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 and 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 not 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.
Original language | English |
---|---|
Pages (from-to) | 1040-1050 |
Number of pages | 11 |
Journal | Influenza and Other Respiratory Viruses |
Volume | 16 |
Issue number | 6 |
DOIs | |
Publication status | Published - Nov 2022 |
Externally published | Yes |
Keywords
- case definitions
- COVID-19
- hospitalisation
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver
}
In: Influenza and Other Respiratory Viruses, Vol. 16, No. 6, 11.2022, p. 1040-1050.
Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Symptom-based case definitions for COVID-19
T2 - Time and geographical variations for detection at hospital admission among 260,000 patients
AU - Baruch, Joaquin
AU - Rojek, Amanda
AU - Kartsonaki, Christiana
AU - Vijayaraghavan, Bharath K.T.
AU - Gonçalves, Bronner P.
AU - Pritchard, Mark G.
AU - Merson, Laura
AU - Dunning, Jake
AU - Hall, Matthew
AU - Sigfrid, Louise
AU - Citarella, Barbara W.
AU - Murthy, Srinivas
AU - Yeabah, Trokon O.
AU - Olliaro, Piero
AU - Abbas, Ali
AU - Abdukahil, Sheryl Ann
AU - Abdulkadir, Nurul Najmee
AU - Abe, Ryuzo
AU - Abel, Laurent
AU - Absil, Lara
AU - Acharya, Subhash
AU - Acker, Andrew
AU - Adam, Elisabeth
AU - Adrião, Diana
AU - Al Ageel, Saleh
AU - Ahmed, Shakeel
AU - Ainscough, Kate
AU - Airlangga, Eka
AU - Aisa, Tharwat
AU - Hssain, Ali Ait
AU - Tamlihat, Younes Ait
AU - Akimoto, Takako
AU - Akmal, Ernita
AU - Al Qasim, Eman
AU - Alalqam, Razi
AU - Alberti, Angela
AU - Al-dabbous, Tala
AU - Alegesan, Senthilkumar
AU - Alegre, Cynthia
AU - Alessi, Marta
AU - Alex, Beatrice
AU - Alexandre, Kévin
AU - Al-Fares, Abdulrahman
AU - Alfoudri, Huda
AU - Ali, Imran
AU - Ali, Adam
AU - Shah, Naseem Ali
AU - Alidjnou, Kazali Enagnon
AU - Aliudin, Jeffrey
AU - Alkhafajee, Qabas
AU - Allavena, Clotilde
AU - Allou, Nathalie
AU - Altaf, Aneela
AU - Alves, João Melo
AU - Alves, Rita
AU - Alves, João Melo
AU - Amaral, Maria
AU - Amira, Nur
AU - Ampaw, Phoebe
AU - Andini, Roberto
AU - Andréjak, Claire
AU - Angheben, Andrea
AU - Angoulvant, François
AU - Ansart, Séverine
AU - Anthonidass, Sivanesen
AU - Antonelli, Massimo
AU - de Brito, Carlos Alexandre Antunes
AU - Apriyana, Ardiyan
AU - Arabi, Yaseen
AU - Aragao, Irene
AU - Araujo, Carolline
AU - Arcadipane, Antonio
AU - Archambault, Patrick
AU - Arenz, Lukas
AU - Arlet, Jean Benoît
AU - Arora, Lovkesh
AU - Arora, Rakesh
AU - Artaud-Macari, Elise
AU - Aryal, Diptesh
AU - Asensio, Angel
AU - Ashraf, Muhammad
AU - Asif, Namra
AU - Asim, Mohammad
AU - Assie, Jean Baptiste
AU - Asyraf, Amirul
AU - Atique, Anika
AU - Attanyake, A. M.Udara Lakshan
AU - Auchabie, Johann
AU - Aumaitre, Hugues
AU - Auvet, Adrien
AU - Axelsen, Eyvind W.
AU - Azemar, Laurène
AU - Azoulay, Cecile
AU - Bach, Benjamin
AU - Bachelet, Delphine
AU - Badr, Claudine
AU - Bævre-Jensen, Roar
AU - Baig, Nadia
AU - Baillie, J. Kenneth
AU - Baird, J. Kevin
AU - Bak, Erica
AU - Bakakos, Agamemnon
AU - Bakar, Nazreen Abu
AU - Bal, Andriy
AU - Balakrishnan, Mohanaprasanth
AU - Balan, Valeria
AU - Bani-Sadr, Firouzé
AU - Barbalho, Renata
AU - Barbosa, Nicholas Yuri
AU - Barclay, Wendy S.
AU - Barnett, Saef Umar
AU - Barnikel, Michaela
AU - Barrasa, Helena
AU - Barrelet, Audrey
AU - Barrigoto, Cleide
AU - Bartoli, Marie
AU - Baruch, Joaquín
AU - Bashir, Mustehan
AU - Basmaci, Romain
AU - Basri, Muhammad Fadhli Hassin
AU - Battaglini, Denise
AU - Bauer, Jules
AU - Rincon, Diego Fernando Bautista
AU - Dow, Denisse Bazan
AU - Beane, Abigail
AU - Bedossa, Alexandra
AU - Bee, Ker Hong
AU - Begum, Husna
AU - Behilill, Sylvie
AU - Beishuizen, Albertus
AU - Beljantsev, Aleksandr
AU - Bellemare, David
AU - Beltrame, Anna
AU - Beltrão, Beatriz Amorim
AU - Beluze, Marine
AU - Benech, Nicolas
AU - Benjiman, Lionel Eric
AU - Benkerrou, Dehbia
AU - Bennett, Suzanne
AU - Bento, Luís
AU - Berdal, Jan Erik
AU - Bergeaud, Delphine
AU - Bergin, Hazel
AU - Sobrino, José Luis Bernal
AU - Bertoli, Giulia
AU - Bertolino, Lorenzo
AU - Bessis, Simon
AU - Bevilcaqua, Sybille
AU - Bezulier, Karine
AU - Bhatt, Amar
AU - Bhavsar, Krishna
AU - Bianco, Claudia
AU - Bidin, Farah Nadiah
AU - Singh, Moirangthem Bikram
AU - Humaid, Felwa Bin
AU - Kamarudin, Mohd Nazlin Bin
AU - Bissuel, François
AU - Bitker, Laurent
AU - Bitton, Jonathan
AU - Blanco-Schweizer, Pablo
AU - Blier, Catherine
AU - Bloos, Frank
AU - Blot, Mathieu
AU - Boccia, Filomena
AU - Bodenes, Laetitia
AU - Bogaarts, Alice
AU - Bogaert, Debby
AU - Boivin, Anne Hélène
AU - Bolze, Pierre Adrien
AU - Bompart, François
AU - Bonfasius, Aurelius
AU - Borges, Diogo
AU - Borie, Raphaël
AU - Bosse, Hans Martin
AU - Botelho-Nevers, Elisabeth
AU - Bouadma, Lila
AU - Bouchaud, Olivier
AU - Bouchez, Sabelline
AU - Bouhmani, Dounia
AU - Bouhour, Damien
AU - Bouiller, Kévin
AU - Bouillet, Laurence
AU - Bouisse, Camile
AU - Boureau, Anne Sophie
AU - Bourke, John
AU - Bouscambert, Maude
AU - Bousquet, Aurore
AU - Bouziotis, Jason
AU - Boxma, Bianca
AU - Boyer-Besseyre, Marielle
AU - Boylan, Maria
AU - Bozza, Fernando Augusto
AU - Braconnier, Axelle
AU - Braga, Cynthia
AU - Brandenburger, Timo
AU - Monteiro, Filipa Brás
AU - Brazzi, Luca
AU - Breen, Patrick
AU - Breen, Dorothy
AU - Breen, Patrick
AU - Brickell, Kathy
AU - Browne, Shaunagh
AU - Browne, Alex
AU - Brozzi, Nicolas
AU - Brunvoll, Sonja Hjellegjerde
AU - Brusse-Keizer, Marjolein
AU - Buchtele, Nina
AU - Buesaquillo, Christian
AU - Bugaeva, Polina
AU - Buisson, Marielle
AU - Buonsenso, Danilo
AU - Burhan, Erlina
AU - Burrell, Aidan
AU - Bustos, Ingrid G.
AU - Butnaru, Denis
AU - Cabie, André
AU - Cabral, Susana
AU - Caceres, Eder
AU - Cadoz, Cyril
AU - Calligy, Kate
AU - Calvache, Jose Andres
AU - Camões, João
AU - Campana, Valentine
AU - Campbell, Paul
AU - Campisi, Josie
AU - Canepa, Cecilia
AU - Cantero, Mireia
AU - Caraux-Paz, Pauline
AU - Cárcel, Sheila
AU - Cardellino, Chiara Simona
AU - Cardoso, Sofia
AU - Cardoso, Filipe
AU - Cardoso, Filipa
AU - Cardoso, Nelson
AU - Carelli, Simone
AU - Carlier, Nicolas
AU - Carmoi, Thierry
AU - Carney, Gayle
AU - Carqueja, Inês
AU - Carret, Marie Christine
AU - Carrier, François Martin
AU - Carroll, Ida
AU - Carson, Gail
AU - McArthur, Colin
AU - Nichol, Alistair
AU - Parke, Rachael
AU - Neto, Ary Serpa
AU - Trapani, Tony
AU - Udy, Andrew
AU - Webb, Steve
AU - ISARIC Clinical Characterisation Group
N1 - Funding Information: This work was made possible by the UK Foreign, Commonwealth and Development Office; Wellcome Trust (215091/Z/18/Z, 205228/Z/16/Z, 220757/Z/20/Z); Bill and Melinda Gates Foundation (OPP1209135); the philanthropic support of the donors to the University of Oxford's COVID‐19 Research Response Fund (0009109); CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and the co‐ordination in Canada by Sunnybrook Research Institute; endorsement of the Irish Critical Care‐Clinical Trials Group, co‐ordination in Ireland by the Irish Critical Care‐Clinical Trials Network at University College Dublin and funding by the Health Research Board of Ireland (CTN‐2014‐12); the Rapid European COVID‐19 Emergency Response research (RECOVER) (H2020 project 101003589) and European Clinical Research Alliance on Infectious Diseases (ECRAID) (965313); the COVID Clinical Management Team, AIIMS, Rishikesh, India; the COVID‐19 Clinical Management Team, Manipal Hospital Whitefield, Bengaluru, India; Cambridge NIHR Biomedical Research Centre; the dedication and hard work of the Groote Schuur Hospital Covid ICU Team; the Liverpool School of Tropical Medicine and the University of Oxford; the dedication and hard work of the Norwegian SARS‐CoV‐2 Study Team; the Research Council of Norway Grant No. 312780 and a philanthropic donation from Vivaldi Invest A/S owned by Jon Stephenson von Tetzchner; Imperial NIHR Biomedical Research Centre; the Comprehensive Local Research Networks (CLRNs) of which PJMO is an NIHR Senior Investigator (NIHR201385); Innovative Medicines Initiative Joint Undertaking under Grant Agreement No. 115523 COMBACTE, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007‐2013) and EFPIA companies, in‐kind contribution; the French COVID cohort (NCT04262921) is sponsored by INSERM and is funded by the REACTing (REsearch & ACtion emergING infectious diseases) Consortium and by a grant of the French Ministry of Health (PHRC No. 20‐0424); Stiftungsfonds zur Förderung der Bekämpfung der Tuberkulose und anderer Lungenkrankheiten of the City of Vienna, Project Number: APCOV22BGM; Italian Ministry of Health ‘Fondi Ricerca corrente–L1P6’ to IRCCS Ospedale Sacro Cuore–Don Calabria; Australian Department of Health grant (3273191); Gender Equity Strategic Fund at University of Queensland, Artificial Intelligence for Pandemics (A14PAN) at University of Queensland, the Australian Research Council Centre of Excellence for Engineered Quantum Systems (EQUS, CE170100009) and the Prince Charles Hospital Foundation, Australia; grants from Instituto de Salud Carlos III, Ministerio de Ciencia, Spain; Brazil, National Council for Scientific and Technological Development Scholarship Number 303953/2018‐7; the Firland Foundation, Shoreline, Washington, USA; a grant from foundation Bevordering Onderzoek Franciscus; the South Eastern Norway Health Authority and the Research Council of Norway; Institute for Clinical Research (ICR), National Institutes of Health (NIH) supported by the Ministry of Health Malaysia; and preparedness work conducted by the Short Period Incidence Study of Severe Acute Respiratory Infection. Funding Information: This work uses data provided by patients and collected by the NHS as part of their care and support #DataSavesLives. The data used for this research were obtained from ISARIC4C. We are extremely grateful to the 2648 frontline NHS clinical and research staff and volunteer medical students who collected these data in challenging circumstances and the generosity of the patients and their families for their individual contributions in these difficult times. The COVID‐19 Clinical Information Network (CO‐CIN) data were collated by ISARIC4C Investigators. Data and Material provision was 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 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 ISBRC‐1215‐20013) and NIHR Clinical Research Network providing infrastructure support. We also acknowledge the support of Jeremy J. Farrar and Nahoko Shindo. Publisher Copyright: © 2022 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd.
PY - 2022/11
Y1 - 2022/11
N2 - 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 and 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 not 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.
AB - 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 and 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 not 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.
KW - case definitions
KW - COVID-19
KW - hospitalisation
UR - http://www.scopus.com/inward/record.url?scp=85137461238&partnerID=8YFLogxK
U2 - 10.1111/irv.13039
DO - 10.1111/irv.13039
M3 - Article
AN - SCOPUS:85137461238
SN - 1750-2640
VL - 16
SP - 1040
EP - 1050
JO - Influenza and Other Respiratory Viruses
JF - Influenza and Other Respiratory Viruses
IS - 6
ER -