez Fernandez, Jorge, Cárcel Fernández, Sheila, Carmona Flores, Rosario, León López, Rafael, De La Fuente Martos, Carmen, Allan, Angela, Polgarova, Petra, Farahi, Neda, McWilliam, Stephen, Hawcutt, Daniel, Rad, Laura, O’Malley, Laura, Whitbread, Jennifer, Kelsall, Olivia, Wild, Laura, Thrush, Jessica, Wood, Hannah, Austin, Karen, Donnelly, Adrian, Kelly, Martin, O’Kane, Sinéad, McClintock, Declan, Warnock, Majella, Johnston, Paul, Gallagher, Linda Jude, Mc Goldrick, Clare, Mc Master, Moyra, Strzelecka, Anna, Jha, Rajeev, Kalogirou, Michael, Ellis, Christine, Krishnamurthy, Vinodh, Deelchand, Vashish, Silversides, Jon, McGuigan, Peter, Ward, Kathryn, O’Neill, Aisling, Finn, Stephanie, Phillips, Barbara, Mullan, Dee, Oritz-Ruiz De Gordoa, Laura, Thomas, Matthew, Sweet, Katie, Grimmer, Lisa, Johnson, Rebekah, Pinnell, Jez, Robinson, Matt, Gledhill, Lisa, Wood, Tracy, Morgan, Matt, Cole, Jade, Hill, Helen, Davies, Michelle, Antcliffe, David, Templeton, Maie, Rojo, Roceld, Coghlan, Phoebe, Smee, Joanna, Mackay, Euan, Cort, Jon, Whileman, Amanda, Spencer, Thomas, Spittle, Nick, Kasipandian, Vidya, Patel, Amit, Allibone, Suzanne, Genetu, Roman Mary, Ramali, Mohamed, Ghosh, Alison, Bamford, Peter, London, Emily, Cawley, Kathryn, Faulkner, Maria, Jeffrey, Helen, Smith, Tim, Brewer, Chris, Gregory, Jane, Limb, James, Cowton, Amanda, O’Brien, Julie, Nikitas, Nikitas, Wells, Colin, Lankester, Liana, Pulletz, Mark, Birch, Jenny, Wiseman, Sophie, Horton, Sarah, Alegria, Ana, Turki, Salah, Elsefi, Tarek, Crisp, Nikki, Allen, Louise, McCullagh, Iain, Robinson, Philip, Hays, Carole, Babio-Galan, Maite, Stevenson, Hannah, Khare, Divya, Pinder, Meredith, Selvamoni, Selvin, Gopinath, Amitha, Pugh, Richard, Menzies, Daniel, Mackay, Callum, Allan, Elizabeth, Davies, Gwyneth, Puxty, Kathryn, McCue, Claire, Cathcart, Susanne, Hickey, Naomi, Ireland, Jane, Yusuff, Hakeem, Isgro, Graziella, Brightling, Chris, Bourne, Michelle, Craner, Michelle, Watters, Malcolm, Prout, Rachel, Davies, Louisa, Pegler, Suzannah, Kyeremeh, Lynsey, Arbane, Gill, Wilson, Karen, Gomm, Linda, Francia, Federica, Brett, Stephen, Sousa Arias, Sonia, Elin Hall, Rebecca, Budd, Joanna, Small, Charlotte, Birch, Janine, Collins, Emma, Henning, Jeremy, Bonner, Stephen, Hugill, Keith, Cirstea, Emanuel, Wilkinson, Dean, Karlikowski, Michal, Sutherland, Helen, Wilhelmsen, Elva, Woods, Jane, North, Julie, Sundaran, Dhinesh, Hollos, Laszlo, Coburn, Susan, Walsh, Joanne, Turns, Margaret, Hopkins, Phil, Smith, John, Noble, Harriet, Depante, Maria Theresa, Clarey, Emma, Laha, Shondipon, Verlander, Mark, Williams, Alexandra, Huckle, Abby, Hall, Andrew, Cooke, Jill, Gardiner-Hill, Caroline, Maloney, Carolyn, Qureshi, Hafiz, Flint, Neil, Nicholson, Sarah, Southin, Sara, Nicholson, Andrew, Borgatta, Barbara, Turner-Bone, Ian, Reddy, Amie, Wilding, Laura, Chamara Warnapura, Loku, Agno Sathianathan, Ronan, Golden, David, Hart, Ciaran, Jones, Jo, Bannard-Smith, Jonathan, Henry, Joanne, Birchall, Katie, Pomeroy, Fiona, Quayle, Rachael, Makowski, Arystarch, Misztal, Beata, Ahmed, Iram, KyereDiabour, Thyra, Naiker, Kevin, Stewart, Richard, Mwaura, Esther, Mew, Louise, Wren, Lynn, Willams, Felicity, Innes, Richard, Doble, Patricia, Hutter, 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Subjects
2. Zero hunger, Adult, Male, Hydrocortisone, SARS-CoV-2, Pneumonia, Viral, Anti-Inflammatory Agents, COVID-19, Shock, Middle Aged, Respiration, Artificial, 3. Good health, Betacoronavirus, Intensive Care Units, Treatment Outcome, Adrenal Cortex Hormones, Early Termination of Clinical Trials, Humans, Female, Coronavirus Infections, Pandemics
Abstract

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707.

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