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Baruch, Joaquin, Rojek, Amanda, Kartsonaki, Christiana, Vijayaraghavan, Bharath K. T.; Gonçalves, Bronner P.; Pritchard, Mark G.; Merson, Laura, Dunning, Jake, Hall, Matthew, Sigfrid, Louise, Citarella, Barbara W.; Murthy, Srinivas, Yeabah, Trokon O.; Olliaro, Piero, Abbas, Ali, Abdukahil, Sheryl Ann, Abdulkadir, Nurul Najmee, Abe, Ryuzo, Abel, Laurent, Absil, Lara, Acharya, Subhash, Acker, Andrew, Adam, Elisabeth, Adrião, Diana, Al Ageel, Saleh, Ahmed, Shakeel, Ainscough, Kate, Airlangga, Eka, Aisa, Tharwat, Hssain, Ali Ait, Tamlihat, Younes Ait, Akimoto, Takako, Akmal, Ernita, Al Qasim, Eman, Alalqam, Razi, Alberti, Angela, Al‐dabbous, Tala, Alegesan, Senthilkumar, Alegre, Cynthia, Alessi, Marta, Alex, Beatrice, Alexandre, Kévin, Al‐Fares, Abdulrahman, Alfoudri, Huda, Ali, Imran, Ali, Adam, Shah, Naseem Ali, Alidjnou, Kazali Enagnon, Aliudin, Jeffrey, Alkhafajee, Qabas, Allavena, Clotilde, Allou, Nathalie, Altaf, Aneela, Alves, João, Alves, Rita, Alves, João Melo, Amaral, Maria, Amira, Nur, Ampaw, Phoebe, Andini, Roberto, Andréjak, Claire, Angheben, Andrea, Angoulvant, François, Ansart, Séverine, Anthonidass, Sivanesen, Antonelli, Massimo, de Brito, Carlos Alexandre Antunes, Apriyana, Ardiyan, Arabi, Yaseen, Aragao, Irene, Araujo, Carolline, Arcadipane, Antonio, Archambault, Patrick, Arenz, Lukas, Arlet, Jean‐Benoît, Arora, Lovkesh, Arora, Rakesh, Artaud‐Macari, Elise, Aryal, Diptesh, Asensio, Angel, Ashraf, Muhammad, Asif, Namra, Asim, Mohammad, Assie, Jean Baptiste, Asyraf, Amirul, Atique, Anika, Attanyake, A. M. Udara Lakshan, Auchabie, Johann, Aumaitre, Hugues, Auvet, Adrien, Axelsen, Eyvind W.; Azemar, Laurène, Azoulay, Cecile, Bach, Benjamin, Bachelet, Delphine, Badr, Claudine, Bævre‐Jensen, Roar, Baig, Nadia, Baillie, J. Kenneth, Baird, J. Kevin, Bak, Erica, Bakakos, Agamemnon, Bakar, Nazreen Abu, Bal, Andriy, Balakrishnan, Mohanaprasanth, Balan, Valeria, Bani‐Sadr, Firouzé, Barbalho, Renata, Barbosa, Nicholas Yuri, Barclay, Wendy S.; Barnett, Saef Umar, Barnikel, Michaela, Barrasa, Helena, Barrelet, Audrey, Barrigoto, Cleide, Bartoli, Marie, Baruch, Joaquín, Bashir, Mustehan, Basmaci, Romain, Basri, Muhammad Fadhli Hassin, Battaglini, Denise, Bauer, Jules, Rincon, Diego Fernando Bautista, Dow, Denisse Bazan, Beane, Abigail, Bedossa, Alexandra, Bee, Ker Hong, Begum, Husna, Behilill, Sylvie, Beishuizen, Albertus, Beljantsev, Aleksandr, Bellemare, David, Beltrame, Anna, Beltrão, Beatriz Amorim, Beluze, Marine, Benech, Nicolas, Benjiman, Lionel Eric, Benkerrou, Dehbia, Bennett, Suzanne, Bento, Luís, Berdal, Jan‐Erik, Bergeaud, Delphine, Bergin, Hazel, Sobrino, José Luis Bernal, Bertoli, Giulia, Bertolino, Lorenzo, Bessis, Simon, Bevilcaqua, Sybille, Bezulier, Karine, Bhatt, Amar, Bhavsar, Krishna, Bianco, Claudia, Bidin, Farah Nadiah, Singh, Moirangthem Bikram, Humaid, Felwa Bin, Kamarudin, Mohd Nazlin Bin, Bissuel, François, Bitker, Laurent, Bitton, Jonathan, Blanco‐Schweizer, Pablo, Blier, Catherine, Bloos, Frank, Blot, Mathieu, Boccia, Filomena, Bodenes, Laetitia, Bogaarts, Alice, Bogaert, Debby, Boivin, Anne‐Hélène, Bolze, Pierre‐Adrien, Bompart, François, Bonfasius, Aurelius, Borges, Diogo, Borie, Raphaël, Bosse, Hans Martin, Botelho‐Nevers, Elisabeth, Bouadma, Lila, Bouchaud, Olivier, Bouchez, Sabelline, Bouhmani, Dounia, Bouhour, Damien, Bouiller, Kévin, Bouillet, Laurence, Bouisse, Camile, Boureau, Anne‐Sophie, Bourke, John, Bouscambert, Maude, Bousquet, Aurore, Bouziotis, Jason, Boxma, Bianca, Boyer‐Besseyre, Marielle, Boylan, Maria, Bozza, Fernando Augusto, Braconnier, Axelle, Braga, Cynthia, Brandenburger, Timo, Monteiro, Filipa Brás, Brazzi, Luca, Breen, Patrick, Breen, Dorothy, Breen, Patrick, Brickell, Kathy, Browne, Shaunagh, Browne, Alex, Brozzi, Nicolas, Brunvoll, Sonja Hjellegjerde, Brusse‐Keizer, Marjolein, Buchtele, Nina, Buesaquillo, Christian, Bugaeva, Polina, Buisson, Marielle, Buonsenso, Danilo, Burhan, Erlina, Burrell, Aidan, Bustos, Ingrid G.; Butnaru, Denis, Cabie, André, Cabral, Susana, Caceres, Eder, Cadoz, Cyril, Calligy, Kate, Calvache, Jose Andres, Camões, João, Campana, Valentine, Campbell, Paul, Campisi, Josie, Canepa, Cecilia, Cantero, Mireia, Caraux‐Paz, Pauline, Cárcel, Sheila, Cardellino, Chiara Simona, Cardoso, Sofia, Cardoso, Filipe, Cardoso, Filipa, Cardoso, Nelson, Carelli, Simone, Carlier, Nicolas, Carmoi, Thierry, Carney, Gayle, Carqueja, Inês, Carret, Marie‐Christine, Carrier, François Martin, Carroll, Ida, Carson, Gail, Casanova, Maire‐Laure, Cascão, Mariana, Casey, Siobhan, Casimiro, José, Cassandra, Bailey, Castañeda, Silvia, Castanheira, Nidyanara, Castor‐Alexandre, Guylaine, Castrillón, Henry, Castro, Ivo, Catarino, Ana, Catherine, François‐Xavier, Cattaneo, Paolo, Cavalin, Roberta, Cavalli, Giulio Giovanni, Cavayas, Alexandros, Ceccato, Adrian, Cervantes‐Gonzalez, Minerva, Chair, Anissa, Chakveatze, Catherine, Chan, Adrienne, Chand, Meera, Auger, Christelle Chantalat, Chapplain, Jean‐Marc, Chas, Julie, Chatterjee, Allegra, Chaudry, Mobin, Iñiguez, Jonathan Samuel Chávez, Chen, Anjellica, Chen, Yih‐Sharng, Cheng, Matthew Pellan, Cheret, Antoine, Chiarabini, Thibault, Chica, Julian, Chidambaram, Suresh Kumar, Tho, Leong Chin, Chirouze, Catherine, Chiumello, Davide, Cho, Sung‐Min, Cholley, Bernard, Chopin, Marie‐Charlotte, Chow, Ting Soo, Chow, Yock Ping, Chua, Jonathan, Chua, Hiu Jian, Cidade, Jose Pedro, Herreros, José Miguel Cisneros, Citarella, Barbara Wanjiru, Ciullo, Anna, Clarke, Jennifer, Clarke, Emma, Granado, Rolando Claure‐Del, Clohisey, Sara, Cobb, Perren J.; Codan, Cassidy, Cody, Caitriona, Coelho, Alexandra, Coles, Megan, Colin, Gwenhaël, Collins, Michael, Colombo, Sebastiano Maria, Combs, Pamela, Connor, Marie, Conrad, Anne, Contreras, Sofía, Conway, Elaine, Cooke, Graham S.; Copland, Mary, Cordel, Hugues, Corley, Amanda, Cornelis, Sabine, Cornet, Alexander Daniel, Corpuz, Arianne Joy, Cortegiani, Andrea, Corvaisier, Grégory, Costigan, Emma, Couffignal, Camille, Couffin‐Cadiergues, Sandrine, Courtois, Roxane, Cousse, Stéphanie, Cregan, Rachel, Croonen, Sabine, Crowl, Gloria, Crump, Jonathan, Cruz, Claudina, Bermúdez, Juan Luis Cruz, Rojo, Jaime Cruz, Csete, Marc, Cullen, Ailbhe, Cummings, Matthew, Curley, Gerard, Curlier, Elodie, Curran, Colleen, Custodio, Paula, da Silva Filipe, Ana, Da Silveira, Charlene, Dabaliz, Al‐Awwab, Dagens, Andrew, Dahl, John Arne, Dahly, Darren, Dalton, Heidi, Dalton, Jo, Daly, Seamus, Daneman, Nick, Daniel, Corinne, Dankwa, Emmanuelle A.; Dantas, Jorge, D'Aragon, Frédérick, de Loughry, Gillian, de Mendoza, Diego, De Montmollin, Etienne, de Oliveira França, Rafael Freitas, de Pinho Oliveira, Ana Isabel, De Rosa, Rosanna, De Rose, Cristina, de Silva, Thushan, de Vries, Peter, Deacon, Jillian, Dean, David, Debard, Alexa, Debray, Marie‐Pierre, DeCastro, Nathalie, Dechert, William, Deconninck, Lauren, Decours, Romain, Defous, Eve, Delacroix, Isabelle, Delaveuve, Eric, Delavigne, Karen, Delfos, Nathalie M.; Deligiannis, Ionna, Dell'Amore, Andrea, Delmas, Christelle, Delobel, Pierre, Delsing, Corine, Demonchy, Elisa, Denis, Emmanuelle, Deplanque, Dominique, Depuydt, Pieter, Desai, Mehul, Descamps, Diane, Desvallées, Mathilde, Dewayanti, Santi, Dhanger, Pathik, Diallo, Alpha, Diamantis, Sylvain, Dias, André, Diaz, Juan Jose, Diaz, Priscila, Diaz, Rodrigo, Didier, Kévin, Diehl, Jean‐Luc, Dieperink, Wim, Dimet, Jérôme, Dinot, Vincent, Diop, Fara, Diouf, Alphonsine, Dishon, Yael, Djossou, Félix, Docherty, Annemarie B.; Doherty, Helen, Dondorp, Arjen M.; Donnelly, Maria, Donnelly, Christl A.; Donohue, Sean, Donohue, Yoann, Donohue, Chloe, Doran, Peter, Dorival, Céline, D'Ortenzio, Eric, Douglas, James Joshua, Douma, Renee, Dournon, Nathalie, Downer, Triona, Downey, Joanne, Downing, Mark, Drake, Tom, Driscoll, Aoife, Dryden, Murray, Fonseca, Claudio Duarte, Dubee, Vincent, Dubos, François, Ducancelle, Alexandre, Duculan, Toni, Dudman, Susanne, Duggal, Abhijit, Dunand, Paul, Dunning, Jake, Duplaix, Mathilde, Durante‐Mangoni, Emanuele, Durham, Lucian, Dussol, Bertrand, Duthoit, Juliette, Duval, Xavier, Dyrhol‐Riise, Anne Margarita, Ean, Sim Choon, Echeverria‐Villalobos, Marco, Egan, Siobhan, Eggesbø, Linn Margrete, Eira, Carla, El Sanharawi, Mohammed, Elapavaluru, Subbarao, Elharrar, Brigitte, Ellerbroek, Jacobien, Ellingjord‐Dale, Merete, Eloy, Philippine, Elshazly, Tarek, Elyazar, Iqbal, Enderle, Isabelle, Endo, Tomoyuki, Eng, Chan Chee, Engelmann, Ilka, Enouf, Vincent, Epaulard, Olivier, Escher, Martina, Esperatti, Mariano, Esperou, Hélène, Esposito‐Farese, Marina, Estevão, João, Etienne, Manuel, Ettalhaoui, Nadia, Everding, Anna Greti, Evers, Mirjam, Fabre, Marc, Fabre, Isabelle, Faheem, Amna, Fahy, Arabella, Fairfield, Cameron J.; Fakar, Zul, Fareed, Komal, Faria, Pedro, Farooq, Ahmed, Fateena, Hanan, Fatoni, Arie Zainul, Faure, Karine, Favory, Raphaël, Fayed, Mohamed, Feely, Niamh, Feeney, Laura, Fernandes, Jorge, Fernandes, Marília Andreia, Fernandes, Susana, Ferrand, François‐Xavier, Devouge, Eglantine Ferrand, Ferrão, Joana, Ferraz, Mário, Ferreira, Sílvia, Ferreira, Isabel, Ferreira, Benigno, Ferrer‐Roca, Ricard, Ferriere, Nicolas, Ficko, Céline, Figueiredo‐Mello, Claudia, Finlayson, William, Fiorda, Juan, Flament, Thomas, Flateau, Clara, Fletcher, Tom, Florio, Letizia Lucia, Flynn, Deirdre, Foley, Claire, Foley, Jean, Fomin, Victor, Fonseca, Tatiana, Fontela, Patricia, Forsyth, Simon, Foster, Denise, Foti, Giuseppe, Fourn, Erwan, Fowler, Robert A.; Fraher, Marianne, Franch‐Llasat, Diego, Fraser, John F.; Fraser, Christophe, Freire, Marcela Vieira, Ribeiro, Ana Freitas, Friedrich, Caren, Fry, Stéphanie, Fuentes, Nora, Fukuda, Masahiro, Argin, G.; Gaborieau, Valérie, Gaci, Rostane, Gagliardi, Massimo, Gagnard, Jean‐Charles, Gagneux‐Brunon, Amandine, Gaião, Sérgio, Skeie, Linda Gail, Gallagher, Phil, Gamble, Carrol, Gani, Yasmin, Garan, Arthur, Garcia, Rebekha, Barrio, Noelia García, Garcia‐Diaz, Julia, Garcia‐Gallo, Esteban, Garimella, Navya, Garot, Denis, Garrait, Valérie, Gauli, Basanta, Gault, Nathalie, Gavin, Aisling, Gavrylov, Anatoliy, Gaymard, Alexandre, Gebauer, Johannes, Geraud, Eva, Morlaes, Louis Gerbaud, Germano, Nuno, Ghisulal, Praveen Kumar, Ghosn, Jade, Giani, Marco, Gibson, Jess, Gigante, Tristan, Gilg, Morgane, Gilroy, Elaine, Giordano, Guillermo, Girvan, Michelle, Gissot, Valérie, Glikman, Daniel, Glybochko, Petr, Gnall, Eric, Goco, Geraldine, Goehringer, François, Goepel, Siri, Goffard, Jean‐Christophe, Goh, Jin Yi, Golob, Jonathan, Gomez, Kyle, Gómez‐Junyent, Joan, Gominet, Marie, Gonçalves, Bronner P.; Gonzalez, Alicia, Gordon, Patricia, Gorenne, Isabelle, Goubert, Laure, Goujard, Cécile, Goulenok, Tiphaine, Grable, Margarite, Graf, Jeronimo, Grandin, Edward Wilson, Granier, Pascal, Grasselli, Giacomo, Green, Christopher A.; Greene, Courtney, Greenhalf, William, Greffe, Segolène, Grieco, Domenico Luca, Griffee, Matthew, Griffiths, Fiona, Grigoras, Ioana, Groenendijk, Albert, Lordemann, Anja Grosse, Gruner, Heidi, Gu, Yusing, Guedj, Jérémie, Guego, Martin, Guellec, Dewi, Guerguerian, Anne‐Marie, Guerreiro, Daniela, Guery, Romain, Guillaumot, Anne, Guilleminault, Laurent, Guimarães de Castro, Maisa, Guimard, Thomas, Haalboom, Marieke, Haber, Daniel, Habraken, Hannah, Hachemi, Ali, Hackmann, Amy, Hadri, Nadir, Haidri, Fakhir, Hakak, Sheeba, Hall, Adam, Hall, Matthew, Halpin, Sophie, Hameed, Jawad, Hamer, Ansley, Hamers, Raph L.; Hamidfar, Rebecca, Hammarström, Bato, Hammond, Terese, Han, Lim Yuen, Haniffa, Rashan, Hao, Kok Wei, Hardwick, Hayley, Harrison, Ewen M.; Harrison, Janet, Harrison, Samuel Bernard Ekow, Hartman, Alan, Hasan, Mohd Shahnaz, Hashmi, Junaid, Hayat, Muhammad, Hayes, Ailbhe, Hays, Leanne, Heerman, Jan, Heggelund, Lars, Hendry, Ross, Hennessy, Martina, Henriquez‐Trujillo, Aquiles, Hentzien, Maxime, Hernandez‐Montfort, Jaime, Hershey, Andrew, Hesstvedt, Liv, Hidayah, Astarini, Higgins, Eibhilin, Higgins, Dawn, Higgins, Rupert, Hinchion, Rita, Hinton, Samuel, Hiraiwa, Hiroaki, Hirkani, Haider, Hitoto, Hikombo, Ho, Yi Bin, Ho, Antonia, Hoctin, Alexandre, Hoffmann, Isabelle, Hoh, Wei Han, Hoiting, Oscar, Holt, Rebecca, Holter, Jan Cato, Horby, Peter, Horcajada, Juan Pablo, Hoshino, Koji, Houas, Ikram, Hough, Catherine L.; Houltham, Stuart, Hsu, Jimmy Ming‐Yang, Hulot, Jean‐Sébastien, Huo, Stella, Hurd, Abby, Hussain, Iqbal, Ijaz, Samreen, Illes, Hajnal‐Gabriela, Imbert, Patrick, Imran, Mohammad, Sikander, Rana Imran, Imtiaz, Aftab, Inácio, Hugo, Dominguez, Carmen Infante, Ing, Yun Sii, Iosifidis, Elias, Ippolito, Mariachiara, Isgett, Sarah, Isidoro, Tiago, Ismail, Nadiah, Isnard, Margaux, Istre, Mette Stausland, Itai, Junji, Ivulich, Daniel, Jaafar, Danielle, Jaafoura, Salma, Jabot, Julien, Jackson, Clare, Jamieson, Nina, Jaquet, Pierre, Jaud‐Fischer, Coline, Jaureguiberry, Stéphane, Jaworsky, Denise, Jego, Florence, Jelani, Anilawati Mat, Jenum, Synne, Jimbo‐Sotomayor, Ruth, Joe, Ong Yiaw, Jorge García, Ruth N.; Jørgensen, Silje Bakken, Joseph, Cédric, Joseph, Mark, Joshi, Swosti, Jourdain, Mercé, Jouvet, Philippe, Jung, Hanna, Jung, Anna, Juzar, Dafsah, Kafif, Ouifiya, Kaguelidou, Florentia, Kaisbain, Neerusha, Kaleesvran, Thavamany, Kali, Sabina, Kalicinska, Alina, Kalleberg, Karl Trygve, Kalomoiri, Smaragdi, Kamaluddin, Muhammad Aisar Ayadi, Kamaruddin, Zul Amali Che, Kamarudin, Nadiah, Kamineni, Kavita, Kandamby, Darshana Hewa, Kandel, Chris, Kang, Kong Yeow, Kanwal, Darakhshan, Karpayah, Pratap, Kartsonaki, Christiana, Kasugai, Daisuke, Kataria, Anant, Katz, Kevin, Kaur, Aasmine, Kay, Christy, Keane, Hannah, Keating, Seán, Kedia, Pulak, Kelly, Claire, Kelly, Yvelynne, Kelly, Andrea, Kelly, Niamh, Kelly, Aoife, Kelly, Sadie, Kelsey, Maeve, Kennedy, Ryan, Kennon, Kalynn, Kernan, Maeve, Kerroumi, Younes, Keshav, Sharma, Khalid, Imrana, Khalid, Osama, Khalil, Antoine, Khan, Coralie, Khan, Irfan, Khan, Quratul Ain, Khanal, Sushil, Khatak, Abid, Khawaja, Amin, Kherajani, Krish, Kho, Michelle E.; Khoo, Ryan, Khoo, Denisa, Khoo, Saye, Khoso, Nasir, Kiat, Khor How, Kida, Yuri, Kiiza, Peter, Granerud, Beathe Kiland, Kildal, Anders Benjamin, Kim, Jae Burm, Kimmoun, Antoine, Kindgen‐Milles, Detlef, King, Alexander, Kitamura, Nobuya, Kjetland, Eyrun Floerecke Kjetland, Klenerman, Paul, Klont, Rob, Bekken, Gry Kloumann, Knight, Stephen R.; Kobbe, Robin, Kodippily, Chamira, Vasconcelos, Malte Kohns, Koirala, Sabin, Komatsu, Mamoru, Kosgei, Caroline, Kpangon, Arsène, Krawczyk, Karolina, Krishnan, Vinothini, Krishnan, Sudhir, Kruglova, Oksana, Kumar, Ganesh, Kumar, Deepali, Kumar, Mukesh, Vecham, Pavan Kumar, Kuriakose, Dinesh, Kurtzman, Ethan, Kutsogiannis, Demetrios, Kutsyna, Galyna, Kyriakoulis, Konstantinos, Lachatre, Marie, Lacoste, Marie, Laffey, John G.; Lagrange, Marie, Laine, Fabrice, Lairez, Olivier, Lakhey, Sanjay, Lalueza, Antonio, Lambert, Marc, Lamontagne, François, Langelot‐Richard, Marie, Langlois, Vincent, Lantang, Eka Yudha, Lanza, Marina, Laouénan, Cédric, Laribi, Samira, Lariviere, Delphine, Lasry, Stéphane, Lath, Sakshi, Latif, Naveed, Launay, Odile, Laureillard, Didier, Lavie‐Badie, Yoan, Law, Andy, Lawrence, Teresa, Lawrence, Cassie, Le, Minh, Le Bihan, Clément, Le Bris, Cyril, Le Falher, Georges, Le Fevre, Lucie, Le Hingrat, Quentin, Le Maréchal, Marion, Le Mestre, Soizic, Le Moal, Gwenaël, Le Moing, Vincent, Le Nagard, Hervé, Le Turnier, Paul, Leal, Ema, Santos, Marta Leal, Lee, Heng Gee, Lee, Biing Horng, Lee, Yi Lin, Lee, Todd C.; Lee, James, Lee, Jennifer, Lee, Su Hwan, Leeming, Gary, Lefebvre, Laurent, Lefebvre, Bénédicte, Lefèvre, Benjamin, LeGac, Sylvie, Lelievre, Jean‐Daniel, Lellouche, François, Lemaignen, Adrien, Lemee, Véronique, Lemeur, Anthony, Lemmink, Gretchen, Lene, Ha Sha, Lennon, Jenny, León, Rafael, Leone, Marc, Leone, Michela, Lepiller, Quentin, Lescure, François‐Xavier, Lesens, Olivier, Lesouhaitier, Mathieu, Lester‐Grant, Amy, Levy, Yves, Levy, Bruno, Levy‐Marchal, Claire, Lewandowska, Katarzyna, L'Her, Erwan, Bassi, Gianluigi Li, Liang, Janet, Liaquat, Ali, Liegeon, Geoffrey, Lim, Kah Chuan, Lim, Wei Shen, Lima, Chantre, Lina, Lim, Lina, Bruno, Lind, Andreas, Lingad, Maja Katherine, Lingas, Guillaume, Lion‐Daolio, Sylvie, Lissauer, Samantha, Liu, Keibun, Livrozet, Marine, Lizotte, Patricia, Loforte, Antonio, Lolong, Navy, Loon, Leong Chee, Lopes, Diogo, Lopez‐Colon, Dalia, Lopez‐Revilla, Jose W.; Loschner, Anthony L.; Loubet, Paul, Loufti, Bouchra, Louis, Guillame, Lourenco, Silvia, Lovelace‐Macon, Lara, Low, Lee Lee, Lowik, Marije, Loy, Jia Shyi, Lucet, Jean Christophe, Bermejo, Carlos Lumbreras, Luna, Carlos M.; Lungu, Olguta, Luong, Liem, Luque, Nestor, Luton, Dominique, Lwin, Nilar, Lyons, Ruth, Maasikas, Olavi, Mabiala, Oryane, Machado, Moïse, Macheda, Gabriel, Madiha, Hashmi, Maestro de la Calle, Guillermo, Mahieu, Rafael, Mahy, Sophie, Maia, Ana Raquel, Maier, Lars S.; Maillet, Mylène, Maitre, Thomas, Malfertheiner, Maximilian, Malik, Nadia, Mallon, Paddy, Maltez, Fernando, Malvy, Denis, Manda, Victoria, Mandelbrot, Laurent, Manetta, Frank, Mankikian, Julie, Manning, Edmund, Manuel, Aldric, Sant'Ana Malaque, Ceila Maria, Marino, Flávio, Marino, Daniel, Markowicz, Samuel, Maroun Eid, Charbel, Marques, Ana, Marquis, Catherine, Marsh, Brian, Marsh, Laura, Marshal, Megan, Marshall, John, Martelli, Celina Turchi, Martin, Dori‐Ann, Martin, Emily, Martin‐Blondel, Guillaume, Martin‐Loeches, Ignacio, Martinot, Martin, Martin‐Quiros, Alejandro, Martins, João, Martins, Ana, Martins, Nuno, Rego, Caroline Martins, Martucci, Gennaro, Martynenko, Olga, Marwali, Eva Miranda, Marzukie, Marsilla, Maslove, David, Mason, Sabina, Masood, Sobia, Nor, Basri Mat, Matan, Moshe, Mathew, Meghena, Mathieu, Daniel, Mattei, Mathieu, Matulevics, Romans, Maulin, Laurence, Maxwell, Michael, Maynar, Javier, Mazzoni, Thierry, Evoy, Natalie Mc, Sweeney, Lisa Mc, McArthur, Colin, McArthur, Colin, McCarthy, Anne, McCarthy, Aine, McCloskey, Colin, McConnochie, Rachael, McDermott, Sherry, McDonald, Sarah E.; McElroy, Aine, McElwee, Samuel, McEneany, Victoria, McGeer, Allison, McKay, Chris, McKeown, Johnny, McLean, Kenneth A.; McNally, Paul, McNicholas, Bairbre, McPartlan, Elaine, Meaney, Edel, Mear‐Passard, Cécile, Mechlin, Maggie, Meher, Maqsood, Mehkri, Omar, Mele, Ferruccio, Melo, Luis, Memon, Kashif, Mendes, Joao Joao, Menkiti, Ogechukwu, Menon, Kusum, Mentré, France, Mentzer, Alexander J.; Mercier, Noémie, Mercier, Emmanuelle, Merckx, Antoine, Mergeay‐Fabre, Mayka, Mergler, Blake, Merson, Laura, Mesquita, António, Meta, Roberta, Metwally, Osama, Meybeck, Agnès, Meyer, Dan, Meynert, Alison M.; Meysonnier, Vanina, Meziane, Amina, Mezidi, Mehdi, Michelanglei, Céline, Michelet, Isabelle, Mihelis, Efstathia, Mihnovit, Vladislav, Miranda‐Maldonado, Hugo, Misnan, Nor Arisah, Mohamed, Tahira Jamal, Mohamed, Nik Nur Eliza, Moin, Asma, Molina, David, Molinos, Elena, Molloy, Brenda, Mone, Mary, Monteiro, Agostinho, Montes, Claudia, Montrucchio, Giorgia, Moore, Shona C.; Moore, Sarah, Cely, Lina Morales, Moro, Lucia, Morton, Ben, Motherway, Catherine, Motos, Ana, Mouquet, Hugo, Perrot, Clara Mouton, Moyet, Julien, Mudara, Caroline, Mufti, Aisha Kalsoom, Muh, Ng Yong, Muhamad, Dzawani, Mullaert, Jimmy, Müller, Fredrik, Müller, Karl Erik, Munblit, Daniel, Muneeb, Syed, Munir, Nadeem, Munshi, Laveena, Murphy, Aisling, Murphy, Lorna, Murphy, Aisling, Murris, Marlène, Murthy, Srinivas, Musaab, Himed, Muvindi, Himasha, Muyandy, Gugapriyaa, Myrodia, Dimitra Melia, Mohd‐Hanafiah, Farah Nadia, Nagpal, Dave, Nagrebetsky, Alex, Narasimhan, Mangala, Narayanan, Nageswaran, Khan, Rashid Nasim, Nazerali‐Maitland, Alasdair, Neant, Nadège, Neb, Holger, Nekliudov, Nikita, Nelwan, Erni, Neto, Raul, Neumann, Emily, Ng, Pauline Yeung, Ng, Wing Yiu, Nghi, Anthony, Nguyen, Duc, Choileain, Orna Ni, Leathlobhair, Niamh Ni, Nichol, Alistair, Nitayavardhana, Prompak, Nonas, Stephanie, Noordin, Nurul Amani Mohd, Noret, Marion, Norharizam, Nurul Faten Izzati, Norman, Lisa, Notari, Alessandra, Noursadeghi, Mahdad, Nowicka, Karolina, Nowinski, Adam, Nseir, Saad, Nunez, Jose I.; Nurnaningsih, Nurnaningsih, Nusantara, Dwi Utomo, Nyamankolly, Elsa, Nygaard, Anders Benteson, Brien, Fionnuala O.; Callaghan, Annmarie O.; O'Callaghan, Annmarie, Occhipinti, Giovanna, Oconnor, Derbrenn, O'Donnell, Max, Ogston, Tawnya, Ogura, Takayuki, Oh, Tak‐Hyuk, O'Halloran, Sophie, O'Hearn, Katie, Ohshimo, Shinichiro, Oldakowska, Agnieszka, Oliveira, João, Oliveira, Larissa, Olliaro, Piero L.; Ong, Jee Yan, Ong, David S. Y.; Oosthuyzen, Wilna, Opavsky, Anne, Openshaw, Peter, Orakzai, Saijad, Orozco‐Chamorro, Claudia Milena, Ortoleva, Jamel, Osatnik, Javier, O'Shea, Linda, O'Sullivan, Miriam, Othman, Siti Zubaidah, Ouamara, Nadia, Ouissa, Rachida, Oziol, Eric, Pagadoy, Maïder, Pages, Justine, Palacios, Mario, Palacios, Amanda, Palmarini, Massimo, Panarello, Giovanna, Panda, Prasan Kumar, Paneru, Hem, Pang, Lai Hui, Panigada, Mauro, Pansu, Nathalie, Papadopoulos, Aurélie, Parke, Rachael, Parker, Melissa, Parra, Briseida, Pasha, Taha, Pasquier, Jérémie, Pastene, Bruno, Patauner, Fabian, Patel, Drashti, Pathmanathan, Mohan Dass, Patrão, Luís, Patricio, Patricia, Patrier, Juliette, Patterson, Lisa, Pattnaik, Rajyabardhan, Paul, Mical, Paul, Christelle, Paulos, Jorge, Paxton, William A.; Payen, Jean‐François, Peariasamy, Kalaiarasu, Jiménez, Miguel Pedrera, Peek, Giles J.; Peelman, Florent, Peiffer‐Smadja, Nathan, Peigne, Vincent, Pejkovska, Mare, Pelosi, Paolo, Peltan, Ithan D.; Pereira, Rui, Perez, Daniel, Periel, Luis, Perpoint, Thomas, Pesenti, Antonio, Pestre, Vincent, Petrou, Lenka, Petrovic, Michele, Petrov‐Sanchez, Ventzislava, Pettersen, Frank Olav, Peytavin, Gilles, Pharand, Scott, Picard, Walter, Picone, Olivier, de Piero, Maria, Pierobon, Carola, Piersma, Djura, Pimentel, Carlos, Pinto, Raquel, Pires, Catarina, Pironneau, Isabelle, Piroth, Lionel, Pitaloka, Ayodhia, Pius, Riinu, Plantier, Laurent, Png, Hon Shen, Poissy, Julien, Pokeerbux, Ryadh, Pokorska‐Spiewak, Maria, Poli, Sergio, Pollakis, Georgios, Ponscarme, Diane, Popielska, Jolanta, Porto, Diego Bastos, Post, Andra‐Maris, Postma, Douwe F.; Povoa, Pedro, Póvoas, Diana, Powis, Jeff, Prapa, Sofia, Preau, Sébastien, Prebensen, Christian, Preiser, Jean‐Charles, Prinssen, Anton, Pritchard, Mark G.; Priyadarshani, Gamage Dona Dilanthi, Proença, Lucia, Pudota, Sravya, Puéchal, Oriane, Semedi, Bambang Pujo, Pulicken, Mathew, Purcell, Gregory, Quesada, Luisa, Quinones‐Cardona, Vilmaris, González, Víctor Quirós, Quist‐Paulsen, Else, Quraishi, Mohammed, Rabaa, Maia, Rabaud, Christian, Rabindrarajan, Ebenezer, Rafael, Aldo, Rafiq, Marie, Rahardjani, Mutia, Rahman, Rozanah Abd, Rahman, Ahmad Kashfi Haji Ab, Rahutullah, Arsalan, Rainieri, Fernando, Rajahram, Giri Shan, Ramachandran, Pratheema, Ramakrishnan, Nagarajan, Ramli, Ahmad Afiq, Rammaert, Blandine, Ramos, Grazielle Viana, Rana, Asim, Rangappa, Rajavardhan, Ranjan, Ritika, Rapp, Christophe, Rashan, Aasiyah, Rashan, Thalha, Rasheed, Ghulam, Rasmin, Menaldi, Rätsep, Indrek, Rau, Cornelius, Ravi, Tharmini, Raza, Ali, Real, Andre, Rebaudet, Stanislas, Redl, Sarah, Reeve, Brenda, Rehman, Attaur, Reid, Liadain, Reikvam, Dag Henrik, Reis, Renato, Rello, Jordi, Remppis, Jonathan, Remy, Martine, Ren, Hongru, Renk, Hanna, Resseguier, Anne‐Sophie, Revest, Matthieu, Rewa, Oleksa, Reyes, Luis Felipe, Reyes, Tiago, Ribeiro, Maria Ines, Ricchiuto, Antonia, Richardson, David, Richardson, Denise, Richier, Laurent, Ridzuan, Siti Nurul Atikah Ahmad, Riera, Jordi, Rios, Ana L.; Rishu, Asgar, Rispal, Patrick, Risso, Karine, Nuñez, Maria Angelica Rivera, Rizer, Nicholas, Robba, Chiara, Roberto, André, Roberts, Stephanie, Robertson, David L.; Robineau, Olivier, Roche‐Campo, Ferran, Rodari, Paola, Rodeia, Simão, Abreu, Julia Rodriguez, Roessler, Bernhard, Roger, Pierre‐Marie, Roger, Claire, Roilides, Emmanuel, Rojek, Amanda, Romaru, Juliette, Roncon‐Albuquerque, Roberto, Roriz, Mélanie, Rosa‐Calatrava, Manuel, Rose, Michael, Rosenberger, Dorothea, Roslan, Nurul Hidayah Mohammad, Rossanese, Andrea, Rossetti, Matteo, Rossignol, Bénédicte, Rossignol, Patrick, Rousset, Stella, Roy, Carine, Roze, Benoît, Rusmawatiningtyas, Desy, Russell, Clark D.; Ryan, Maria, Ryan, Maeve, Ryckaert, Steffi, Holten, Aleksander Rygh, Saba, Isabela, Sadaf, Sairah, Sadat, Musharaf, Sahraei, Valla, Saint‐Gilles, Maximilien, Sakiyalak, Pranya, Salahuddin, Nawal, Salazar, Leonardo, Saleem, Jodat, Sales, Gabriele, Sallaberry, Stéphane, Salmon Gandonniere, Charlotte, Salvator, Hélène, Sanchez, Olivier, Sanchez‐Miralles, Angel, Sancho‐Shimizu, Vanessa, Sandhu, Gyan, Sandhu, Zulfiqar, Sandrine, Pierre‐François, Sandulescu, Oana, Santos, Marlene, Sarfo‐Mensah, Shirley, Banheiro, Bruno Sarmento, Sarmiento, Iam Claire E.; Sarton, Benjamine, Satya, Ankana, Satyapriya, Sree, Satyawati, Rumaisah, Saviciute, Egle, Savvidou, Parthena, Saw, Yen Tsen, Schaffer, Justin, Schermer, Tjard, Scherpereel, Arnaud, Schneider, Marion, Schroll, Stephan, Schwameis, Michael, Schwartz, Gary, Scott, Janet T.; Scott‐Brown, James, Sedillot, Nicholas, Seitz, Tamara, Selvanayagam, Jaganathan, Selvarajoo, Mageswari, Semaille, Caroline, Semple, Malcolm G.; Senian, Rasidah Bt, Senneville, Eric, Sequeira, Filipa, Sequeira, Tânia, Neto, Ary Serpa, Balazote, Pablo Serrano, Shadowitz, Ellen, Shahidan, Syamin Asyraf, Shamsah, Mohammad, Shankar, Anuraj, Sharjeel, Shaikh, Sharma, Pratima, Shaw, Catherine A.; Shaw, Victoria, Sheharyar, Ashraf, Shetty, Rohan, Shetty, Rajesh Mohan, Shi, Haixia, Shiekh, Mohiuddin, Shime, Nobuaki, Shimizu, Keiki, Shrapnel, Sally, Shrestha, Pramesh Sundar, Shrestha, Shubha Kalyan, Shum, Hoi Ping, Mohammed, Nassima Si, Siang, Ng Yong, Sibiude, Jeanne, Siddiqui, Atif, Sigfrid, Louise, Sillaots, Piret, Silva, Catarina, Silva, Rogério, Silva, Maria Joao, Heng, Benedict Sim Lim, Sin, Wai Ching, Sinatti, Dario, Singh, Punam, Singh, Budha Charan, Sitompul, Pompini Agustina, Sivam, Karisha, Skogen, Vegard, Smith, Sue, Smood, Benjamin, Smyth, Coilin, Smyth, Michelle, Snacken, Morgane, So, Dominic, Soh, Tze Vee, Solberg, Lene Bergendal, Solomon, Joshua, Solomon, Tom, Somers, Emily, Sommet, Agnès, Song, Rima, Song, Myung Jin, Song, Tae, Chia, Jack Song, Sonntagbauer, Michael, Soom, Azlan Mat, Søraas, Arne, Søraas, Camilla Lund, Sotto, Alberto, Soum, Edouard, Sousa, Marta, Sousa, Ana Chora, Uva, Maria Sousa, Souza‐Dantas, Vicente, Sperry, Alexandra, Spinuzza, Elisabetta, Darshana, B. P. Sanka Ruwan Sri, Sriskandan, Shiranee, Stabler, Sarah, Staudinger, Thomas, Stecher, Stephanie‐Susanne, Steinsvik, Trude, Stienstra, Ymkje, Stiksrud, Birgitte, Stolz, Eva, Stone, Amy, Streinu‐Cercel, Adrian, Streinu‐Cercel, Anca, Stuart, David, Stuart, Ami, Subekti, Decy, Suen, Gabriel, Suen, Jacky Y.; Sultana, Asfia, Summers, Charlotte, Supic, Dubravka, Suppiah, Deepashankari, Surovcová, Magdalena, Suwarti, Suwarti, Svistunov, Andrey, Syahrin, Sarah, Syrigos, Konstantinos, Sztajnbok, Jaques, Szuldrzynski, Konstanty, Tabrizi, Shirin, Taccone, Fabio S.; Tagherset, Lysa, Taib, Shahdattul Mawarni, Talarek, Ewa, Taleb, Sara, Talsma, Jelmer, Tamisier, Renaud, Tampubolon, Maria Lawrensia, Tan, Kim Keat, Tan, Yan Chyi, Tanaka, Taku, Tanaka, Hiroyuki, Taniguchi, Hayato, Taqdees, Huda, Taqi, Arshad, Tardivon, Coralie, Tattevin, Pierre, Taufik, M. Azhari, Tawfik, Hassan, Tedder, Richard S.; Tee, Tze Yuan, Teixeira, João, Tejada, Sofia, Tellier, Marie‐Capucine, Teoh, Sze Kye, Teotonio, Vanessa, Téoulé, François, Terpstra, Pleun, Terrier, Olivier, Terzi, Nicolas, Tessier‐Grenier, Hubert, Tey, Adrian, Thabit, Alif Adlan Mohd, Thakur, Anand, Tham, Zhang Duan, Thangavelu, Suvintheran, Thibault, Vincent, Thiberville, Simon‐Djamel, Thill, Benoît, Thirumanickam, Jananee, Thompson, Shaun, Thomson, Emma C.; Thurai, Surain Raaj Thanga, Thwaites, Ryan S.; Tierney, Paul, Tieroshyn, Vadim, Timashev, Peter S.; Timsit, Jean‐François, Vijayaraghavan, Bharath Kumar Tirupakuzhi, Tissot, Noémie, Toh, Jordan Zhien Yang, Toki, Maria, Tonby, Kristian, Tonnii, Sia Loong, Torres, Margarida, Torres, Antoni, Santos‐Olmo, Rosario Maria Torres, Torres‐Zevallos, Hernando, Towers, Michael, Trapani, Tony, Treoux, Théo, Tromeur, Cécile, Trontzas, Ioannis, Trouillon, Tiffany, Truong, Jeanne, Tual, Christelle, Tubiana, Sarah, Tuite, Helen, Turmel, Jean‐Marie, Turtle, Lance C. W.; Tveita, Anders, Twardowski, Pawel, Uchiyama, Makoto, Udayanga, P. G. Ishara, Udy, Andrew, Ullrich, Roman, Uribe, Alberto, Usman, Asad.
Influenza and Other Respiratory Viruses ; 2022.
Article in English | Web of Science | ID: covidwho-2019369

ABSTRACT

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe arid Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years;geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did riot meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.

3.
Lancet Infect Dis ; 22(8): 1153-1162, 2022 08.
Article in English | MEDLINE | ID: covidwho-1972395

ABSTRACT

BACKGROUND: Cases of human monkeypox are rarely seen outside of west and central Africa. There are few data regarding viral kinetics or the duration of viral shedding and no licensed treatments. Two oral drugs, brincidofovir and tecovirimat, have been approved for treatment of smallpox and have demonstrated efficacy against monkeypox in animals. Our aim was to describe the longitudinal clinical course of monkeypox in a high-income setting, coupled with viral dynamics, and any adverse events related to novel antiviral therapies. METHODS: In this retrospective observational study, we report the clinical features, longitudinal virological findings, and response to off-label antivirals in seven patients with monkeypox who were diagnosed in the UK between 2018 and 2021, identified through retrospective case-note review. This study included all patients who were managed in dedicated high consequence infectious diseases (HCID) centres in Liverpool, London, and Newcastle, coordinated via a national HCID network. FINDINGS: We reviewed all cases since the inception of the HCID (airborne) network between Aug 15, 2018, and Sept 10, 2021, identifying seven patients. Of the seven patients, four were men and three were women. Three acquired monkeypox in the UK: one patient was a health-care worker who acquired the virus nosocomially, and one patient who acquired the virus abroad transmitted it to an adult and child within their household cluster. Notable disease features included viraemia, prolonged monkeypox virus DNA detection in upper respiratory tract swabs, reactive low mood, and one patient had a monkeypox virus PCR-positive deep tissue abscess. Five patients spent more than 3 weeks (range 22-39 days) in isolation due to prolonged PCR positivity. Three patients were treated with brincidofovir (200 mg once a week orally), all of whom developed elevated liver enzymes resulting in cessation of therapy. One patient was treated with tecovirimat (600 mg twice daily for 2 weeks orally), experienced no adverse effects, and had a shorter duration of viral shedding and illness (10 days hospitalisation) compared with the other six patients. One patient experienced a mild relapse 6 weeks after hospital discharge. INTERPRETATION: Human monkeypox poses unique challenges, even to well resourced health-care systems with HCID networks. Prolonged upper respiratory tract viral DNA shedding after skin lesion resolution challenged current infection prevention and control guidance. There is an urgent need for prospective studies of antivirals for this disease. FUNDING: None.


Subject(s)
Monkeypox , Adult , Animals , Antiviral Agents/therapeutic use , Child , Female , Humans , Male , Monkeypox/diagnosis , Monkeypox/drug therapy , Monkeypox/epidemiology , Prospective Studies , Retrospective Studies , United Kingdom/epidemiology
4.
BMC Infect Dis ; 22(1): 556, 2022 Jun 18.
Article in English | MEDLINE | ID: covidwho-1962756

ABSTRACT

BACKGROUND: SARS-CoV-2 is known to transmit in hospital settings, but the contribution of infections acquired in hospitals to the epidemic at a national scale is unknown. METHODS: We used comprehensive national English datasets to determine the number of COVID-19 patients with identified hospital-acquired infections (with symptom onset > 7 days after admission and before discharge) in acute English hospitals up to August 2020. As patients may leave the hospital prior to detection of infection or have rapid symptom onset, we combined measures of the length of stay and the incubation period distribution to estimate how many hospital-acquired infections may have been missed. We used simulations to estimate the total number (identified and unidentified) of symptomatic hospital-acquired infections, as well as infections due to onward community transmission from missed hospital-acquired infections, to 31st July 2020. RESULTS: In our dataset of hospitalised COVID-19 patients in acute English hospitals with a recorded symptom onset date (n = 65,028), 7% were classified as hospital-acquired. We estimated that only 30% (range across weeks and 200 simulations: 20-41%) of symptomatic hospital-acquired infections would be identified, with up to 15% (mean, 95% range over 200 simulations: 14.1-15.8%) of cases currently classified as community-acquired COVID-19 potentially linked to hospital transmission. We estimated that 26,600 (25,900 to 27,700) individuals acquired a symptomatic SARS-CoV-2 infection in an acute Trust in England before 31st July 2020, resulting in 15,900 (15,200-16,400) or 20.1% (19.2-20.7%) of all identified hospitalised COVID-19 cases. CONCLUSIONS: Transmission of SARS-CoV-2 to hospitalised patients likely caused approximately a fifth of identified cases of hospitalised COVID-19 in the "first wave" in England, but less than 1% of all infections in England. Using time to symptom onset from admission for inpatients as a detection method likely misses a substantial proportion (> 60%) of hospital-acquired infections.


Subject(s)
COVID-19 , Cross Infection , COVID-19/epidemiology , Cross Infection/epidemiology , Hospitalization , Hospitals , Humans , SARS-CoV-2
5.
BMC Med ; 20(1): 244, 2022 07 06.
Article in English | MEDLINE | ID: covidwho-1923545

ABSTRACT

BACKGROUND: Previous studies assessing the prevalence of COVID-19 sequelae in adults and children were performed in the absence of an agreed definition. We investigated prevalence of post-COVID-19 condition (PCC) (WHO definition), at 6- and 12-months follow-up, amongst previously hospitalised adults and children and assessed risk factors. METHODS: Prospective cohort study of children and adults with confirmed COVID-19 in Moscow, hospitalised between April and August, 2020. Two follow-up telephone interviews, using the International Severe Acute Respiratory and Emerging Infection Consortium survey, were performed at 6 and 12 months after discharge. RESULTS: One thousand thirteen of 2509 (40%) of adults and 360 of 849 (42%) of children discharged participated in both the 6- and 12-month follow-ups. PCC prevalence was 50% (95% CI 47-53) in adults and 20% (95% CI 16-24) in children at 6 months, with decline to 34% (95% CI 31-37) and 11% (95% CI 8-14), respectively, at 12 months. In adults, female sex was associated with PCC at 6- and 12-month follow-up (OR 2.04, 95% CI 1.57 to 2.65) and (OR 2.04, 1.54 to 2.69), respectively. Pre-existing hypertension (OR 1.42, 1.04 to 1.94) was associated with post-COVID-19 condition at 12 months. In children, neurological comorbidities were associated with PCC both at 6 months (OR 4.38, 1.36 to 15.67) and 12 months (OR 8.96, 2.55 to 34.82) while allergic respiratory diseases were associated at 12 months (OR 2.66, 1.04 to 6.47). CONCLUSIONS: Although prevalence of PCC declined one year after discharge, one in three adults and one in ten children experienced ongoing sequelae. In adults, females and persons with pre-existing hypertension, and in children, persons with neurological comorbidities or allergic respiratory diseases are at higher risk of PCC.


Subject(s)
COVID-19 , Hypertension , Adult , COVID-19/epidemiology , Child , Cohort Studies , Female , Hospitals , Humans , Moscow/epidemiology , Patient Discharge , Prevalence , Prospective Studies , Risk Factors
6.
Open Forum Infect Dis ; 9(5): ofac179, 2022 May.
Article in English | MEDLINE | ID: covidwho-1915843

ABSTRACT

Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11-1.70] ng/mL vs 0.24 [0.10-0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51-.60]).

8.
Gigascience ; 112022 05 26.
Article in English | MEDLINE | ID: covidwho-1873911

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a complex strategy for the transcription of viral subgenomic mRNAs (sgmRNAs), which are targets for nucleic acid diagnostics. Each of these sgmRNAs has a unique 5' sequence, the leader-transcriptional regulatory sequence gene junction (leader-TRS junction), that can be identified using sequencing. High-resolution sequencing has been used to investigate the biology of SARS-CoV-2 and the host response in cell culture and animal models and from clinical samples. LeTRS, a bioinformatics tool, was developed to identify leader-TRS junctions and can be used as a proxy to quantify sgmRNAs for understanding virus biology. LeTRS is readily adaptable for other coronaviruses such as Middle East respiratory syndrome coronavirus or a future newly discovered coronavirus. LeTRS was tested on published data sets and novel clinical samples from patients and longitudinal samples from animal models with coronavirus disease 2019. LeTRS identified known leader-TRS junctions and identified putative novel sgmRNAs that were common across different mammalian species. This may be indicative of an evolutionary mechanism where plasticity in transcription generates novel open reading frames, which can then subject to selection pressure. The data indicated multiphasic abundance of sgmRNAs in two different animal models. This recapitulates the relative sgmRNA abundance observed in cells at early points in infection but not at late points. This pattern is reflected in some human nasopharyngeal samples and therefore has implications for transmission models and nucleic acid-based diagnostics. LeTRS provides a quantitative measure of sgmRNA abundance from sequencing data. This can be used to assess the biology of SARS-CoV-2 (or other coronaviruses) in clinical and nonclinical samples, especially to evaluate different variants and medical countermeasures that may influence viral RNA synthesis.


Subject(s)
COVID-19 , SARS-CoV-2 , Animals , Cell Culture Techniques , Computational Biology , Humans , Mammals/genetics , Models, Animal , RNA, Messenger/genetics , SARS-CoV-2/genetics
9.
JCI Insight ; 7(13)2022 07 08.
Article in English | MEDLINE | ID: covidwho-1861743

ABSTRACT

The role of immune responses to previously seen endemic coronavirus epitopes in severe acute respiratory coronavirus 2 (SARS-CoV-2) infection and disease progression has not yet been determined. Here, we show that a key characteristic of fatal outcomes with coronavirus disease 2019 (COVID-19) is that the immune response to the SARS-CoV-2 spike protein is enriched for antibodies directed against epitopes shared with endemic beta-coronaviruses and has a lower proportion of antibodies targeting the more protective variable regions of the spike. The magnitude of antibody responses to the SARS-CoV-2 full-length spike protein, its domains and subunits, and the SARS-CoV-2 nucleocapsid also correlated strongly with responses to the endemic beta-coronavirus spike proteins in individuals admitted to an intensive care unit (ICU) with fatal COVID-19 outcomes, but not in individuals with nonfatal outcomes. This correlation was found to be due to the antibody response directed at the S2 subunit of the SARS-CoV-2 spike protein, which has the highest degree of conservation between the beta-coronavirus spike proteins. Intriguingly, antibody responses to the less cross-reactive SARS-CoV-2 nucleocapsid were not significantly different in individuals who were admitted to an ICU with fatal and nonfatal outcomes, suggesting an antibody profile in individuals with fatal outcomes consistent with an "original antigenic sin" type response.


Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Antibodies, Viral , Antibody Formation , Epitopes , Humans , SARS-CoV-2
10.
Front Immunol ; 13: 807104, 2022.
Article in English | MEDLINE | ID: covidwho-1855349

ABSTRACT

Immunoglobulin gene heterogeneity reflects the diversity and focus of the humoral immune response towards different infections, enabling inference of B cell development processes. Detailed compositional and lineage analysis of long read IGH repertoire sequencing, combining examples of pandemic, epidemic and endemic viral infections with control and vaccination samples, demonstrates general responses including increased use of IGHV4-39 in both Zaire Ebolavirus (EBOV) and COVID-19 patient cohorts. We also show unique characteristics absent in Respiratory Syncytial Virus or yellow fever vaccine samples: EBOV survivors show unprecedented high levels of class switching events while COVID-19 repertoires from acute disease appear underdeveloped. Despite the high levels of clonal expansion in COVID-19 IgG1 repertoires there is a striking lack of evidence of germinal centre mutation and selection. Given the differences in COVID-19 morbidity and mortality with age, it is also pertinent that we find significant differences in repertoire characteristics between young and old patients. Our data supports the hypothesis that a primary viral challenge can result in a strong but immature humoral response where failures in selection of the repertoire risk off-target effects.


Subject(s)
COVID-19 , Ebolavirus , Hemorrhagic Fever, Ebola , Respiratory Syncytial Virus, Human , Antibodies, Viral , Humans , Pandemics , Respiratory Syncytial Virus, Human/genetics , SARS-CoV-2
11.
mSphere ; 7(3): e0091321, 2022 06 29.
Article in English | MEDLINE | ID: covidwho-1832362

ABSTRACT

New variants of SARS-CoV-2 are continuing to emerge and dominate the global sequence landscapes. Several variants have been labeled variants of concern (VOCs) because they may have a transmission advantage, increased risk of morbidity and/or mortality, or immune evasion upon a background of prior infection or vaccination. Placing the VOCs in context with the underlying variability of SARS-CoV-2 is essential in understanding virus evolution and selection pressures. Dominant genome sequences and the population genetics of SARS-CoV-2 in nasopharyngeal swabs from hospitalized patients were characterized. Nonsynonymous changes at a minor variant level were identified. These populations were generally preserved when isolates were amplified in cell culture. To place the Alpha, Beta, Delta, and Omicron VOCs in context, their growth was compared to clinical isolates of different lineages from earlier in the pandemic. The data indicated that the growth in cell culture of the Beta variant was more than that of the other variants in Vero E6 cells but not in hACE2-A549 cells. Looking at each time point, Beta grew more than the other VOCs in hACE2-A549 cells at 24 to 48 h postinfection. At 72 h postinfection there was no difference in the growth of any of the variants in either cell line. Overall, this work suggested that exploring the biology of SARS-CoV-2 is complicated by population dynamics and that these need to be considered with new variants. In the context of variation seen in other coronaviruses, the variants currently observed for SARS-CoV-2 are very similar in terms of their clinical spectrum of disease. IMPORTANCE SARS-CoV-2 is the causative agent of COVID-19. The virus has spread across the planet, causing a global pandemic. In common with other coronaviruses, SARS-CoV-2 genomes can become quite diverse as a consequence of replicating inside cells. This has given rise to multiple variants from the original virus that infected humans. These variants may have different properties and in the context of a widespread vaccination program may render vaccines less effective. Our research confirms the degree of genetic diversity of SARS-CoV-2 in patients. By comparing the growth of previous variants to the pattern seen with four variants of concern (VOCs) (Alpha, Beta, Delta, and Omicron), we show that, at least in cells, Beta variant growth exceeds that of Alpha, Delta, and Omicron VOCs at 24 to 48 h in both Vero E6 and hACE2-A549 cells, but by 72 h postinfection, the amount of virus is not different from that of the other VOCs.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Pandemics , Phenotype , SARS-CoV-2/genetics
12.
Anal Chem ; 94(19): 6919-6923, 2022 05 17.
Article in English | MEDLINE | ID: covidwho-1829921

ABSTRACT

Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10-16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10-16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients.


Subject(s)
COVID-19 , Humans , Magnetic Resonance Spectroscopy/methods , Metabolome , Metabolomics/methods , Proton Magnetic Resonance Spectroscopy
13.
Sci Rep ; 12(1): 6843, 2022 04 27.
Article in English | MEDLINE | ID: covidwho-1815585

ABSTRACT

COVID-19 is clinically characterised by fever, cough, and dyspnoea. Symptoms affecting other organ systems have been reported. However, it is the clinical associations of different patterns of symptoms which influence diagnostic and therapeutic decision-making. In this study, we applied clustering techniques to a large prospective cohort of hospitalised patients with COVID-19 to identify clinically meaningful sub-phenotypes. We obtained structured clinical data on 59,011 patients in the UK (the ISARIC Coronavirus Clinical Characterisation Consortium, 4C) and used a principled, unsupervised clustering approach to partition the first 25,477 cases according to symptoms reported at recruitment. We validated our findings in a second group of 33,534 cases recruited to ISARIC-4C, and in 4,445 cases recruited to a separate study of community cases. Unsupervised clustering identified distinct sub-phenotypes. First, a core symptom set of fever, cough, and dyspnoea, which co-occurred with additional symptoms in three further patterns: fatigue and confusion, diarrhoea and vomiting, or productive cough. Presentations with a single reported symptom of dyspnoea or confusion were also identified, alongside a sub-phenotype of patients reporting few or no symptoms. Patients presenting with gastrointestinal symptoms were more commonly female, had a longer duration of symptoms before presentation, and had lower 30-day mortality. Patients presenting with confusion, with or without core symptoms, were older and had a higher unadjusted mortality. Symptom sub-phenotypes were highly consistent in replication analysis within the ISARIC-4C study. Similar patterns were externally verified in patients from a study of self-reported symptoms of mild disease. The large scale of the ISARIC-4C study enabled robust, granular discovery and replication. Clinical interpretation is necessary to determine which of these observations have practical utility. We propose that four sub-phenotypes are usefully distinct from the core symptom group: gastro-intestinal disease, productive cough, confusion, and pauci-symptomatic presentations. Importantly, each is associated with an in-hospital mortality which differs from that of patients with core symptoms.


Subject(s)
COVID-19 , Confusion , Cough , Dyspnea , Fatigue , Female , Fever , Humans , Prospective Studies
14.
Pediatr Res ; 2022 Apr 22.
Article in English | MEDLINE | ID: covidwho-1805591

ABSTRACT

BACKGROUND: We hypothesised that the clinical characteristics of hospitalised children and young people (CYP) with SARS-CoV-2 in the UK second wave (W2) would differ from the first wave (W1) due to the alpha variant (B.1.1.7), school reopening and relaxation of shielding. METHODS: Prospective multicentre observational cohort study of patients <19 years hospitalised in the UK with SARS-CoV-2 between 17/01/20 and 31/01/21. Clinical characteristics were compared between W1 and W2 (W1 = 17/01/20-31/07/20,W2 = 01/08/20-31/01/21). RESULTS: 2044 CYP < 19 years from 187 hospitals. 427/2044 (20.6%) with asymptomatic/incidental SARS-CoV-2 were excluded from main analysis. 16.0% (248/1548) of symptomatic CYP were admitted to critical care and 0.8% (12/1504) died. 5.6% (91/1617) of symptomatic CYP had Multisystem Inflammatory Syndrome in Children (MIS-C). After excluding CYP with MIS-C, patients in W2 had lower Paediatric Early Warning Scores (PEWS, composite vital sign score), lower antibiotic use and less respiratory and cardiovascular support than W1. The proportion of CYP admitted to critical care was unchanged. 58.0% (938/1617) of symptomatic CYP had no reported comorbidity. Patients without co-morbidities were younger (42.4%, 398/938, <1 year), had lower PEWS, shorter length of stay and less respiratory support. CONCLUSIONS: We found no evidence of increased disease severity in W2 vs W1. A large proportion of hospitalised CYP had no comorbidity. IMPACT: No evidence of increased severity of COVID-19 admissions amongst children and young people (CYP) in the second vs first wave in the UK, despite changes in variant, relaxation of shielding and return to face-to-face schooling. CYP with no comorbidities made up a significant proportion of those admitted. However, they had shorter length of stays and lower treatment requirements than CYP with comorbidities once those with MIS-C were excluded. At least 20% of CYP admitted in this cohort had asymptomatic/incidental SARS-CoV-2 infection. This paper was presented to SAGE to inform CYP vaccination policy in the UK.

15.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-333336

ABSTRACT

Importance: Neurological complications are common following acute COVID-19, causing significant morbidity with health economic consequences. However, no treatment studies in COVID-19 focussing on neurological complications have been published to date. Objective: Does treatment with either remdesivir, dexamethasone or both reduce the risk of neurological complications in adult patients hospitalised with COVID-19? Design and setting: COVID-19 neurological complications, and remdesivir and dexamethasone use, were studied in adults admitted to hospitals in the UK with COVID-19, using data from the International Severe Acute and emerging Respiratory Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK, study registration ISRCTN66726260). Treatment allocation was non-blinded and performed by reporting clinicians. A propensity scoring methodology was used to correct for confounding between treatment groups. Participants: 89,297 patients aged 18 years and older with laboratory confirmed SARS-CoV-2 infection were eligible for inclusion. Patients requiring supplemental oxygen at any point during admission (n=64,088) were defined as having severe COVID-19, as per WHO criteria. Patients were excluded if they received a dose of any SARS-CoV-2 vaccine or contracted COVID-19 in hospital. Exposures: Treatment with remdesivir, dexamethasone or both was assessed against standard of care. Main outcome(s) and measure(s): A neurological complication (stroke, seizure, meningitis/encephalitis or any other neurological complication) occurring at the point of death, discharge, or resolution of the COVID-19 clinical episode. Results: The median age of patients was 71 (IQR, 56 to 82). 56% were identified as male and 71% were of white ethnicity. 4,408 patients (4.7%) developed neurological complications. In patients with severe COVID-19, neurological complications were associated with increased mortality (OR 1.36, 95% CI 1.25 to 1.47), intensive care admission (OR 1.54, 95% CI 1.41 to 1.6), likelihood of worse self-care on discharge (OR 3.79, 95% CI 3.36 to 4.26) and an increased time to recovery (9.65 days, 95% CI 7.12 to 12.17 days). Treatment with dexamethasone (n=21,129), remdesivir (n=1,428) and both treatments combined (n=10,846) in severe COVID-19 were associated with a reduced incidence of neurological complications;OR 0.76 (95% CI 0.69 to 0.83);OR 0.68 (95% CI 0.51 to 0.90);OR 0.54, (95% CI 0.47 to 0.61) respectively. Conclusions and relevance: Treatment with dexamethasone, remdesivir or both in patients hospitalised with COVID-19 was associated with reduced neurological complications in an additive manner, such that the greatest benefit was observed in patients who received both drugs together. The potential of these treatments to reduce neurological disability is of urgent importance to patients, healthcare systems and public health bodies.

16.
Nat Med ; 28(5): 1031-1041, 2022 05.
Article in English | MEDLINE | ID: covidwho-1773989

ABSTRACT

Since its emergence in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of cases and continues to circulate globally. To establish a novel SARS-CoV-2 human challenge model that enables controlled investigation of pathogenesis, correlates of protection and efficacy testing of forthcoming interventions, 36 volunteers aged 18-29 years without evidence of previous infection or vaccination were inoculated with 10 TCID50 of a wild-type virus (SARS-CoV-2/human/GBR/484861/2020) intranasally in an open-label, non-randomized study (ClinicalTrials.gov identifier NCT04865237 ; funder, UK Vaccine Taskforce). After inoculation, participants were housed in a high-containment quarantine unit, with 24-hour close medical monitoring and full access to higher-level clinical care. The study's primary objective was to identify an inoculum dose that induced well-tolerated infection in more than 50% of participants, with secondary objectives to assess virus and symptom kinetics during infection. All pre-specified primary and secondary objectives were met. Two participants were excluded from the per-protocol analysis owing to seroconversion between screening and inoculation, identified post hoc. Eighteen (~53%) participants became infected, with viral load (VL) rising steeply and peaking at ~5 days after inoculation. Virus was first detected in the throat but rose to significantly higher levels in the nose, peaking at ~8.87 log10 copies per milliliter (median, 95% confidence interval (8.41, 9.53)). Viable virus was recoverable from the nose up to ~10 days after inoculation, on average. There were no serious adverse events. Mild-to-moderate symptoms were reported by 16 (89%) infected participants, beginning 2-4 days after inoculation, whereas two (11%) participants remained asymptomatic (no reportable symptoms). Anosmia or dysosmia developed more slowly in 15 (83%) participants. No quantitative correlation was noted between VL and symptoms, with high VLs present even in asymptomatic infection. All infected individuals developed serum spike-specific IgG and neutralizing antibodies. Results from lateral flow tests were strongly associated with viable virus, and modeling showed that twice-weekly rapid antigen tests could diagnose infection before 70-80% of viable virus had been generated. Thus, with detailed characterization and safety analysis of this first SARS-CoV-2 human challenge study in young adults, viral kinetics over the course of primary infection with SARS-CoV-2 were established, with implications for public health recommendations and strategies to affect SARS-CoV-2 transmission. Future studies will identify the immune factors associated with protection in those participants who did not develop infection or symptoms and define the effect of prior immunity and viral variation on clinical outcome.


Subject(s)
COVID-19 , SARS-CoV-2 , Antibodies, Viral , Humans , Kinetics , Treatment Outcome , Viral Load , Young Adult
18.
Diabetes Care ; 45(5): 1132-1140, 2022 05 01.
Article in English | MEDLINE | ID: covidwho-1742155

ABSTRACT

OBJECTIVE: To investigate the association between admission blood glucose levels and risk of in-hospital cardiovascular and renal complications. RESEARCH DESIGN AND METHODS: In this multicenter prospective study of 36,269 adults hospitalized with COVID-19 between 6 February 2020 and 16 March 2021 (N = 143,266), logistic regression models were used to explore associations between admission glucose level (mmol/L and mg/dL) and odds of in-hospital complications, including heart failure, arrhythmia, cardiac ischemia, cardiac arrest, coagulation complications, stroke, and renal injury. Nonlinearity was investigated using restricted cubic splines. Interaction models explored whether associations between glucose levels and complications were modified by clinically relevant factors. RESULTS: Cardiovascular and renal complications occurred in 10,421 (28.7%) patients; median admission glucose level was 6.7 mmol/L (interquartile range 5.8-8.7) (120.6 mg/dL [104.4-156.6]). While accounting for confounders, for all complications except cardiac ischemia and stroke, there was a nonlinear association between glucose and cardiovascular and renal complications. For example, odds of heart failure, arrhythmia, coagulation complications, and renal injury decreased to a nadir at 6.4 mmol/L (115 mg/dL), 4.9 mmol/L (88.2 mg/dL), 4.7 mmol/L (84.6 mg/dL), and 5.8 mmol/L (104.4 mg/dL), respectively, and increased thereafter until 26.0 mmol/L (468 mg/dL), 50.0 mmol/L (900 mg/dL), 8.5 mmol/L (153 mg/dL), and 32.4 mmol/L (583.2 mg/dL). Compared with 5 mmol/L (90 mg/dL), odds ratios at these glucose levels were 1.28 (95% CI 0.96, 1.69) for heart failure, 2.23 (1.03, 4.81) for arrhythmia, 1.59 (1.36, 1.86) for coagulation complications, and 2.42 (2.01, 2.92) for renal injury. For most complications, a modifying effect of age was observed, with higher odds of complications at higher glucose levels for patients age <69 years. Preexisting diabetes status had a similar modifying effect on odds of complications, but evidence was strongest for renal injury, cardiac ischemia, and any cardiovascular/renal complication. CONCLUSIONS: Increased odds of cardiovascular or renal complications were observed for admission glucose levels indicative of both hypo- and hyperglycemia. Admission glucose could be used as a marker for risk stratification of high-risk patients. Further research should evaluate interventions to optimize admission glucose on improving COVID-19 outcomes.


Subject(s)
COVID-19 , Heart Failure , Stroke , Adult , Aged , Blood Glucose , COVID-19/complications , COVID-19/epidemiology , Humans , Ischemia , Kidney , Prospective Studies , Stroke/epidemiology , Stroke/etiology
19.
Nature ; 607(7917): 97-103, 2022 07.
Article in English | MEDLINE | ID: covidwho-1730298

ABSTRACT

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2-4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease.


Subject(s)
COVID-19 , Critical Illness , Genome, Human , Host-Pathogen Interactions , Whole Genome Sequencing , ATP-Binding Cassette Transporters , COVID-19/genetics , COVID-19/mortality , COVID-19/pathology , COVID-19/virology , Cell Adhesion Molecules , Critical Care , Critical Illness/mortality , E-Selectin , Factor VIII , Fucosyltransferases , Genome, Human/genetics , Genome-Wide Association Study , Host-Pathogen Interactions/genetics , Humans , Interleukin-10 Receptor beta Subunit , Lectins, C-Type , Mucin-1 , Nerve Tissue Proteins , Phospholipid Transfer Proteins , Receptors, Cell Surface , Repressor Proteins , SARS-CoV-2/pathogenicity
20.
Eur Respir J ; 59(2)2022 Feb.
Article in English | MEDLINE | ID: covidwho-1690989

ABSTRACT

BACKGROUND: The long-term sequelae of coronavirus disease 2019 (COVID-19) in children remain poorly characterised. This study aimed to assess long-term outcomes in children previously hospitalised with COVID-19 and associated risk factors. METHODS: This is a prospective cohort study of children (≤18 years old) admitted to hospital with confirmed COVID-19. Children admitted between 2 April 2020 and 26 August 2020 were included. Telephone interviews used the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 Health and Wellbeing Follow-up Survey for Children. Persistent symptoms (>5 months) were further categorised by system(s) involved. RESULTS: 518 out of 853 (61%) eligible children were available for the follow-up assessment and included in the study. Median (interquartile range (IQR)) age was 10.4 (3-15.2) years and 270 (52.1%) were girls. Median (IQR) follow-up since hospital discharge was 256 (223-271) days. At the time of the follow-up interview 126 (24.3%) participants reported persistent symptoms, among which fatigue (53, 10.7%), sleep disturbance (36, 6.9%) and sensory problems (29, 5.6%) were the most common. Multiple symptoms were experienced by 44 (8.4%) participants. Risk factors for persistent symptoms were: older age "6-11 years" (OR 2.74, 95% CI 1.37-5.75) and "12-18 years" (OR 2.68, 95% CI 1.41-5.4), and a history of allergic diseases (OR 1.67, 95% CI 1.04-2.67). CONCLUSIONS: A quarter of children experienced persistent symptoms months after hospitalisation with acute COVID-19 infection, with almost one in 10 experiencing multisystem involvement. Older age and allergic diseases were associated with higher risk of persistent symptoms at follow-up.


Subject(s)
COVID-19 , Adolescent , Aged , Child , Child, Hospitalized , Female , Follow-Up Studies , Humans , Prospective Studies , Risk Factors , SARS-CoV-2
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