Potential pitfalls in the use of real-world data for studying long COVID

The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)

doi:10.1038/s41591-023-02274-y

Potential pitfalls in the use of real-world data for studying long COVID

The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)

Department of Information Management

Research output: Contribution to journal › Journal Letter › peer-review

20 Scopus citations

Original language	English
Pages (from-to)	1040-1043
Number of pages	4
Journal	Nature Medicine
Volume	29
Issue number	5
DOIs	https://doi.org/10.1038/s41591-023-02274-y
State	Published - 05 2023

Keywords

Humans
COVID-19
Post-Acute COVID-19 Syndrome
Research

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10.1038/s41591-023-02274-y

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@article{77a70c29ad444994a9e637dcc16a1f65,

title = "Potential pitfalls in the use of real-world data for studying long COVID",

keywords = "Humans, COVID-19, Post-Acute COVID-19 Syndrome, Research",

author = "\{The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)\} and Zhang, \{Harrison G.\} and Honerlaw, \{Jacqueline P.\} and Monika Maripuri and Samayamuthu, \{Malarkodi Jebathilagam\} and Beaulieu-Jones, \{Brendin R.\} and Baig, \{Huma S.\} and Sehi L{\textquoteright}Yi and Ho, \{Yuk Lam\} and Michele Morris and Panickan, \{Vidul Ayakulangara\} and Xuan Wang and Weber, \{Griffin M.\} and Liao, \{Katherine P.\} and Shyam Visweswaran and Tan, \{Bryce W.Q.\} and William Yuan and Nils Gehlenborg and Sumitra Muralidhar and Ramoni, \{Rachel B.\} and Aaron, \{James R.\} and Giuseppe Agapito and Adem Albayrak and Giuseppe Albi and Mario Alessiani and Anna Alloni and Amendola, \{Danilo F.\} and Fran{\c c}ois Angoulvant and Anthony, \{Li L.L.J.\} and Aronow, \{Bruce J.\} and Fatima Ashraf and Andrew Atz and Paul Avillach and Azevedo, \{Paula S.\} and James Balshi and Beaulieu-Jones, \{Brett K.\} and Bell, \{Douglas S.\} and Antonio Bellasi and Riccardo Bellazzi and Vincent Benoit and Michele Beraghi and Bernal-Sobrino, \{Jos{\'e} Luis\} and M{\'e}lodie Bernaux and Romain Bey and Surbhi Bhatnagar and Alvar Blanco-Mart{\'i}nez and Bonzel, \{Clara Lea\} and John Booth and Silvano Bosari and Bourgeois, \{Florence T.\} and Tseng, \{Yi Ju\}",

year = "2023",

month = may,

doi = "10.1038/s41591-023-02274-y",

language = "英语",

volume = "29",

pages = "1040--1043",

journal = "Nature Medicine",

issn = "1078-8956",

publisher = "Nature Research",

number = "5",

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T1 - Potential pitfalls in the use of real-world data for studying long COVID

AU - The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)

AU - Zhang, Harrison G.

AU - Honerlaw, Jacqueline P.

AU - Maripuri, Monika

AU - Samayamuthu, Malarkodi Jebathilagam

AU - Beaulieu-Jones, Brendin R.

AU - Baig, Huma S.

AU - L’Yi, Sehi

AU - Ho, Yuk Lam

AU - Morris, Michele

AU - Panickan, Vidul Ayakulangara

AU - Wang, Xuan

AU - Weber, Griffin M.

AU - Liao, Katherine P.

AU - Visweswaran, Shyam

AU - Tan, Bryce W.Q.

AU - Yuan, William

AU - Gehlenborg, Nils

AU - Muralidhar, Sumitra

AU - Ramoni, Rachel B.

AU - Aaron, James R.

AU - Agapito, Giuseppe

AU - Albayrak, Adem

AU - Albi, Giuseppe

AU - Alessiani, Mario

AU - Alloni, Anna

AU - Amendola, Danilo F.

AU - Angoulvant, François

AU - Anthony, Li L.L.J.

AU - Aronow, Bruce J.

AU - Ashraf, Fatima

AU - Atz, Andrew

AU - Avillach, Paul

AU - Azevedo, Paula S.

AU - Balshi, James

AU - Beaulieu-Jones, Brett K.

AU - Bell, Douglas S.

AU - Bellasi, Antonio

AU - Bellazzi, Riccardo

AU - Benoit, Vincent

AU - Beraghi, Michele

AU - Bernal-Sobrino, José Luis

AU - Bernaux, Mélodie

AU - Bey, Romain

AU - Bhatnagar, Surbhi

AU - Blanco-Martínez, Alvar

AU - Bonzel, Clara Lea

AU - Booth, John

AU - Bosari, Silvano

AU - Bourgeois, Florence T.

AU - Tseng, Yi Ju

PY - 2023/5

Y1 - 2023/5

KW - Humans

KW - COVID-19

KW - Post-Acute COVID-19 Syndrome

KW - Research

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DO - 10.1038/s41591-023-02274-y

M3 - 快报

C2 - 37055567

AN - SCOPUS:85152697250

SN - 1078-8956

VL - 29

SP - 1040

EP - 1043

JO - Nature Medicine

JF - Nature Medicine

IS - 5

ER -

Potential pitfalls in the use of real-world data for studying long COVID

Keywords

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