12 results on '"Cheung, Winston"'
Search Results
2. Outcomes for patients with COVID-19 admitted to Australian intensive care units during the first four months of the pandemic.
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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
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- 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
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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.)
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- 2021
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3. Problematic Dichotomization of Risk for Intensive Care Unit (ICU)-Acquired Invasive Candidiasis: Results Using a Risk-Predictive Model to Categorize 3 Levels of Risk From a Multicenter Prospective Cohort of Australian ICU Patients.
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Playford EG, Lipman J, Jones M, Lau AF, Kabir M, Chen SC, Marriott DJ, Seppelt I, Gottlieb T, Cheung W, Iredell JR, McBryde ES, and Sorrell TC
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- Adult, Aged, Antifungal Agents therapeutic use, Australia epidemiology, Candida isolation & purification, Candidiasis epidemiology, Candidiasis microbiology, Candidiasis prevention & control, Candidiasis, Invasive drug therapy, Candidiasis, Invasive microbiology, Candidiasis, Invasive prevention & control, Cohort Studies, Critical Illness, Cross Infection microbiology, Cross Infection prevention & control, Female, Humans, Male, Middle Aged, Models, Theoretical, Predictive Value of Tests, Prospective Studies, ROC Curve, Risk Assessment, Risk Factors, Candidiasis, Invasive epidemiology, Cross Infection epidemiology, Intensive Care Units
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Background: Delayed antifungal therapy for invasive candidiasis (IC) contributes to poor outcomes. Predictive risk models may allow targeted antifungal prophylaxis to those at greatest risk., Methods: A prospective cohort study of 6685 consecutive nonneutropenic patients admitted to 7 Australian intensive care units (ICUs) for ≥72 hours was performed. Clinical risk factors for IC occurring prior to and following ICU admission, colonization with Candida species on surveillance cultures from 3 sites assessed twice weekly, and the occurrence of IC ≥72 hours following ICU admission or ≤72 hours following ICU discharge were measured. From these parameters, a risk-predictive model for the development of ICU-acquired IC was then derived., Results: Ninety-six patients (1.43%) developed ICU-acquired IC. A simple summation risk-predictive model using the 10 independently significant variables associated with IC demonstrated overall moderate accuracy (area under the receiver operating characteristic curve = 0.82). No single threshold score could categorize patients into clinically useful high- and low-risk groups. However, using 2 threshold scores, 3 patient cohorts could be identified: those at high risk (score ≥6, 4.8% of total cohort, positive predictive value [PPV] 11.7%), those at low risk (score ≤2, 43.1% of total cohort, PPV 0.24%), and those at intermediate risk (score 3-5, 52.1% of total cohort, PPV 1.46%)., Conclusions: Dichotomization of ICU patients into high- and low-risk groups for IC risk is problematic. Categorizing patients into high-, intermediate-, and low-risk groups may more efficiently target early antifungal strategies and utilization of newer diagnostic tests., (© The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.)
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- 2016
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4. A multicentre evaluation of two intensive care unit triage protocols for use in an influenza pandemic.
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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
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- 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.
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- 2012
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5. Design of Australasian intensive care units: time for change or time for more research?
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Cheung W
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- Critical Care, Humans, Infection Control, Outcome Assessment, Health Care, Patient Satisfaction, Cross Infection, Intensive Care Units
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Recommendations exist to guide the design and construction of adult intensive care units, but current guidelines are hampered by the paucity of high-quality research. Much of the current literature on ICU design has focused on patient-centred outcomes, such as nosocomial infections, aspects of psychological and physiological wellbeing, and patient satisfaction, but the design of the ICU environment also affects health care workers. The literature seems to favour the use of single rooms rather than an open-plan ICU design, with the major benefits being to infection control, but this notion is controversial. For most aspects of ICU design, more research is required before definite conclusions can be drawn. This article discusses the application of evidence-based design to improve the ICU environment and reviews some of the controversial issues and concepts.
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- 2008
6. A survey of Australian public opinion on using comorbidity to triage intensive care patients in a pandemic.
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Cheung, Winston, Naganathan, Vasi, Myburgh, John, Saxena, Manoj K., Fiona, Blyth, Seppelt, Ian, Parr, Michael, Hooker, Claire, Kerridge, Ian, Nguyen, Nhi, Kelly, Sean, Skowronski, George, Hammond, Naomi, Attokaran, Antony, Chalmers, Debbie, Gandhi, Kalpesh, Kol, Mark, McGuinness, Shay, Nair, Priya, and Nayyar, Vineet
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AT-risk people , *STATISTICAL sampling , *HEALTH policy , *QUESTIONNAIRES , *PUBLIC opinion , *DESCRIPTIVE statistics , *CHI-squared test , *SURVEYS , *CHRONIC diseases , *INTENSIVE care units , *FRONTLINE personnel , *DISASTERS , *SURVIVAL analysis (Biometry) , *PUBLIC health , *CONFIDENCE intervals , *DATA analysis software , *COVID-19 pandemic , *COMORBIDITY , *MEDICAL triage , *CRITICAL care medicine - Abstract
Objectives: This study aimed to determine which method to triage intensive care patients using chronic comorbidity in a pandemic was perceived to be the fairest by the general public. Secondary objectives were to determine whether the public perceived it fair to provide preferential intensive care triage to vulnerable or disadvantaged people, and frontline healthcare workers. Methods: A postal survey of 2000 registered voters randomly selected from the Australian Electoral Commission electoral roll was performed. The main outcome measures were respondents' fairness rating of four hypothetical intensive care triage methods that assess comorbidity (chronic medical conditions, long-term survival, function and frailty); and respondents' fairness rating of providing preferential triage to vulnerable or disadvantaged people, and frontline healthcare workers. Results: The proportion of respondents who considered it fair to triage based on chronic medical conditions, long-term survival, function and frailty, was 52.1, 56.1, 65.0 and 62.4%, respectively. The proportion of respondents who considered it unfair to triage based on these four comorbidities was 31.9, 30.9, 23.8 and 23.2%, respectively. More respondents considered it unfair to preferentially triage vulnerable or disadvantaged people, than fair (41.8% versus 21.2%). More respondents considered it fair to preferentially triage frontline healthcare workers, than unfair (44.2% versus 30.0%). Conclusion: Respondents in this survey perceived all four hypothetical methods to triage intensive care patients based on comorbidity in a pandemic disaster to be fair. However, the sizable minority who consider this to be unfair indicates that these triage methods could encounter significant opposition if they were to be enacted in health policy. What is known about the topic? Triage systems can be used to prioritise the order in which patients are treated in a pandemic, but the views of the general public on using chronic comorbidity as intensive care unit (ICU) triage criteria are unknown. What does this paper add? This Australian survey, conducted during the coronavirus disease 2019 pandemic, demonstrated that the majority of respondents perceived ICU triage methods based on comorbidity to be fair, but significant ethical issues exist. What are the implications for practitioners? It may be possible to develop an ICU triage protocol for future pandemics in Australia, but further research is required. [ABSTRACT FROM AUTHOR]
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- 2024
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7. Development and evaluation of an influenza pandemic intensive care unit triage protocol
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Cheung, Winston, Myburgh, John, Seppelt, Ian M, Parr, Michael J, Blackwell, Nikki, DeMonte, Shannon, Gandhi, Kalpesh, Hoyling, Larissa, Nair, Priya, Passer, Melissa, Reynolds, Claire, Saunders, Nicholas M, Saxena, Manoj K, and Thanakrishnan, Govindasamy
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- 2012
8. Prevalence of Patient Vigilance System management plans before and after rapid response system calls.
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Chau, Cindy, Cheung, Winston, Sahai, Vineta, Phillips, Kirrilee, Waite, Michelle, Jacobs, Rodney, and Mead, Lawrence
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CLINICAL deterioration , *AUDITING , *INTENSIVE care units , *RAPID response teams , *ACADEMIC medical centers , *MEDICAL protocols , *CRITICAL care medicine , *PATIENT safety , *EMERGENCY medicine - Abstract
The article introduces the Patient Vigilance System (PVS) to reduce rapid response system (RRS) calls and improve patient care planning, demonstrating that the PVS significantly increased the proportion of patients with clinical plans after RRS calls.
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- 2023
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9. People in intensive care with COVID‐19: demographic and clinical features during the first, second, and third pandemic waves in Australia.
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Begum, Husna, Neto, Ary S, Alliegro, Patricia, Broadley, Tessa, Trapani, Tony, Campbell, Lewis T, Cheng, Allen C, Cheung, Winston, Cooper, D James, Erickson, Simon J, French, Craig J, Litton, Edward, McAllister, Richard, Nichol, Alistair, Palermo, Annamaria, Plummer, Mark P, Rotherham, Hannah, Ramanan, Mahesh, Reddi, Benjamin, and Reynolds, Claire
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COVID-19 ,CRITICAL care medicine ,COMORBIDITY ,INTENSIVE care patients ,INTENSIVE care units - 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. [ABSTRACT FROM AUTHOR]
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- 2022
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10. Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19:The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial
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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
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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.
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- 2020
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11. Healthcare worker infections with the SARS-CoV-2 virus following the inception of an adult COVID-19 intensive care unit.
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Baukes, Allanah, Brannelly, Alison, Cheung, Winston, Cross, Rosalba, Gottlieb, Thomas, Gray, Timothy, Griffiths, Karina, Hunt, Rhiannon, Kol, Mark, Li, Ying, Mckew, Genevieve, Mendes, Anne, Shah, Asim, Skylas, Katina, Smith, Gemma, Wagh, Atul, and Wong, Helen
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CROSS infection prevention ,INTENSIVE care units ,COVID-19 ,IMMUNIZATION ,SICK people ,COVID-19 vaccines ,MEDICAL personnel ,DISEASE prevalence ,PERSONAL protective equipment ,NURSE-patient ratio ,ADULTS - Published
- 2022
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12. Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial
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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, 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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, and Carr-Knott, Lisa
- 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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