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1.
BMJ paediatrics open ; JOUR(1), 6.
Article in English | EuropePMC | ID: covidwho-2092727

ABSTRACT

Background The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries. Methods The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria. Results A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)). Conclusion Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities.

2.
Elife ; 112022 10 05.
Article in English | MEDLINE | ID: covidwho-2056253

ABSTRACT

Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings. Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries. Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population. Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome. Funding: Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , COVID-19/virology , Humans , SARS-CoV-2/genetics
3.
Crit Care ; 26(1): 276, 2022 09 13.
Article in English | MEDLINE | ID: covidwho-2029728

ABSTRACT

BACKGROUND: Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs). METHODS: This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support. RESULTS: A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]). CONCLUSIONS: In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.


Subject(s)
COVID-19 , Respiratory Insufficiency , COVID-19/therapy , Humans , Prospective Studies , Respiratory Insufficiency/therapy , SARS-CoV-2 , Tachypnea
4.
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.; 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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.; 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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.

5.
Lancet Respir Med ; 10(7): 632-634, 2022 07.
Article in English | MEDLINE | ID: covidwho-1984282
6.
Sci Data ; 9(1): 454, 2022 07 30.
Article in English | MEDLINE | ID: covidwho-1967615

ABSTRACT

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.


Subject(s)
COVID-19 , Hospitalization , Humans , Pandemics , Prospective Studies , SARS-CoV-2
7.
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
8.
Lancet Respir Med ; 10(7): 715-724, 2022 07.
Article in English | MEDLINE | ID: covidwho-1886188

ABSTRACT

Health consequences that persist beyond the acute infection phase of COVID-19, termed post-COVID-19 condition (also commonly known as long COVID), vary widely and represent a growing global health challenge. Research on post-COVID-19 condition is expanding but, at present, no agreement exists on the health outcomes that should be measured in people living with the condition. To address this gap, we conducted an international consensus study, which included a comprehensive literature review and classification of outcomes for post-COVID-19 condition that informed a two-round online modified Delphi process followed by an online consensus meeting to finalise the core outcome set (COS). 1535 participants from 71 countries were involved, with 1148 individuals participating in both Delphi rounds. Eleven outcomes achieved consensus for inclusion in the final COS: fatigue; pain; post-exertion symptoms; work or occupational and study changes; survival; and functioning, symptoms, and conditions for each of cardiovascular, respiratory, nervous system, cognitive, mental health, and physical outcomes. Recovery was included a priori because it was a relevant outcome that was part of a previously published COS on COVID-19. The next step in this COS development exercise will be to establish the instruments that are most appropriate to measure these core outcomes. This international consensus-based COS should provide a framework for standardised assessment of adults with post-COVID-19 condition, aimed at facilitating clinical care and research worldwide.


Subject(s)
COVID-19 , Adult , COVID-19/complications , Delphi Technique , Humans , Outcome Assessment, Health Care , Research Design , Treatment Outcome
9.
BMJ ; 377: o1321, 2022 05 25.
Article in English | MEDLINE | ID: covidwho-1874539
10.
Lancet Respir Med ; 9(7): 679-680, 2021 07.
Article in English | MEDLINE | ID: covidwho-1747385
11.
Mol Ther ; 30(5): 1801-1809, 2022 05 04.
Article in English | MEDLINE | ID: covidwho-1702807

ABSTRACT

Lessons drawn from successes and failures with coronavirus disease 2019 (COVID-19) and Ebola virus disease (EVD) should help shaping a robust health innovation system for infectious disease epidemics. Epidemic response research and development (R&D) can be mobilized quickly for public health priorities and yield medicinal products within months. However, to resolve epidemics, technological advances must be equitably accessible and deployed, and these examples expose the limitations of a supply-driven, fragmented R&D ecosystem relying primarily on the private sector to deliver health products. Efficient epidemic response requires a coordinated public health-focused, end-to-end R&D ecosystem for the development, registration, availability, and use of pharmaceutical products. Because pivotal clinical trials can only be conducted during outbreaks, significant preparation must be done beforehand: strengthening clinical research capacity and developing pre-positioned trial protocols and clinical characterization protocols, as well as conducting discovery and pre-clinical research, manufacturing, and early clinical testing of candidate products. This will allow for speedy execution of clinical research early into an outbreak and delivering products within a short time. Effective interventions should be adopted and deployed ensuring equitable access during the ongoing outbreak. Measures to make products available where and when needed must be integrated throughout the R&D value chain.


Subject(s)
COVID-19 , Communicable Diseases , Epidemics , Hemorrhagic Fever, Ebola , COVID-19/epidemiology , Ecosystem , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/prevention & control , Humans
12.
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
13.
BMC Med ; 20(1): 50, 2022 02 04.
Article in English | MEDLINE | ID: covidwho-1690914

ABSTRACT

BACKGROUND: A substantial portion of people with COVID-19 subsequently experience lasting symptoms including fatigue, shortness of breath, and neurological complaints such as cognitive dysfunction many months after acute infection. Emerging evidence suggests that this condition, commonly referred to as long COVID but also known as post-acute sequelae of SARS-CoV-2 infection (PASC) or post-COVID-19 condition, could become a significant global health burden. MAIN TEXT: While the number of studies investigating the post-COVID-19 condition is increasing, there is no agreement on how this new disease should be defined and diagnosed in clinical practice and what relevant outcomes to measure. There is an urgent need to optimise and standardise outcome measures for this important patient group both for clinical services and for research and to allow comparing and pooling of data. CONCLUSIONS: A Core Outcome Set for post-COVID-19 condition should be developed in the shortest time frame possible, for improvement in data quality, harmonisation, and comparability between different geographical locations. We call for a global initiative, involving all relevant partners, including, but not limited to, healthcare professionals, researchers, methodologists, patients, and caregivers. We urge coordinated actions aiming to develop a Core Outcome Set (COS) for post-COVID-19 condition in both the adult and paediatric populations.


Subject(s)
COVID-19 , Adult , COVID-19/complications , Child , Disease Progression , Humans , Outcome Assessment, Health Care , SARS-CoV-2
14.
ProQuest Central;
Preprint in English | ProQuest Central | ID: ppcovidwho-328232

ABSTRACT

Although the majority of people with Covid-19 will experience mild to moderate symptoms and will recover fully, there is now increasing evidence that a significant proportion will experience persistent symptoms for months after the acute phase of the illness. These symptoms include, among others, fatigue, problems breathing, lack of smell and taste, headaches, and depression and anxiety. It is also clear the virus has lasting fluctuating multiorgan sequelae, including affecting not only the respiratory system but also the heart, liver, and nervous system. We present a protocol for a living systematic review that aims to synthesize the evidence on the prevalence and characteristics of post-acute COVID-19. The living systematic review will be updated regularly, approximately every 6 months, as new evidence emerges. We will include studies that follow up at least 100 people with Covid-19 at 12 or more weeks post Covid-19 onset, with no restrictions regarding country, setting, or language. We will use descriptive statistics and, for outcomes reported in two or more studies, we will use meta-analyses to estimate prevalence with 95% confidence intervals (CIs) using the exact method. Heterogeneity between estimates will be assessed using the I2 statistic. Our findings will also be presented as infographics to facilitate transcription to lay audiences. Ultimately, we aim to support the work of policy makers, practitioners, and patients when planning rehabilitation for those recovering from Covid-19. The protocol has been registered with PROSPERO (  CRD42020211131, 25/09/2020).

15.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-326233

ABSTRACT

Abstract Background: Recent data suggest that many people experience Post COVID-19 Condition (Long COVID) following the acute phase of the SaRS CoV-2 infection. At present there is no agreement on what patient health outcomes should be measured in Post COVID-19 Condition. We aimed to identify core outcomes for Post COVID-19 Condition that stakeholders considered critical to assess in all research studies and clinical practice. Methods: We conducted a multi-step study: (1) review of outcomes reported in studies of Post COVID-19 Condition to develop a list of potential core outcomes;(2) outcomes were then grouped, using the COMET taxonomy, to present in a consensus process;(3) a two-round online international modified Delphi consensus process, including 3 stakeholder groups (‘people with Post COVID-19 Condition and their carers’, ‘healthcare professionals and researchers’ and ‘healthcare professionals and researchers with Post COVID-19 Condition) to prioritise outcomes;and (4) an international online consensus meeting to finalize the core outcome set. Consensus ‘in’ was defined, a priori, as 80% or more of each stakeholder group rating an outcome as critical (‘7-9’ on a 9-point scale). Patient engagement and global outreach activities were undertaken at all stages of the project. Findings: 1535 participants from 71 countries, representing six continents, were involved in the online modified Delphi process, with 1148 participating in both rounds (75% completion rate). Eleven of 24 outcomes met consensus ‘in’ criteria after the two Delphi rounds and consensus meeting: fatigue or exhaustion;pain;post-exertion symptoms;work/occupational and study changes;survival;and “functioning, symptoms and conditions” for each of the following outcomes: cardiovascular, respiratory, nervous system, cognition, mental and physical. ‘Recovery’ outcome was added ‘a-priori’ as a part of previously published COS on COVID-19. Interpretation: This international study resulted in the development of a COS for Post COVID-19 Condition using a rigorous methodology. The generated consensus-based list of core outcomes should be assessed in clinical research and practice settings. The next step for the development of this COS will be to determine which measurement instruments best measure these outcomes. Funding Information: Funding by the National Institute for Health Research (NIHR) (Grant COV-LT2-0072) supporting the second stage of the process. Declaration of Interests: None to declare.

16.
ERJ open research ; 2021.
Article in English | EuropePMC | ID: covidwho-1610380

ABSTRACT

Due to the large number of patients with severe COVID-19, many were treated outside of the traditional walls of the ICU, and in many cases, by personnel who were not trained in critical care. The clinical characteristics and the relative impact of caring for severe COVID-19 patients outside of the ICU is unknown. This was a multinational, multicentre, prospective cohort study embedded in the ISARIC WHO COVID-19 platform. Severe COVID-19 patients were identified as those admitted to an ICU and/or those treated with one of the following treatments: invasive or non-invasive mechanical ventilation, high-flow nasal cannula, inotropes, and vasopressors. A logistic Generalised Additive Model was used to compare clinical outcomes among patients admitted and not to the ICU. A total of 40 440 patients from 43 countries and six continents were included in this analysis. Severe COVID-19 patients were frequently male (62.9%), older adults (median [IQR], 67 years [55, 78]), and with at least one comorbidity (63.2%). The overall median (IQR) length of hospital stay was 10 days (5–19) and was longer in patients admitted to an ICU than in those that were cared for outside of ICU (12 [6–23] versus 8 [4–15] days, p<0.0001). The 28-day fatality ratio was lower in ICU-admitted patients (30.7% [5797/18831] versus 39.0% [7532/19295], p<0.0001). Patients admitted to an ICU had a significantly lower probability of death than those who were not (adjusted OR:0.70, 95%CI: 0.65-0.75, p<0.0001). Patients with severe COVID-19 admitted to an ICU had significantly lower 28-day fatality ratio than those cared for outside of an ICU.

17.
PLoS Negl Trop Dis ; 15(12): e0010064, 2021 12.
Article in English | MEDLINE | ID: covidwho-1581898

ABSTRACT

BACKGROUND: Among the many collaterals of the COVID-19 pandemic is the disruption of health services and vital clinical research. COVID-19 has magnified the challenges faced in research and threatens to slow research for urgently needed therapeutics for Neglected Tropical Diseases (NTDs) and diseases affecting the most vulnerable populations. Here we explore the impact of the pandemic on a clinical trial for plague therapeutics and strategies that have been considered to ensure research efforts continue. METHODS: To understand the impact of the COVID-19 pandemic on the trial accrual rate, we documented changes in patterns of all-cause consultations that took place before and during the pandemic at health centres in two districts of the Amoron'I Mania region of Madagascar where the trial is underway. We also considered trends in plague reporting and other external factors that may have contributed to slow recruitment. RESULTS: During the pandemic, we found a 27% decrease in consultations at the referral hospital, compared to an 11% increase at peripheral health centres, as well as an overall drop during the months of lockdown. We also found a nation-wide trend towards reduced number of reported plague cases. DISCUSSION: COVID-19 outbreaks are unlikely to dissipate in the near future. Declining NTD case numbers recorded during the pandemic period should not be viewed in isolation or taken as a marker of things to come. It is vitally important that researchers are prepared for a rebound in cases and, most importantly, that research continues to avoid NTDs becoming even more neglected.


Subject(s)
COVID-19 , Health Impact Assessment , Neglected Diseases/drug therapy , Plague/drug therapy , Randomized Controlled Trials as Topic , Research , Tropical Medicine/trends , Disease Notification , Epidemiological Monitoring , Humans , Madagascar/epidemiology , Pandemics , Patient Acceptance of Health Care , Patient Selection , Plague/epidemiology , Referral and Consultation/trends
18.
Elife ; 102021 11 23.
Article in English | MEDLINE | ID: covidwho-1529015

ABSTRACT

Background: There is potentially considerable variation in the nature and duration of the care provided to hospitalised patients during an infectious disease epidemic or pandemic. Improvements in care and clinician confidence may shorten the time spent as an inpatient, or the need for admission to an intensive care unit (ICU) or high dependency unit (HDU). On the other hand, limited resources at times of high demand may lead to rationing. Nevertheless, these variables may be used as static proxies for disease severity, as outcome measures for trials, and to inform planning and logistics. Methods: We investigate these time trends in an extremely large international cohort of 142,540 patients hospitalised with COVID-19. Investigated are: time from symptom onset to hospital admission, probability of ICU/HDU admission, time from hospital admission to ICU/HDU admission, hospital case fatality ratio (hCFR) and total length of hospital stay. Results: Time from onset to admission showed a rapid decline during the first months of the pandemic followed by peaks during August/September and December 2020. ICU/HDU admission was more frequent from June to August. The hCFR was lowest from June to August. Raw numbers for overall hospital stay showed little variation, but there is clear decline in time to discharge for ICU/HDU survivors. Conclusions: Our results establish that variables of these kinds have limitations when used as outcome measures in a rapidly evolving situation. Funding: This work was supported by the UK Foreign, Commonwealth and Development Office and Wellcome [215091/Z/18/Z] and the Bill & Melinda Gates Foundation [OPP1209135]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Subject(s)
Hospitalization/statistics & numerical data , Outcome Assessment, Health Care/statistics & numerical data , SARS-CoV-2/pathogenicity , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/therapy , Child , Child, Preschool , Female , Humans , Infant , Intensive Care Units/statistics & numerical data , Length of Stay/statistics & numerical data , Male , Middle Aged , Retrospective Studies , Young Adult
19.
Thorax ; 77(6): 606-615, 2022 06.
Article in English | MEDLINE | ID: covidwho-1528562

ABSTRACT

PURPOSE: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. METHODS: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. RESULTS: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, -0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. CONCLUSION: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making. TRIAL REGISTRATION NUMBER: ISRCTN66726260.


Subject(s)
COVID-19 , Adolescent , Adult , COVID-19/therapy , Hospital Mortality , Humans , Observational Studies as Topic , Prognosis , SARS-CoV-2 , State Medicine , World Health Organization
20.
BMJ Glob Health ; 6(9)2021 09.
Article in English | MEDLINE | ID: covidwho-1440817

ABSTRACT

BACKGROUND: While it is now apparent clinical sequelae (long COVID) may persist after acute COVID-19, their nature, frequency and aetiology are poorly characterised. This study aims to regularly synthesise evidence on long COVID characteristics, to help inform clinical management, rehabilitation strategies and interventional studies to improve long-term outcomes. METHODS: A living systematic review. Medline, CINAHL (EBSCO), Global Health (Ovid), WHO Global Research on COVID-19 database, LitCovid and Google Scholar were searched till 17 March 2021. Studies including at least 100 people with confirmed or clinically suspected COVID-19 at 12 weeks or more post onset were included. Risk of bias was assessed using the tool produced by Hoy et al. Results were analysed using descriptive statistics and meta-analyses to estimate prevalence. RESULTS: A total of 39 studies were included: 32 cohort, 6 cross-sectional and 1 case-control. Most showed high or moderate risk of bias. None were set in low-income countries and few included children. Studies reported on 10 951 people (48% female) in 12 countries. Most included previously hospitalised people (78%, 8520/10 951). The longest mean follow-up time was 221.7 (SD: 10.9) days post COVID-19 onset. Over 60 physical and psychological signs and symptoms with wide prevalence were reported, most commonly weakness (41%; 95% CI 25% to 59%), general malaise (33%; 95% CI 15% to 57%), fatigue (31%; 95% CI 24% to 39%), concentration impairment (26%; 95% CI 21% to 32%) and breathlessness (25%; 95% CI 18% to 34%). 37% (95% CI 18% to 60%) of patients reported reduced quality of life; 26% (10/39) of studies presented evidence of reduced pulmonary function. CONCLUSION: Long COVID is a complex condition with prolonged heterogeneous symptoms. The nature of studies precludes a precise case definition or risk evaluation. There is an urgent need for prospective, robust, standardised, controlled studies into aetiology, risk factors and biomarkers to characterise long COVID in different at-risk populations and settings. PROSPERO REGISTRATION NUMBER: CRD42020211131.


Subject(s)
COVID-19 , Quality of Life , COVID-19/complications , Child , Cross-Sectional Studies , Female , Humans , Male , Prospective Studies , SARS-CoV-2
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