External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact.


Journal

Annals of medicine
ISSN: 1365-2060
Titre abrégé: Ann Med
Pays: England
ID NLM: 8906388

Informations de publication

Date de publication:
12 2023
Historique:
medline: 14 4 2023
entrez: 13 4 2023
pubmed: 14 4 2023
Statut: ppublish

Résumé

Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis. Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method. Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81-5.30, The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study. Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory featuresIn this study, we externally confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignmentThis could indirectly support the validity of both phenotype’s development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics.

Sections du résumé

BACKGROUND
Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis.
METHODS
Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method.
RESULTS
Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81-5.30,
CONCLUSIONS
The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.
Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory featuresIn this study, we externally confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignmentThis could indirectly support the validity of both phenotype’s development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics.

Autres résumés

Type: plain-language-summary (eng)
Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory featuresIn this study, we externally confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignmentThis could indirectly support the validity of both phenotype’s development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics.

Identifiants

pubmed: 37052252
doi: 10.1080/07853890.2023.2195204
pmc: PMC10116925
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2195204

Références

Nat Rev Immunol. 2021 Oct;21(10):626-636
pubmed: 34373623
PLoS One. 2021 Mar 31;16(3):e0248956
pubmed: 33788884
J Clin Epidemiol. 2022 Nov;151:185-188
pubmed: 36150546
EBioMedicine. 2022 Sep;83:104208
pubmed: 35952496
Lancet Infect Dis. 2021 Jun;21(6):783-792
pubmed: 33636145
Respir Physiol Neurobiol. 2020 Aug;279:103455
pubmed: 32437877
Front Med (Lausanne). 2021 Mar 11;8:632933
pubmed: 33777977
Clin Microbiol Infect. 2020 Nov;26(11):1537-1544
pubmed: 32810610
Eur Respir J. 2020 May 21;55(5):
pubmed: 32341111
N Engl J Med. 2022 Mar 10;386(10):933-941
pubmed: 35020982
Infect Drug Resist. 2021 Sep 21;14:3865-3871
pubmed: 34584430

Auteurs

Daniele Roberto Giacobbe (DR)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Emilio Di Maria (E)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
University Unit of Medical Genetics, Galliera Hospital, Genoa, Italy.

Alberto Stefano Tagliafico (AS)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Martina Bavastro (M)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Carlo Simone Trombetta (CS)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Hygiene Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Cristina Marelli (C)

Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Gabriele Di Meco (G)

Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Greta Cattardico (G)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Sara Mora (S)

Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.

Alessio Signori (A)

Section of Biostatistics, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.

Antonio Vena (A)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Malgorzata Mikulska (M)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Chiara Dentone (C)

Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Bianca Bruzzone (B)

Hygiene Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Bianca Bignotti (B)

Department of Radiology, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Department of Experimental Medicine (DIMES), University of Genoa, Genoa, Italy.

Andrea Orsi (A)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Hygiene Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Chiara Robba (C)

Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy.
Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Lorenzo Ball (L)

Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy.
Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Iole Brunetti (I)

Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Denise Battaglini (D)

Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Antonio Di Biagio (A)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Maria Pia Sormani (MP)

Section of Biostatistics, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.

Paolo Pelosi (P)

Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy.
Anesthesia and Intensive Care, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Mauro Giacomini (M)

Department of Informatics, Bioengineering, Robotics and System Engineering (DIBRIS), University of Genoa, Genoa, Italy.

Giancarlo Icardi (G)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Hygiene Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Matteo Bassetti (M)

Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Clinica Malattie Infettive, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH