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1. Knowledge-Assisted Privacy Preserving in Semantic Communication

Author

Liu, Xuesong, Sun, Yao, Cheng, Runze, Xia, Le, Abumarshoud, Hanaa, Zhang, Lei, and Imran, Muhammad Ali

Subjects
Computer Science - Cryptography and Security
Abstract

Semantic communication (SC) offers promising advancements in data transmission efficiency and reliability by focusing on delivering true meaning rather than solely binary bits of messages. However, privacy concerns in SC might become outstanding. Eavesdroppers equipped with advanced semantic coding models and extensive knowledge could be capable of correctly decoding and reasoning sensitive semantics from just a few stolen bits. To this end, this article explores utilizing knowledge to enhance data privacy in SC networks. Specifically, we first identify the potential attacks in SC based on the analysis of knowledge. Then, we propose a knowledge-assisted privacy preserving SC framework, which consists of a data transmission layer for precisely encoding and decoding source messages, and a knowledge management layer responsible for injecting appropriate knowledge into the transmission pair. Moreover, we elaborate on the transceiver design in the proposed SC framework to explain how knowledge should be utilized properly. Finally, some challenges of the proposed SC framework are discussed to expedite the practical implementation.

Published
2024

2. Hybrid Semantic/Bit Communication Based Networking Problem Optimization

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Zhang, Lan, Zhang, Lei, and Imran, Muhammad Ali

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Information Theory, Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a novel and practical next-generation cellular network where two modes of semantic communication (SemCom) and conventional bit communication (BitCom) coexist, namely hybrid semantic/bit communication network (HSB-Net). Concretely, we first identify a unified performance metric of message throughput for both SemCom and BitCom links. Next, we comprehensively develop a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency. Combined with several practical constraints, we then formulate a joint optimization problem for UA, MS, and BA to maximize the overall message throughput of HSB-Net. Afterward, we propose an optimal resource management strategy by employing a Lagrange primal-dual method and devising a preference list-based heuristic algorithm. Finally, numerical results validate the performance superiority of our proposed strategy compared with different benchmarks., Comment: This paper has been accepted for publication and will be presented in 2024 IEEE Global Communications Conference (GlobeCom 2024). arXiv admin note: substantial text overlap with arXiv:2404.04162

Published
2024

3. Wireless Resource Optimization in Hybrid Semantic/Bit Communication Networks

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Zhang, Lan, and Imran, Muhammad Ali

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Systems and Control
Abstract

Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel and practical cellular network paradigm where two modes of SemCom and conventional bit communication (BitCom) coexist. Nevertheless, the involved wireless resource management becomes rather complicated and challenging, given the unique background knowledge matching and time-consuming semantic coding requirements in SemCom. To this end, this paper jointly investigates user association (UA), mode selection (MS), and bandwidth allocation (BA) problems in a hybrid semantic/bit communication network (HSB-Net). Concretely, we first identify a unified performance metric of message throughput for both SemCom and BitCom links. Next, we specially develop a knowledge matching-aware two-stage tandem packet queuing model and theoretically derive the average packet loss ratio and queuing latency. Combined with practical constraints, we then formulate a joint optimization problem for UA, MS, and BA to maximize the overall message throughput of HSB-Net. Afterward, we propose an optimal resource management strategy by utilizing a Lagrange primal-dual transformation method and a preference list-based heuristic algorithm with polynomial-time complexity. Numerical results not only demonstrate the accuracy of our analytical queuing model, but also validate the performance superiority of our proposed strategy compared with different benchmarks., Comment: This paper has been accepted for publication by the IEEE Transactions on Communications

Published
2024
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6. Knowledge Base Aware Semantic Communication in Vehicular Networks

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Ma, Kairong, Kang, Jiawen, and Imran, Muhammad Ali

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Networking and Internet Architecture
Abstract

Semantic communication (SemCom) has recently been considered a promising solution for the inevitable crisis of scarce communication resources. This trend stimulates us to explore the potential of applying SemCom to vehicular networks, which normally consume a tremendous amount of resources to achieve stringent requirements on high reliability and low latency. Unfortunately, the unique background knowledge matching mechanism in SemCom makes it challenging to realize efficient vehicle-to-vehicle service provisioning for multiple users at the same time. To this end, this paper identifies and jointly addresses two fundamental problems of knowledge base construction (KBC) and vehicle service pairing (VSP) inherently existing in SemCom-enabled vehicular networks. Concretely, we first derive the knowledge matching based queuing latency specific for semantic data packets, and then formulate a latency-minimization problem subject to several KBC and VSP related reliability constraints. Afterward, a SemCom-empowered Service Supplying Solution (S$^{\text{4}}$) is proposed along with the theoretical analysis of its optimality guarantee. Simulation results demonstrate the superiority of S$^{\text{4}}$ in terms of average queuing latency, semantic data packet throughput, and user knowledge preference satisfaction compared with two different benchmarks., Comment: This paper has been accepted for publication by 2023 IEEE International Conference on Communications (ICC 2023). arXiv admin note: substantial text overlap with arXiv:2302.11993

Published
2023

7. Generative AI for Semantic Communication: Architecture, Challenges, and Outlook

Author

Xia, Le, Sun, Yao, Liang, Chengsi, Zhang, Lei, Imran, Muhammad Ali, and Niyato, Dusit

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Image and Video Processing, Electrical Engineering and Systems Science - Signal Processing
Abstract

Semantic communication (SemCom) is expected to be a core paradigm in future communication networks, yielding significant benefits in terms of spectrum resource saving and information interaction efficiency. However, the existing SemCom structure is limited by the lack of context-reasoning ability and background knowledge provisioning, which, therefore, motivates us to seek the potential of incorporating generative artificial intelligence (GAI) technologies with SemCom. Recognizing GAI's powerful capability in automating and creating valuable, diverse, and personalized multimodal content, this article first highlights the principal characteristics of the combination of GAI and SemCom along with their pertinent benefits and challenges. To tackle these challenges, we further propose a novel GAI-integrated SemCom network (GAI-SCN) framework in a cloud-edge-mobile design. Specifically, by employing global and local GAI models, our GAI-SCN enables multimodal semantic content provisioning, semantic-level joint-source-channel coding, and AIGC acquisition to maximize the efficiency and reliability of semantic reasoning and resource utilization. Afterward, we present a detailed implementation workflow of GAI-SCN, followed by corresponding initial simulations for performance evaluation in comparison with two benchmarks. Finally, we discuss several open issues and offer feasible solutions to unlock the full potential of GAI-SCN., Comment: This magazine article has been accepted for publication by IEEE Wireless Communications

Published
2023

8. xURLLC-Aware Service Provisioning in Vehicular Networks: A Semantic Communication Perspective

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Feng, Daquan, Feng, Lei, and Imran, Muhammad Ali

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Semantic communication (SemCom), as an emerging paradigm focusing on meaning delivery, has recently been considered a promising solution for the inevitable crisis of scarce communication resources. This trend stimulates us to explore the potential of applying SemCom to wireless vehicular networks, which normally consume a tremendous amount of resources to meet stringent reliability and latency requirements. Unfortunately, the unique background knowledge matching mechanism in SemCom makes it challenging to simultaneously realize efficient service provisioning for multiple users in vehicle-to-vehicle networks. To this end, this paper identifies and jointly addresses two fundamental problems of knowledge base construction (KBC) and vehicle service pairing (VSP) inherently existing in SemCom-enabled vehicular networks in alignment with the next-generation ultra-reliable and low-latency communication (xURLLC) requirements. Concretely, we first derive the knowledge matching based queuing latency specific for semantic data packets, and then formulate a latency-minimization problem subject to several KBC and VSP related reliability constraints. Afterward, a SemCom-empowered Service Supplying Solution (S$^{\text{4}}$) is proposed along with the theoretical analysis of its optimality guarantee and computational complexity. Numerical results demonstrate the superiority of S$^{\text{4}}$ in terms of average queuing latency, semantic data packet throughput, user knowledge matching degree and knowledge preference satisfaction compared with two benchmarks., Comment: This paper has been accepted for publication by IEEE Transactions on Wireless Communications

Published
2023
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9. Joint User Association and Bandwidth Allocation in Semantic Communication Networks

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Li, Xiaoqian, and Imran, Muhammad Ali

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Information Theory
Abstract

Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient wireless resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this paper investigates SemCom from a networking perspective, where two fundamental problems of user association (UA) and bandwidth allocation (BA) are systematically addressed in the SC-Net. First, considering varying knowledge matching states between mobile users and associated base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we describe its distinctive semantic channel model from the semantic information theory perspective, whereby a concept of bit-rate-to-message-rate transformation is developed along with a new semantics-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we then formulate a joint STM-maximization problem of UA and BA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both scenarios demonstrate significant superiority and reliability of our solutions in the STM performance compared with two benchmarks., Comment: This paper has been accepted for publication by IEEE Transactions on Vehicular Technology

Published
2022
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10. WiserVR: Semantic Communication Enabled Wireless Virtual Reality Delivery

Author

Xia, Le, Sun, Yao, Liang, Chengsi, Feng, Daquan, Cheng, Runze, Yang, Yang, and Imran, Muhammad Ali

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract

Virtual reality (VR) over wireless is expected to be one of the killer applications in next-generation communication networks. Nevertheless, the huge data volume along with stringent requirements on latency and reliability under limited bandwidth resources makes untethered wireless VR delivery increasingly challenging. Such bottlenecks, therefore, motivate this work to seek the potential of using semantic communication, a new paradigm that promises to significantly ease the resource pressure, for efficient VR delivery. To this end, we propose a novel framework, namely WIreless SEmantic deliveRy for VR (WiserVR), for delivering consecutive 360{\deg} video frames to VR users. Specifically, deep learning-based multiple modules are well-devised for the transceiver in WiserVR to realize high-performance feature extraction and semantic recovery. Among them, we dedicatedly develop a concept of semantic location graph and leverage the joint-semantic-channel-coding method with knowledge sharing to not only substantially reduce communication latency, but also to guarantee adequate transmission reliability and resilience under various channel states. Moreover, implementation of WiserVR is presented, followed by corresponding initial simulations for performance evaluation compared with benchmarks. Finally, we discuss several open issues and offer feasible solutions to unlock the full potential of WiserVR., Comment: This magazine article has been accepted for publication by IEEE Wireless Communications

Published
2022
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11. Wireless Resource Management in Intelligent Semantic Communication Networks

Author

Xia, Le, Sun, Yao, Li, Xiaoqian, Feng, Gang, and Imran, Muhammad Ali

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract

The prosperity of artificial intelligence (AI) has laid a promising paradigm of communication system, i.e., intelligent semantic communication (ISC), where semantic contents, instead of traditional bit sequences, are coded by AI models for efficient communication. Due to the unique demand of background knowledge for semantic recovery, wireless resource management faces new challenges in ISC. In this paper, we address the user association (UA) and bandwidth allocation (BA) problems in an ISC-enabled heterogeneous network (ISC-HetNet). We first introduce the auxiliary knowledge base (KB) into the system model, and develop a new performance metric for the ISC-HetNet, named system throughput in message (STM). Joint optimization of UA and BA is then formulated with the aim of STM maximization subject to KB matching and wireless bandwidth constraints. To this end, we propose a two-stage solution, including a stochastic programming method in the first stage to obtain a deterministic objective with semantic confidence, and a heuristic algorithm in the second stage to reach the optimality of UA and BA. Numerical results show great superiority and reliability of our proposed solution on the STM performance when compared with two baseline algorithms., Comment: This work has been accepted for publication by 2022 IEEE International Conference on Computer Communications (INFOCOM)

Published
2022
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13. Smart and Secure CAV Networks Empowered by AI-Enabled Blockchain: The Next Frontier for Intelligent Safe Driving Assessment

Author

Xia, Le, Sun, Yao, Swash, Rafiq, Mohjazi, Lina, Zhang, Lei, and Imran, Muhammad Ali

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

Securing safe driving for connected and autonomous vehicles (CAVs) continues to be a widespread concern, despite various sophisticated functions delivered by artificial intelligence for in-vehicle devices. Diverse malicious network attacks are ubiquitous, along with the worldwide implementation of the Internet of Vehicles, which exposes a range of reliability and privacy threats for managing data in CAV networks. Combined with the fact that the capability of existing CAVs in handling intensive computation tasks is limited, this implies a need for designing an efficient assessment system to guarantee autonomous driving safety without compromising data security. In this article we propose a novel framework, namely Blockchain-enabled intElligent Safe-driving assessmenT (BEST), which offers a smart and reliable approach for conducting safe driving supervision while protecting vehicular information. Specifically, a promising solution that exploits a long short-term memory model is introduced to assess the safety level of the moving CAVs. Then we investigate how a distributed blockchain obtains adequate trustworthiness and robustness for CAV data by adopting a byzantine fault tolerance-based delegated proof-of-stake consensus mechanism. Simulation results demonstrate that our presented BEST gains better data credibility with a higher prediction accuracy for vehicular safety assessment when compared with existing schemes. Finally, we discuss several open challenges that need to be addressed in future CAV networks., Comment: This article has been accepted for publication by IEEE Network

Published
2021
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14. Intelligent Monitoring and Visualization System for High Building Nighttime Utilization Based on Image Processing.

Author

He, Yuanrong, Yu, Xianhui, Liang, Qihao, Yu, Peng, Xie, Zhiying, Xia, Le, and Qin, Minghang

Subjects
GEOGRAPHIC information systems, TALL buildings, IMAGE processing, CAMPUS safety, ENERGY consumption
Abstract

The rise of complex high-rise buildings has made building management increasingly challenging, especially the nighttime supervision of university laboratories. Idle occupation increases the risk of accidents and undermines campus sustainability. Effective occupancy detection is essential for optimizing campus building safety and energy efficiency. Environmental sensors for occupancy detection offer limited coverage and are costly, making them unsuitable for campuses. Surveillance cameras, as part of campus infrastructure, provide wide coverage. On this basis, we designed a detection algorithm that uses light brightness to assess nighttime building use. Experimental results showed that the algorithm achieves an average accuracy of 98.67%, enabling large-scale nighttime occupancy detection without the need for installing additional sensors, significantly improving the efficiency of campus building management. In addition, to address the limitations of indoor space representation in geographic information system (GIS) management models, this paper developed a comprehensive 3D GIS model based on a "building–floor–room" hierarchical structure, utilizing oblique photogrammetry and laser scanning technology. This study combined the detection results with real-world 3D data for visualization, providing a new perspective for the 3D spatiotemporal refinement of complex high-rise buildings, and providing a reference framework for the detection and analysis of other types of building environments. [ABSTRACT FROM AUTHOR]

Published
2024
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18. mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite–Phenotype Associations

Author

Xia, Le Chang, Guangyan Zhou, and Jianguo

Subjects
mGWAS, metabolomics, causal inference, two-sample Mendelian randomization, semantic triples
Abstract

Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn’s disease, as well as between glycine and coronary heart disease.

Published
2023
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19. Joint User Association and Bandwidth Allocation in Semantic Communication Networks

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Li, Xiaoqian, and Imran, Muhammad Ali

Abstract

Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient wireless resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this article investigates SemCom from a networking perspective, where two fundamental problems of user association (UA) and bandwidth allocation (BA) are systematically addressed in the SC-Net. First, considering varying knowledge matching states between mobile users and associated base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we describe its distinctive semantic channel model from the semantic information theory perspective, whereby a concept of bit-rate-to-message-rate transformation is developed along with a new semantics-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we then formulate a joint STM-maximization problem of UA and BA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both scenarios demonstrate significant superiority and reliability of our solutions in the STM performance compared with two benchmarks.

Published
2024
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22. Smart and Secure CAV Networks Empowered by AI-Enabled Blockchain: The Next Frontier for Intelligent Safe Driving Assessment

Author

Xia, Le, Sun, Yao, Swash, Rafiq, Mohjazi, Lina, Zhang, Lei, and Imran, Muhammad Ali

Subjects
Networking and Internet Architecture (cs.NI), FOS: Computer and information sciences, safety, Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Networks and Communications, blockchains, artificial intelligence, Computer Science - Networking and Internet Architecture, Artificial Intelligence (cs.AI), servers, Hardware and Architecture, peer-to-peer computing, logic gates, task analysis, Cryptography and Security (cs.CR), Software, Information Systems
Abstract

Securing safe driving for connected and autonomous vehicles (CAVs) continues to be a widespread concern, despite various sophisticated functions delivered by artificial intelligence for in-vehicle devices. Diverse malicious network attacks are ubiquitous, along with the worldwide implementation of the Internet of Vehicles, which exposes a range of reliability and privacy threats for managing data in CAV networks. Combined with the fact that the capability of existing CAVs in handling intensive computation tasks is limited, this implies a need for designing an efficient assessment system to guarantee autonomous driving safety without compromising data security. In this article we propose a novel framework, namely Blockchain-enabled intElligent Safe-driving assessmenT (BEST), which offers a smart and reliable approach for conducting safe driving supervision while protecting vehicular information. Specifically, a promising solution that exploits a long short-term memory model is introduced to assess the safety level of the moving CAVs. Then we investigate how a distributed blockchain obtains adequate trustworthiness and robustness for CAV data by adopting a byzantine fault tolerance-based delegated proof-of-stake consensus mechanism. Simulation results demonstrate that our presented BEST gains better data credibility with a higher prediction accuracy for vehicular safety assessment when compared with existing schemes. Finally, we discuss several open challenges that need to be addressed in future CAV networks., This article has been accepted for publication by IEEE Network. Copyright may be transferred without notice, after which this version may no longer be accessible

Published
2022
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23. Wireless Semantic Communication: A Networking Perspective

Author

Xia, Le, Sun, Yao, Niyato, Dusit, Li, Xiaoqian, and Imran, Muhammad Ali

Subjects
FOS: Computer and information sciences, Information Theory (cs.IT), Computer Science - Information Theory, FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control
Abstract

Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient wireless resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this paper investigates SemCom from a networking perspective, where two fundamental problems of user association (UA) and bandwidth allocation (BA) are systematically addressed in the SC-Net. First, considering varying knowledge matching states between mobile users and associated base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we describe its distinctive semantic channel model from the semantic information theory perspective, whereby a concept of bit-rate-to-message-rate transformation is developed along with a new semantics-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we then formulate a joint STM-maximization problem of UA and BA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both scenarios demonstrate significant superiority and reliability of our solutions in the STM performance compared with two benchmarks., This paper has been submitted to IEEE Transactions on Vehicular Technology for peer review

Published
2022

25. A Privacy-preserved D2D Caching Scheme Underpinned by Blockchain-enabled Federated Learning

Author

Cheng, Runze, Sun, Yao, Liu, Yijing, Xia, Le, Sun, Sanshan, and Imran, Muhammad Ali

Abstract

Cache-enabled device-to-device (D2D) communication has been widely deemed as a promising approach to tackle the unprecedented growth of wireless traffic demands. Recently, tremendous efforts have been put into designing an efficient caching policy to provide users better quality of service. However, public concerns of data privacy still remain in D2D cache sharing networks, which thus arises an urgent need for a privacy-preserved caching scheme. In this study, we propose a double-layer blockchain-based federated learning (DBFL) scheme with the aim of minimizing the download latency for all users in a privacy-preserving manner. Specifically, in the sublayer, the devices within the same coverage area run a federated learning (FL) to train the caching scheme model for each area separately without exchange of local data. The model parameters for each area are recorded in sublayer chains with Raft consensus mechanism. Meanwhile, in the main layer, a mainchain based on practical Byzantine fault tolerance (PBFT) mechanism is used to resist faults and attacks, thus securing the reliability of FL updates. Only the reliable area models authorized by the mainchain are utilized to update the global model in the main layer. Numerical results show the convergence, as well as the gain of download latency of the proposed DBFL caching scheme when compared with several traditional schemes.

Published
2021

28. Comprehensive test stand for high-intensity cyclotron development

Author

Zhang, TianJue, Li, ZhenGuo, Chu, ChengJie, Xing, JianSheng, Guan, FengPing, Zhong, JunQing, Ji, Bin, Ge, Tao, Yin, ZhiGuo, Hou, ShiGang, Pan, GaoFeng, Yao, HongJuan, Lu, YinLong, Wang, ZhenHui, Wu, LongCheng, Lin, Jun, Jia, XianLu, Wei, SuMin, Wen, LiPeng, Wang, Feng, Xia, Le, Cai, HongRu, Xie, HuaiDong, Chen, RongFan, Zhang, Yan, Zhang, SuPing, Liu, GengShou, Zou, Jian, An, ShiZhong, Yang, JianJun, Bi, YuanJie, and Yang, Fang

Published
2011
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29. 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
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33. Flavone from Zhongjiefeng ( Herba Sarcandrae Glabrae ) inhibits platelet apoptosis in immune-induced bone marrow failure through mitochondrial pathway

Author

Zhang Aiping, Luo Mei-hong, Cui Lele, Xia Le-Min, Jiang Yi-Ling, and Zheng Qin

Subjects
0301 basic medicine, biology, business.industry, Cytochrome c, chemistry.chemical_element, General Medicine, Phosphatidylserine, Calcium, Pharmacology, Mitochondrion, 03 medical and health sciences, chemistry.chemical_compound, 030104 developmental biology, 0302 clinical medicine, Immune system, chemistry, Apoptosis, 030220 oncology & carcinogenesis, biology.protein, Medicine, Platelet, business, Caspase
Abstract

Objective To investigate the effect of Flavone from Zhongjiefeng (Herba Sarcandrae Glabrae) on the platelet number in immune-induced bone marrow failure (BMF) and its mechanism of mitochondrial apoptotic pathway. Methods Immune-induced BMF model, established in mice, was randomly divided into four groups: normal control group without BMF, BMF control group, cyclosporine (CSA) group and flavone group (n = 10 in each group). Mice were given 0.027 g/kg cyclosporine or 0.2 g/kg flavone lavage daily in either the cyclosporine or flavone group respectively. Platelet count, mitochondrial transmembrane potential (ΔΨ), cytochrome C (Cyt C), phosphatidylserine (PS), changes of calcium ion (Ca2+), and protein expression of mitochondrial apoptotic pathway including B-cell lymphoma-2 (bcl-2) Homologous Antagonist-Killer Protein (Bak), bcl-2-associated X protein (Bax), caspase-3, caspase-8, and caspase-9 were examined and compared. Results Compared with the normal control group, the BMF group had significantly lower levels of platelet count, ΔΨ, and expressions of caspase family proteins as well as higher levels of Cyt C, PS, Ca2+, and expressions of Bak and Bax (all P Conclusion Flavone from Zhongjiefeng (Herba Sarcandrae Glabrae) significantly increases the platelet number and prevents its apoptosis through mitochondrial pathway.

Published
2017
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35. Bilateral swap agreement and Renminbi settlement in cross-border trade

Author

Song, Ke and Xia, Le

Subjects
SWIFT, F36, Bilateral Swap Agreement, ddc:330, F33, RMB, Cross-Border Trade, F42
Abstract

This research empirically examines the impact of China's Renminbi (RMB) bilateral swap agree-ments (BSAs) on the usage of the currency in cross-border trade transactions. By using a unique dataset from SWIFT including cross-border settlement messages of 91 countries/regions between October 2010 and November 2015, we confirm that the signing of a RMB BSA helps to increase the number, the value and the proportion of RMB settlement in cross-border trade. Our results are robust with respect to the choice of different models, including multi-level mixed model, two-stage regression model, and difference-in-difference model. In addition to justifying the effectiveness of China's BSA-signing strategy to promote the RMB usage in trade settlement, our results clarify that the signing of those RMB BSAs is not purely for China's political ends as some scholars claim.

Published
2019

40. Pretreatment quality of life as a predictor of survival for patients with nasopharyngeal carcinoma treated with IMRT

Author

Guo, Shan-Shan, primary, Hu, Wen, additional, Chen, Qiu-Yan, additional, Li, Jian-Mei, additional, Zhu, Shi-Heng, additional, He, Yan, additional, Li, Jia-Wen, additional, Xia, Le, additional, Ji, Lu, additional, Lin, Cui-Ying, additional, Liu, Li-Ting, additional, Tang, Lin-Quan, additional, Guo, Ling, additional, Mo, Hao-Yuan, additional, Zhao, Chong, additional, Guo, Xiang, additional, Cao, Ka-Jia, additional, Qian, Chao-Nan, additional, Zeng, Mu-Sheng, additional, Hong, Ming-Huang, additional, Shao, Jian-Yong, additional, Sun, Ying, additional, Ma, Jun, additional, Fan, Yu-Ying, additional, and Mai, Hai-Qiang, additional

Published
2018
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43. China’s RMB bilateral swap agreements: What explains the choice of countries?

Author

Garcia-Herrero , Alicia and Xia, Le

Subjects
RMB internationalization, bilateral swap agreements, jel:F42, jel:F36, jel:F33
Abstract

This paper analyzes empirically what determines the choice of countries signing an RMB-denominated Bilateral Swap Agreement (BSA) with China. The gravity motif is predominant (both in terms of country size and distance from China) but so is the trade motif, in terms of both exports to China and the existence of an FTA with China. Institutional soundness also matters since countries with better government and less corruption are more likely to sign an RMB-denominated BSA. This contravenes the view that China has used RMB BSAs as a soft power tool in more corrupted countries. However, the fact that China has a preference for countries with a default history and a closed capital account calls for caution.

Published
2013

44. China's RMB bilateral swap agreements: What explains the choice of countries?

Author

Garcia-Herrero, Alicia and Xia, Le

Subjects
bilateral swap agreements, F36, ddc:330, RMB internationalization, F33, F42
Abstract

This paper analyzes empirically what determines the choice of countries signing an RMB-denominated Bilateral Swap Agreement (BSA) with China. The gravity motif is predominant (both in terms of country size and distance from China) but so is the trade motif, in terms of both exports to China and the existence of an FTA with China. Institutional soundness also matters since countries with better government and less corruption are more likely to sign an RMB-denominated BSA. This contravenes the view that China has used RMB BSAs as a soft power tool in more corrupted countries. However, the fact that China has a preference for countries with a default history and a closed capital account calls for caution.

Published
2013

46. Single and cooperative bioleaching of sphalerite by two kinds of bacteria: Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans.

Author

Xia Le-Xian, Geng Mei-Mei, Li Ban-Mei, Liu Jian-She, Qiu Guan-Zhou., Xiao Li, Zeng Jia, Xia Le-Xian, Geng Mei-Mei, Li Ban-Mei, Liu Jian-She, Qiu Guan-Zhou., Xiao Li, and Zeng Jia

Abstract

The results of investigations into the bioleaching of sphalerite showed that the Zn leaching rate was higher in the mixed culture than in the single cultures and in a sterile control. The two bacteria perform different functions and play a cooperative role during the leaching process. The role of Acidithiobacillus ferrooxidans is to oxidise Fe2+ to Fe3+ and to maintain a high redox potential. Addition of an appropriate concentration of ferric iron to the leaching system was beneficial for Zn dissolution. In the absence of Acidithiobacillus thiooxidans, elemental S layers formed on the mineral surface during the dissolution of Zn and prevented continuous leaching. The presence of Acidithiobacillus thiooxidans prevented passivation and resulted in continuation of the bioleaching process. Protons from the bacterial oxidation of the elemental S layers also accelerated the leaching of Zn., The results of investigations into the bioleaching of sphalerite showed that the Zn leaching rate was higher in the mixed culture than in the single cultures and in a sterile control. The two bacteria perform different functions and play a cooperative role during the leaching process. The role of Acidithiobacillus ferrooxidans is to oxidise Fe2+ to Fe3+ and to maintain a high redox potential. Addition of an appropriate concentration of ferric iron to the leaching system was beneficial for Zn dissolution. In the absence of Acidithiobacillus thiooxidans, elemental S layers formed on the mineral surface during the dissolution of Zn and prevented continuous leaching. The presence of Acidithiobacillus thiooxidans prevented passivation and resulted in continuation of the bioleaching process. Protons from the bacterial oxidation of the elemental S layers also accelerated the leaching of Zn.

Published
2008

49. Sulphur/iron oxidation activity of three typical bioleaching bacteria and sulphur speciation in bioleaching of chalcopyrite.

Author

Peng An-An, Nie Zhen-Yuan, Tang Lu, Xia Jin-Lan, Xia Le-Xian, Zhao Xiao-Juan, Zhu Wei., Peng An-An, Nie Zhen-Yuan, Tang Lu, Xia Jin-Lan, Xia Le-Xian, Zhao Xiao-Juan, and Zhu Wei.

Abstract

The sulphur/iron oxidation activities were investigated of Acidithiobacillus ferrooxidans, Leptospirillum ferriphilum and Acidithiobacillus thiooxidans, and the sulphur speciation on the surface of chalcopyrite during leaching using pure and mixed bacteria was studied. The chalcopyrite dissolution rate was higher at redox potentials of less than 400 mV vs. SCE and decreased at higher potentials. Mixed bacterial cultures showed higher sulphur/iron oxidation activities. The mixed cultures promoted the formation of chalcocite and inhibited the formation of a passivation layer containing sulphur and jarosite., The sulphur/iron oxidation activities were investigated of Acidithiobacillus ferrooxidans, Leptospirillum ferriphilum and Acidithiobacillus thiooxidans, and the sulphur speciation on the surface of chalcopyrite during leaching using pure and mixed bacteria was studied. The chalcopyrite dissolution rate was higher at redox potentials of less than 400 mV vs. SCE and decreased at higher potentials. Mixed bacterial cultures showed higher sulphur/iron oxidation activities. The mixed cultures promoted the formation of chalcocite and inhibited the formation of a passivation layer containing sulphur and jarosite.

50. Effect of hydrocortisone on mortality and organ support in patients with severe COVID-19

Author

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

Subjects
[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, General Medicine, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Writing Committee for the REMAP-CAP Investigators, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.TOX] Life Sciences [q-bio]/Toxicology, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.TOX]Life Sciences [q-bio]/Toxicology, General & Internal Medicine, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, 11 Medical and Health Sciences
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.

Published
2020
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